Source code for galaxy.datatypes.images

"""
Image classes
"""

import base64
import json
import logging
from typing import Optional

import mrcfile
import numpy as np
import tifffile

from galaxy.datatypes.binary import Binary
from galaxy.datatypes.metadata import (
    FileParameter,
    MetadataElement,
)
from galaxy.datatypes.protocols import (
    DatasetProtocol,
    HasExtraFilesAndMetadata,
)
from galaxy.datatypes.sniff import (
    build_sniff_from_prefix,
    FilePrefix,
)
from galaxy.datatypes.text import Html as HtmlFromText
from galaxy.util import nice_size
from galaxy.util.image_util import check_image_type
from . import data
from .xml import GenericXml

log = logging.getLogger(__name__)

# TODO: Uploading image files of various types is supported in Galaxy, but on
# the main public instance, the display_in_upload is not set for these data
# types in datatypes_conf.xml because we do not allow image files to be uploaded
# there.  There is currently no API feature that allows uploading files outside
# of a data library ( where it requires either the upload_paths or upload_directory
# option to be enabled, which is not the case on the main public instance ).  Because
# of this, we're currently safe, but when the api is enhanced to allow other uploads,
# we need to ensure that the implementation is such that image files cannot be uploaded
# to our main public instance.


[docs]class Image(data.Data):
    """Class describing an image"""

    edam_data = "data_2968"
    edam_format = "format_3547"
    file_ext = ""

[docs]    def __init__(self, **kwd):
        super().__init__(**kwd)
        self.image_formats = [self.file_ext.upper()]

[docs]    def set_peek(self, dataset: DatasetProtocol, **kwd) -> None:
        if not dataset.dataset.purged:
            dataset.peek = f"Image in {dataset.extension} format"
            dataset.blurb = nice_size(dataset.get_size())
        else:
            dataset.peek = "file does not exist"
            dataset.blurb = "file purged from disk"

[docs]    def sniff(self, filename: str) -> bool:
        """Determine if the file is in this format"""
        return check_image_type(filename, self.image_formats)

[docs]    def handle_dataset_as_image(self, hda: DatasetProtocol) -> str:
        dataset = hda.dataset
        name = hda.name or ""
        with open(dataset.get_file_name(), "rb") as f:
            base64_image_data = base64.b64encode(f.read()).decode("utf-8")
        return f"![{name}](data:image/{self.file_ext};base64,{base64_image_data})"


[docs]class Jpg(Image):
    edam_format = "format_3579"
    file_ext = "jpg"

[docs]    def __init__(self, **kwd):
        super().__init__(**kwd)
        self.image_formats = ["JPEG"]


[docs]class Png(Image):
    edam_format = "format_3603"
    file_ext = "png"


[docs]class Tiff(Image):
    edam_format = "format_3591"
    file_ext = "tiff"
    MetadataElement(
        name="offsets",
        desc="Offsets File",
        param=FileParameter,
        file_ext="json",
        readonly=True,
        visible=False,
        optional=True,
    )

[docs]    def set_meta(
        self, dataset: DatasetProtocol, overwrite: bool = True, metadata_tmp_files_dir: Optional[str] = None, **kwd
    ) -> None:
        spec_key = "offsets"
        offsets_file = dataset.metadata.offsets
        if not offsets_file:
            offsets_file = dataset.metadata.spec[spec_key].param.new_file(
                dataset=dataset, metadata_tmp_files_dir=metadata_tmp_files_dir
            )
        with tifffile.TiffFile(dataset.get_file_name()) as tif:
            offsets = [page.offset for page in tif.pages]
        with open(offsets_file.get_file_name(), "w") as f:
            json.dump(offsets, f)
        dataset.metadata.offsets = offsets_file


[docs]class OMETiff(Tiff):
    file_ext = "ome.tiff"

[docs]    def sniff(self, filename: str) -> bool:
        with tifffile.TiffFile(filename) as tif:
            if tif.is_ome:
                return True
        return False


[docs]class Hamamatsu(Image):
    file_ext = "vms"


[docs]class Mirax(Image):
    file_ext = "mrxs"


