- start rust rewrite
This commit is contained in:
Wim Pomp
22
.github/workflows/pytest.yml
vendored
22
.github/workflows/pytest.yml
vendored
@@ -1,22 +0,0 @@
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name: PyTest
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on: [workflow_call, push, pull_request]
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jobs:
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pytest:
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runs-on: ubuntu-latest
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strategy:
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matrix:
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python-version: ["3.10", "3.11", "3.12"]
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|
||||
steps:
|
||||
- uses: actions/checkout@v4
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- name: Set up Python ${{ matrix.python-version }}
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uses: actions/setup-python@v5
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with:
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python-version: ${{ matrix.python-version }}
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- name: Install dependencies
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run: |
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pip install .[test]
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- name: Test with pytest
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run: pytest
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84
.gitignore
vendored
84
.gitignore
vendored
@@ -1,12 +1,72 @@
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._*
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*.pyc
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/build/
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*.egg-info
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/venv/
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.idea
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/.pytest_cache/
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/ndbioimage/_version.py
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/ndbioimage/jars
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/tests/files/*
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/poetry.lock
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/dist/
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/target
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# Byte-compiled / optimized / DLL files
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__pycache__/
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.pytest_cache/
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*.py[cod]
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# C extensions
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*.so
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# Distribution / packaging
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.Python
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.venv/
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env/
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bin/
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build/
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develop-eggs/
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dist/
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eggs/
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lib/
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lib64/
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parts/
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sdist/
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var/
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include/
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man/
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venv/
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*.egg-info/
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.installed.cfg
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*.egg
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# Installer logs
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pip-log.txt
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pip-delete-this-directory.txt
|
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pip-selfcheck.json
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||||
|
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# Unit test / coverage reports
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htmlcov/
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.tox/
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.coverage
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.cache
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nosetests.xml
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coverage.xml
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|
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# Translations
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*.mo
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# Mr Developer
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.mr.developer.cfg
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.project
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.pydevproject
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# Rope
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.ropeproject
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# Django stuff:
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||||
*.log
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||||
*.pot
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.DS_Store
|
||||
|
||||
# Sphinx documentation
|
||||
docs/_build/
|
||||
|
||||
# PyCharm
|
||||
.idea/
|
||||
|
||||
# VSCode
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||||
.vscode/
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|
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# Pyenv
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||||
.python-version
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816
Cargo.lock
generated
Normal file
816
Cargo.lock
generated
Normal file
@@ -0,0 +1,816 @@
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# This file is automatically @generated by Cargo.
|
||||
# It is not intended for manual editing.
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version = 4
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|
||||
version = "0.52.6"
|
||||
source = "registry+https://github.com/rust-lang/crates.io-index"
|
||||
checksum = "8e9b5ad5ab802e97eb8e295ac6720e509ee4c243f69d781394014ebfe8bbfa0b"
|
||||
|
||||
[[package]]
|
||||
name = "windows_i686_gnullvm"
|
||||
version = "0.52.6"
|
||||
source = "registry+https://github.com/rust-lang/crates.io-index"
|
||||
checksum = "0eee52d38c090b3caa76c563b86c3a4bd71ef1a819287c19d586d7334ae8ed66"
|
||||
|
||||
[[package]]
|
||||
name = "windows_i686_msvc"
|
||||
version = "0.52.6"
|
||||
source = "registry+https://github.com/rust-lang/crates.io-index"
|
||||
checksum = "240948bc05c5e7c6dabba28bf89d89ffce3e303022809e73deaefe4f6ec56c66"
|
||||
|
||||
[[package]]
|
||||
name = "windows_x86_64_gnu"
|
||||
version = "0.52.6"
|
||||
source = "registry+https://github.com/rust-lang/crates.io-index"
|
||||
checksum = "147a5c80aabfbf0c7d901cb5895d1de30ef2907eb21fbbab29ca94c5b08b1a78"
|
||||
|
||||
[[package]]
|
||||
name = "windows_x86_64_gnullvm"
|
||||
version = "0.52.6"
|
||||
source = "registry+https://github.com/rust-lang/crates.io-index"
|
||||
checksum = "24d5b23dc417412679681396f2b49f3de8c1473deb516bd34410872eff51ed0d"
|
||||
|
||||
[[package]]
|
||||
name = "windows_x86_64_msvc"
|
||||
version = "0.52.6"
|
||||
source = "registry+https://github.com/rust-lang/crates.io-index"
|
||||
checksum = "589f6da84c646204747d1270a2a5661ea66ed1cced2631d546fdfb155959f9ec"
|
||||
|
||||
[[package]]
|
||||
name = "zerocopy"
|
||||
version = "0.7.35"
|
||||
source = "registry+https://github.com/rust-lang/crates.io-index"
|
||||
checksum = "1b9b4fd18abc82b8136838da5d50bae7bdea537c574d8dc1a34ed098d6c166f0"
|
||||
dependencies = [
|
||||
"byteorder",
|
||||
"zerocopy-derive",
|
||||
]
|
||||
|
||||
[[package]]
|
||||
name = "zerocopy-derive"
|
||||
version = "0.7.35"
|
||||
source = "registry+https://github.com/rust-lang/crates.io-index"
|
||||
checksum = "fa4f8080344d4671fb4e831a13ad1e68092748387dfc4f55e356242fae12ce3e"
|
||||
dependencies = [
|
||||
"proc-macro2",
|
||||
"quote",
|
||||
"syn 2.0.98",
|
||||
]
|
||||
33
Cargo.toml
Normal file
33
Cargo.toml
Normal file
@@ -0,0 +1,33 @@
|
||||
[package]
|
||||
name = "ndbioimage_rs"
|
||||
version = "2025.1.0"
|
||||
edition = "2021"
|
||||
|
||||
# See more keys and their definitions at https://doc.rust-lang.org/cargo/reference/manifest.html
|
||||
[lib]
|
||||
name = "ndbioimage_rs"
|
||||
crate-type = ["cdylib"]
|
||||
|
||||
[dependencies]
|
||||
anyhow = "1.0.95"
|
||||
j4rs = "0.22.0"
|
||||
ndarray = "0.16.1"
|
||||
num = "0.4.3"
|
||||
numpy = { version = "0.23.0", optional = true }
|
||||
|
||||
[dependencies.pyo3]
|
||||
version = "0.23.4"
|
||||
features = ["extension-module", "abi3-py310", "generate-import-lib", "anyhow"]
|
||||
optional = true
|
||||
|
||||
[dev-dependencies]
|
||||
rayon = "1.10.0"
|
||||
|
||||
[build-dependencies]
|
||||
j4rs = { version = "0.22", features = [] }
|
||||
retry = { version = "2.0.0"}
|
||||
anyhow = { version = "1.0.95"}
|
||||
|
||||
[features]
|
||||
python = ["dep:pyo3", "dep:numpy"]
|
||||
gpl-formats = []
|
||||
94
README.md
94
README.md
@@ -1,94 +1,4 @@
|
||||
[](https://github.com/wimpomp/ndbioimage/actions/workflows/pytest.yml)
|
||||
|
||||
# ndbioimage
|
||||
|
||||
Exposes (bio) images as a numpy ndarray-like object, but without loading the whole
|
||||
image into memory, reading from the file only when needed. Some metadata is read
|
||||
and stored in an [ome](https://genomebiology.biomedcentral.com/articles/10.1186/gb-2005-6-5-r47) structure.
|
||||
Additionally, it can automatically calculate an affine transform that corrects for chromatic aberrations etc. and apply
|
||||
it on the fly to the image.
|
||||
|
||||
Currently, it supports imagej tif files, czi files, micromanager tif sequences and anything
|
||||
[bioformats](https://www.openmicroscopy.org/bio-formats/) can handle.
|
||||
|
||||
## Installation
|
||||
|
||||
```
|
||||
pip install ndbioimage
|
||||
```
|
||||
|
||||
### Installation with option to write mp4 or mkv:
|
||||
Work in progress! Make sure ffmpeg is installed.