[docs]class Sakura(Image):
    file_ext = "svslide"


[docs]class Nrrd(Image):
    file_ext = "nrrd"


[docs]class Bmp(Image):
    edam_format = "format_3592"
    file_ext = "bmp"


[docs]class Gif(Image):
    edam_format = "format_3467"
    file_ext = "gif"


[docs]class Im(Image):
    edam_format = "format_3593"
    file_ext = "im"


[docs]class Pcd(Image):
    edam_format = "format_3594"
    file_ext = "pcd"


[docs]class Pcx(Image):
    edam_format = "format_3595"
    file_ext = "pcx"


[docs]class Ppm(Image):
    edam_format = "format_3596"
    file_ext = "ppm"


[docs]class Psd(Image):
    edam_format = "format_3597"
    file_ext = "psd"


[docs]class Xbm(Image):
    edam_format = "format_3598"
    file_ext = "xbm"


[docs]class Xpm(Image):
    edam_format = "format_3599"
    file_ext = "xpm"


[docs]class Rgb(Image):
    edam_format = "format_3600"
    file_ext = "rgb"


[docs]class Pbm(Image):
    edam_format = "format_3601"
    file_ext = "pbm"


[docs]class Pgm(Image):
    edam_format = "format_3602"
    file_ext = "pgm"


[docs]class Eps(Image):
    edam_format = "format_3466"
    file_ext = "eps"


[docs]class Rast(Image):
    edam_format = "format_3605"
    file_ext = "rast"


[docs]class Pdf(Image):
    edam_format = "format_3508"
    file_ext = "pdf"

[docs]    def sniff(self, filename: str) -> bool:
        """Determine if the file is in pdf format."""
        with open(filename, "rb") as fh:
            return fh.read(4) == b"%PDF"


[docs]@build_sniff_from_prefix
class Tck(Binary):
    """
    Tracks file format (.tck) format
    https://mrtrix.readthedocs.io/en/latest/getting_started/image_data.html#tracks-file-format-tck

    >>> from galaxy.datatypes.sniff import get_test_fname
    >>> fname = get_test_fname('fibers_sparse_top_6_lines.tck')
    >>> Tck().sniff( fname )
    True
    >>> fname = get_test_fname('2.txt')
    >>> Tck().sniff( fname )
    False
    """

    file_ext = "tck"

[docs]    def sniff_prefix(self, file_prefix: FilePrefix) -> bool:
        format_def = [
            [b"mrtrix tracks"],
            [b"datatype: Float32LE", b"datatype: Float32BE", b"datatype: Float64BE", b"datatype: Float64LE"],
            [b"count: "],
            [b"file: ."],
            [b"END"],
        ]
        matches = 0

        for elem in format_def:
            for identifier in elem:
                if identifier in file_prefix.contents_header_bytes:
                    matches += 1
        if matches == 5:
            return True
        return False


[docs]@build_sniff_from_prefix
class Trk(Binary):
    """
    Track File format (.trk) is the tractography file format.
    http://trackvis.org/docs/?subsect=fileformat

    >>> from galaxy.datatypes.sniff import get_test_fname
    >>> fname = get_test_fname('IIT2mean_top_2000bytes.trk')
    >>> Trk().sniff( fname )
    True
    >>> fname = get_test_fname('2.txt')
    >>> Trk().sniff( fname )
    False
    """

    file_ext = "trk"

[docs]    def sniff_prefix(self, file_prefix: FilePrefix) -> bool:
        # quick check
        header_raw = None
        header_raw = file_prefix.contents_header_bytes[:1000]