|
||||
|
||||
```
|
||||
pip install ndbioimage[write]
|
||||
```
|
||||
|
||||
## Usage
|
||||
### Python
|
||||
|
||||
- Reading an image file and plotting the frame at channel=2, time=1
|
||||
|
||||
```
|
||||
import matplotlib.pyplot as plt
|
||||
from ndbioimage import Imread
|
||||
with Imread('image_file.tif', axes='ctyx', dtype=int) as im:
|
||||
plt.imshow(im[2, 1])
|
||||
```
|
||||
|
||||
- Showing some image metadata
|
||||
|
||||
```
|
||||
from ndbioimage import Imread
|
||||
from pprint import pprint
|
||||
with Imread('image_file.tif') as im:
|
||||
pprint(im)
|
||||
```
|
||||
|
||||
- Slicing the image without loading the image into memory
|
||||
|
||||
```
|
||||
from ndbioimage import Imread
|
||||
with Imread('image_file.tif', axes='cztyx') as im:
|
||||
sliced_im = im[1, :, :, 100:200, 100:200]
|
||||
```
|
||||
|
||||
sliced_im is an instance of Imread which will load any image data from file only when needed
|
||||
|
||||
|
||||
- Converting (part) of the image to a numpy ndarray
|
||||
|
||||
```
|
||||
from ndbioimage import Imread
|
||||
import numpy as np
|
||||
with Imread('image_file.tif', axes='cztyx') as im:
|
||||
array = np.asarray(im[0, 0])
|
||||
```
|
||||
|
||||
### Command line
|
||||
```ndbioimage --help```: show help
|
||||
```ndbioimage image```: show metadata about image
|
||||
```ndbioimage image -w {name}.tif -r```: copy image into image.tif (replacing {name} with image), while registering channels
|
||||
```ndbioimage image -w image.mp4 -C cyan lime red``` copy image into image.mp4 (z will be max projected), make channel colors cyan lime and red
|
||||
|
||||
## Adding more formats
|
||||
Readers for image formats subclass AbstractReader. When an image reader is imported, Imread will
|
||||
automatically recognize it and use it to open the appropriate file format. Image readers
|
||||
are required to implement the following methods:
|
||||
|
||||
- staticmethod _can_open(path): return True if path can be opened by this reader
|
||||
- \_\_frame__(self, c, z, t): return the frame at channel=c, z-slice=z, time=t from the file
|
||||
|
||||
Optional methods:
|
||||
- get_ome: reads metadata from file and adds them to an OME object imported
|
||||
from the ome-types library
|
||||
- open(self): maybe open some file handle
|
||||
- close(self): close any file handles
|
||||
|
||||
Optional fields:
|
||||
- priority (int): Imread will try readers with a lower number first, default: 99
|
||||
- do_not_pickle (strings): any attributes that should not be included when the object is pickled,
|
||||
for example: any file handles
|
||||
|
||||
# TODO
|
||||
- more image formats
|
||||
# Work in progress
|
||||
Rust rewrite of python version
|
||||
|
||||
28
build.rs
Normal file
28
build.rs
Normal file
@@ -0,0 +1,28 @@
|
||||
// copied from https://github.com/AzHicham/bioformats-rs
|
||||
|
||||
use j4rs::{errors::J4RsError, JvmBuilder, MavenArtifact, MavenArtifactRepo, MavenSettings};
|
||||
use retry::{delay, delay::Exponential, retry};
|
||||
|
||||
fn main() -> anyhow::Result<()> {
|
||||
println!("cargo:rerun-if-changed=build.rs");
|
||||
|
||||
Ok(retry(
|
||||
Exponential::from_millis(1000).map(delay::jitter).take(4),
|
||||
deploy_java_artifacts,
|
||||
)?)