        if header_raw[:5] != b"TRACK":
            return False
        # detailed check
        header_def = [
            ("magic", "S6"),
            ("dim", "h", 3),
            ("voxel_size", "f4", 3),
            ("origin", "f4", 3),
            ("n_scalars", "h"),
            ("scalar_name", "S20", 10),
            ("n_properties", "h"),
            ("property_name", "S20", 10),
            ("vox_to_ras", "f4", (4, 4)),
            ("reserved", "S444"),
            ("voxel_order", "S4"),
            ("pad2", "S4"),
            ("image_orientation_patient", "f4", 6),
            ("pad1", "S2"),
            ("invert_x", "S1"),
            ("invert_y", "S1"),
            ("invert_z", "S1"),
            ("swap_xy", "S1"),
            ("swap_yz", "S1"),
            ("swap_zx", "S1"),
            ("n_count", "i4"),
            ("version", "i4"),
            ("header_size", "i4"),
        ]
        np_dtype = np.dtype(header_def)
        header: np.ndarray = np.ndarray(shape=(), dtype=np_dtype, buffer=header_raw)
        if (
            header["header_size"] == 1000
            and b"TRACK" in header["magic"]
            and header["version"] == 2
            and len(header["dim"]) == 3
        ):
            return True
        return False


[docs]class Mrc2014(Binary):
    """
    MRC/CCP4 2014 file format (.mrc).
    https://www.ccpem.ac.uk/mrc_format/mrc2014.php

    >>> from galaxy.datatypes.sniff import get_test_fname
    >>> fname = get_test_fname('1.mrc')
    >>> Mrc2014().sniff(fname)
    True
    >>> fname = get_test_fname('2.txt')
    >>> Mrc2014().sniff(fname)
    False
    """

    file_ext = "mrc"

[docs]    def sniff(self, filename: str) -> bool:
        try:
            # An exception is thrown
            # if the file is not an
            # mrc2014 file.
            mrcfile.load_functions.open(filename, header_only=True)
            return True
        except Exception:
            return False


[docs]class Gmaj(data.Data):
    """Deprecated class. Exists for limited backwards compatibility."""

    edam_format = "format_3547"
    file_ext = "gmaj.zip"

[docs]    def get_mime(self) -> str:
        """Returns the mime type of the datatype"""
        return "application/zip"


[docs]class Analyze75(Binary):
    """
    Mayo Analyze 7.5 files
    http://www.imzml.org
    """

    file_ext = "analyze75"
    composite_type = "auto_primary_file"

[docs]    def __init__(self, **kwd):
        super().__init__(**kwd)

        # The header file provides information about dimensions, identification,
        # and processing history.
        self.add_composite_file("hdr", description="The Analyze75 header file.", is_binary=True)

        # The image file contains the actual data, whose data type and ordering
        # are described by the header file.
        self.add_composite_file("img", description="The Analyze75 image file.", is_binary=True)

        self.add_composite_file("t2m", description="The Analyze75 t2m file.", optional=True, is_binary=True)

[docs]    def generate_primary_file(self, dataset: HasExtraFilesAndMetadata) -> str:
        rval = ["<html><head><title>Analyze75 Composite Dataset.</title></head><p/>"]
        rval.append("<div>This composite dataset is composed of the following files:<p/><ul>")
        for composite_name, composite_file in self.get_composite_files(dataset=dataset).items():
            fn = composite_name
            opt_text = ""
            if composite_file.optional:
                opt_text = " (optional)"
            if composite_file.get("description"):
                rval.append(
                    f"<li><a href=\"{fn}\" type=\"text/plain\">{fn} ({composite_file.get('description')})</a>{opt_text}</li>"
                )
            else:
                rval.append(f'<li><a href="{fn}" type="text/plain">{fn}</a>{opt_text}</li>')
        rval.append("</ul></div></html>")
        return "\n".join(rval)


[docs]@build_sniff_from_prefix
class Nifti1(Binary):
    """
    Nifti1 format
    https://nifti.nimh.nih.gov/pub/dist/src/niftilib/nifti1.h

    >>> from galaxy.datatypes.sniff import get_test_fname
    >>> fname = get_test_fname('T1_top_350bytes.nii1')
    >>> Nifti1().sniff( fname )
    True
    >>> fname = get_test_fname('2.txt')
    >>> Nifti1().sniff( fname )
    False
    """

    file_ext = "nii1"

[docs]    def sniff_prefix(self, file_prefix: FilePrefix) -> bool:
        magic = file_prefix.contents_header_bytes[344:348]
        if magic == b"n+1\0":
            return True
        return False