|
||||
}
|
||||
|
||||
fn deploy_java_artifacts() -> Result<(), J4RsError> {
|
||||
let jvm = JvmBuilder::new()
|
||||
.with_maven_settings(MavenSettings::new(vec![MavenArtifactRepo::from(
|
||||
"openmicroscopy::https://artifacts.openmicroscopy.org/artifactory/ome.releases",
|
||||
)]))
|
||||
.build()?;
|
||||
|
||||
jvm.deploy_artifact(&MavenArtifact::from("ome:bioformats_package:8.0.1"))?;
|
||||
|
||||
#[cfg(feature = "gpl-formats")]
|
||||
jvm.deploy_artifact(&MavenArtifact::from("ome:formats-gpl:8.0.1"))?;
|
||||
|
||||
Ok(())
|
||||
}
|
||||
File diff suppressed because it is too large
Load Diff
@@ -1,77 +0,0 @@
|
||||
from pathlib import Path
|
||||
from urllib import request
|
||||
|
||||
|
||||
class JVMException(Exception):
|
||||
pass
|
||||
|
||||
|
||||
try:
|
||||
class JVM:
|
||||
""" There can be only one java virtual machine per python process,
|
||||
so this is a singleton class to manage the jvm.
|
||||
"""
|
||||
_instance = None
|
||||
vm_started = False
|
||||
vm_killed = False
|
||||
success = True
|
||||
|
||||
def __new__(cls, *args):
|
||||
if cls._instance is None:
|
||||
cls._instance = object.__new__(cls)
|
||||
return cls._instance
|
||||
|
||||
def __init__(self, jars=None):
|
||||
if not self.vm_started and not self.vm_killed:
|
||||
try:
|
||||
jar_path = Path(__file__).parent / 'jars'
|
||||
if jars is None:
|
||||
jars = {}
|
||||
for jar, src in jars.items():
|
||||
if not (jar_path / jar).exists():
|
||||
JVM.download(src, jar_path / jar)
|
||||
classpath = [str(jar_path / jar) for jar in jars.keys()]
|
||||
|
||||
import jpype
|
||||
jpype.startJVM(classpath=classpath)
|
||||
except Exception: # noqa
|
||||
self.vm_started = False
|
||||
else:
|
||||
self.vm_started = True
|
||||
try:
|
||||
import jpype.imports
|
||||
from loci.common import DebugTools # noqa
|
||||
from loci.formats import ChannelSeparator # noqa
|
||||
from loci.formats import FormatTools # noqa
|
||||
from loci.formats import ImageReader # noqa
|
||||
from loci.formats import MetadataTools # noqa
|
||||
|
||||
DebugTools.setRootLevel("ERROR")
|
||||
|
||||
self.image_reader = ImageReader
|
||||
self.channel_separator = ChannelSeparator
|
||||
self.format_tools = FormatTools
|
||||
self.metadata_tools = MetadataTools
|
||||
except Exception: # noqa
|
||||
pass
|
||||
|
||||
if self.vm_killed:
|
||||
raise Exception('The JVM was killed before, and cannot be restarted in this Python process.')
|
||||
|
||||
@staticmethod
|
||||
def download(src, dest):
|
||||
print(f'Downloading {dest.name} to {dest}.')
|
||||
dest.parent.mkdir(exist_ok=True)
|
||||
dest.write_bytes(request.urlopen(src).read())
|
||||
|
||||
@classmethod
|
||||
def kill_vm(cls):
|
||||
self = cls._instance
|
||||
if self is not None and self.vm_started and not self.vm_killed:
|
||||
import jpype
|
||||
jpype.shutdownJVM() # noqa
|
||||
self.vm_started = False
|
||||
self.vm_killed = True
|
||||
|
||||
except ImportError:
|
||||
JVM = None
|
||||
@@ -1 +0,0 @@
|
||||
__all__ = 'bfread', 'cziread', 'fijiread', 'ndread', 'seqread', 'tifread', 'metaseriesread'
|
||||
@@ -1,208 +0,0 @@
|
||||
import multiprocessing
|
||||
from abc import ABC
|
||||
from multiprocessing import queues
|
||||
from pathlib import Path
|
||||
from traceback import format_exc
|
||||
|
||||
import numpy as np
|
||||
|
||||
from .. import JVM, AbstractReader, JVMException
|
||||
|
||||
jars = {'bioformats_package.jar': 'https://downloads.openmicroscopy.org/bio-formats/latest/artifacts/'
|
||||
'bioformats_package.jar'}
|
||||
|
||||
|
||||
class JVMReader:
|
||||
def __init__(self, path: Path, series: int) -> None:
|
||||
mp = multiprocessing.get_context('spawn')
|
||||
self.path = path
|
||||
self.series = series
|
||||
self.queue_in = mp.Queue()
|
||||
self.queue_out = mp.Queue()
|
||||
self.done = mp.Event()
|
||||
self.process = mp.Process(target=self.run)
|
||||
self.process.start()
|
||||
status, message = self.queue_out.get()
|
||||
if status == 'status' and message == 'started':
|
||||
self.is_alive = True
|
||||
else:
|
||||
raise JVMException(message)
|
||||
|
||||
def close(self) -> None:
|
||||
if self.is_alive:
|
||||
self.done.set()
|
||||
while not self.queue_in.empty():
|
||||
self.queue_in.get()
|
||||
self.queue_in.close()
|
||||
self.queue_in.join_thread()
|
||||
while not self.queue_out.empty():
|
||||
print(self.queue_out.get())
|
||||
self.queue_out.close()
|
||||
self.process.join()
|
||||
self.process.close()
|
||||
self.is_alive = False
|
||||
|
||||
def frame(self, c: int, z: int, t: int) -> np.ndarray:
|
||||
self.queue_in.put((c, z, t))
|
||||
status, message = self.queue_out.get()
|
||||
if status == 'frame':
|
||||
return message
|
||||
else:
|
||||
raise JVMException(message)
|
||||
|
||||
def run(self) -> None:
|
||||
""" Read planes from the image reader file.
|
||||
adapted from python-bioformats/bioformats/formatreader.py
|
||||
"""
|
||||
jvm = None
|
||||
try:
|
||||
jvm = JVM(jars)
|
||||
reader = jvm.image_reader()
|
||||
ome_meta = jvm.metadata_tools.createOMEXMLMetadata()
|
||||
reader.setMetadataStore(ome_meta)
|
||||
reader.setId(str(self.path))
|
||||
reader.setSeries(self.series)
|
||||
|
||||
open_bytes_func = reader.openBytes
|
||||
width, height = int(reader.getSizeX()), int(reader.getSizeY())
|
||||
|
||||
pixel_type = reader.getPixelType()
|
||||
little_endian = reader.isLittleEndian()
|
||||
|
||||
if pixel_type == jvm.format_tools.INT8:
|
||||
dtype = np.int8
|
||||
elif pixel_type == jvm.format_tools.UINT8:
|
||||
dtype = np.uint8
|
||||
elif pixel_type == jvm.format_tools.UINT16:
|
||||
dtype = '<u2' if little_endian else '>u2'
|
||||
elif pixel_type == jvm.format_tools.INT16:
|
||||
dtype = '<i2' if little_endian else '>i2'
|
||||
elif pixel_type == jvm.format_tools.UINT32:
|
||||
dtype = '<u4' if little_endian else '>u4'
|
||||
elif pixel_type == jvm.format_tools.INT32:
|
||||
dtype = '<i4' if little_endian else '>i4'
|
||||
elif pixel_type == jvm.format_tools.FLOAT:
|
||||
dtype = '<f4' if little_endian else '>f4'
|
||||
elif pixel_type == jvm.format_tools.DOUBLE:
|
||||
dtype = '<f8' if little_endian else '>f8'
|
||||
else:
|
||||
dtype = None
|
||||
self.queue_out.put(('status', 'started'))
|
||||
|
||||
while not self.done.is_set():
|
||||
try:
|
||||
c, z, t = self.queue_in.get(True, 0.02)
|
||||
if reader.isRGB() and reader.isInterleaved():
|
||||
index = reader.getIndex(z, 0, t)
|
||||
image = np.frombuffer(open_bytes_func(index), dtype)
|
||||
image.shape = (height, width, reader.getSizeC())
|
||||
if image.shape[2] > 3:
|
||||
image = image[:, :, :3]
|
||||
elif c is not None and reader.getRGBChannelCount() == 1:
|
||||
index = reader.getIndex(z, c, t)