[docs]@build_sniff_from_prefix
class Nifti2(Binary):
    """
    Nifti2 format
    https://brainder.org/2015/04/03/the-nifti-2-file-format/

    >>> from galaxy.datatypes.sniff import get_test_fname
    >>> fname = get_test_fname('avg152T1_LR_nifti2_top_100bytes.nii2')
    >>> Nifti2().sniff( fname )
    True
    >>> fname = get_test_fname('T1_top_350bytes.nii1')
    >>> Nifti2().sniff( fname )
    False
    """

    file_ext = "nii2"

[docs]    def sniff_prefix(self, file_prefix: FilePrefix) -> bool:
        magic = file_prefix.contents_header_bytes[4:8]
        if magic in [b"n+2\0", b"ni2\0"]:
            return True
        return False


[docs]@build_sniff_from_prefix
class Gifti(GenericXml):
    """Class describing a Gifti format"""

    file_ext = "gii"

[docs]    def sniff_prefix(self, file_prefix: FilePrefix) -> bool:
        """Determines whether the file is a Gifti file

        >>> from galaxy.datatypes.sniff import get_test_fname
        >>> fname = get_test_fname('Human.colin.R.activations.label.gii')
        >>> Gifti().sniff(fname)
        True
        >>> fname = get_test_fname('interval.interval')
        >>> Gifti().sniff(fname)
        False
        >>> fname = get_test_fname('megablast_xml_parser_test1.blastxml')
        >>> Gifti().sniff(fname)
        False
        >>> fname = get_test_fname('tblastn_four_human_vs_rhodopsin.blastxml')
        >>> Gifti().sniff(fname)
        False
        """
        handle = file_prefix.string_io()
        line = handle.readline()
        if not line.strip().startswith('<?xml version="1.0"'):
            return False
        line = handle.readline()
        if line.strip() == '<!DOCTYPE GIFTI SYSTEM "http://www.nitrc.org/frs/download.php/1594/gifti.dtd">':
            return True
        line = handle.readline()
        if line.strip().startswith("<GIFTI"):
            return True
        return False


[docs]@build_sniff_from_prefix
class Star(data.Text):
    """Base format class for Relion STAR (Self-defining
    Text Archiving and Retrieval) image files.
    https://relion.readthedocs.io/en/latest/Reference/Conventions.html"""

    file_ext = "star"

[docs]    def set_peek(self, dataset: DatasetProtocol, **kwd) -> None:
        """Set the peek and blurb text"""
        if not dataset.dataset.purged:
            dataset.peek = data.get_file_peek(dataset.get_file_name())
            dataset.blurb = "Relion STAR data"
        else:
            dataset.peek = "file does not exist"
            dataset.blurb = "file purged from disk"

[docs]    def sniff_prefix(self, file_prefix: FilePrefix) -> bool:
        """Each file must have one or more data blocks.
        The start of a data block is defined by the keyword
        ``data_`` followed by an optional string for
        identification (e.g., ``data_images``).  All text
        before the first ``data_`` keyword are comments

        >>> from galaxy.datatypes.sniff import get_test_fname
        >>> fname = get_test_fname('1.star')
        >>> Star().sniff(fname)
        True
        >>> fname = get_test_fname('interval.interval')
        >>> Star().sniff(fname)
        False
        """
        in_data_block = False
        for line in file_prefix.line_iterator():
            # All lines before the first
            # data_ block must be comments.
            line = line.strip()
            if len(line) == 0:
                continue
            if line.startswith("data_"):
                in_data_block = True
                continue
            if in_data_block:
                # Lines within data blocks must
                # be blank, start with loop_, or
                # start with _.
                if len(line) == 0:
                    continue
                if line.startswith("loop_") or line.startswith("_"):
                    return True
                return False
        return False


[docs]class Html(HtmlFromText):
    """Deprecated class. This class should not be used anymore, but the galaxy.datatypes.text:Html one.
    This is for backwards compatibilities only."""


[docs]class Laj(data.Text):
    """Deprecated class. Exists for limited backwards compatibility."""