|
||||
image = np.frombuffer(open_bytes_func(index), dtype)
|
||||
image.shape = (height, width)
|
||||
elif reader.getRGBChannelCount() > 1:
|
||||
n_planes = reader.getRGBChannelCount()
|
||||
rdr = jvm.channel_separator(reader)
|
||||
planes = [np.frombuffer(rdr.openBytes(rdr.getIndex(z, i, t)), dtype) for i in range(n_planes)]
|
||||
if len(planes) > 3:
|
||||
planes = planes[:3]
|
||||
elif len(planes) < 3:
|
||||
# > 1 and < 3 means must be 2
|
||||
# see issue #775
|
||||
planes.append(np.zeros(planes[0].shape, planes[0].dtype))
|
||||
image = np.dstack(planes)
|
||||
image.shape = (height, width, 3)
|
||||
del rdr
|
||||
elif reader.getSizeC() > 1:
|
||||
images = [np.frombuffer(open_bytes_func(reader.getIndex(z, i, t)), dtype)
|
||||
for i in range(reader.getSizeC())]
|
||||
image = np.dstack(images)
|
||||
image.shape = (height, width, reader.getSizeC())
|
||||
# if not channel_names is None:
|
||||
# metadata = MetadataRetrieve(self.metadata)
|
||||
# for i in range(self.reader.getSizeC()):
|
||||
# index = self.reader.getIndex(z, 0, t)
|
||||
# channel_name = metadata.getChannelName(index, i)
|
||||
# if channel_name is None:
|
||||
# channel_name = metadata.getChannelID(index, i)
|
||||
# channel_names.append(channel_name)
|
||||
elif reader.isIndexed():
|
||||
#
|
||||
# The image data is indexes into a color lookup-table
|
||||
# But sometimes the table is the identity table and just generates
|
||||
# a monochrome RGB image
|
||||
#
|
||||
index = reader.getIndex(z, 0, t)
|
||||
image = np.frombuffer(open_bytes_func(index), dtype)
|
||||
if pixel_type in (jvm.format_tools.INT16, jvm.format_tools.UINT16):
|
||||
lut = reader.get16BitLookupTable()
|
||||
if lut is not None:
|
||||
lut = np.array(lut)
|
||||
# lut = np.array(
|
||||
# [env.get_short_array_elements(d)
|
||||
# for d in env.get_object_array_elements(lut)]) \
|
||||
# .transpose()
|
||||
else:
|
||||
lut = reader.get8BitLookupTable()
|
||||
if lut is not None:
|
||||
lut = np.array(lut)
|
||||
# lut = np.array(
|
||||
# [env.get_byte_array_elements(d)
|
||||
# for d in env.get_object_array_elements(lut)]) \
|
||||
# .transpose()
|
||||
image.shape = (height, width)
|
||||
if (lut is not None) and not np.all(lut == np.arange(lut.shape[0])[:, np.newaxis]):
|
||||
image = lut[image, :]
|
||||
else:
|
||||
index = reader.getIndex(z, 0, t)
|
||||
image = np.frombuffer(open_bytes_func(index), dtype)
|
||||
image.shape = (height, width)
|
||||
|
||||
if image.ndim == 3:
|
||||
self.queue_out.put(('frame', image[..., c]))
|
||||
else:
|
||||
self.queue_out.put(('frame', image))
|
||||
except queues.Empty: # noqa
|
||||
continue
|
||||
except (Exception,):
|
||||
self.queue_out.put(('error', format_exc()))
|
||||
finally:
|
||||
if jvm is not None:
|
||||
jvm.kill_vm()
|
||||
|
||||
|
||||
def can_open(path: Path) -> bool:
|
||||
try:
|
||||
jvm = JVM(jars)
|
||||
reader = jvm.image_reader()
|
||||
reader.getFormat(str(path))
|
||||
return True
|
||||
except (Exception,):
|
||||
return False
|
||||
finally:
|
||||
jvm.kill_vm() # noqa
|
||||
|
||||
|
||||
class Reader(AbstractReader, ABC):
|
||||
""" This class is used as a last resort, when we don't have another way to open the file. We don't like it
|
||||
because it requires the java vm.
|
||||
"""
|
||||
priority = 99 # panic and open with BioFormats
|
||||
do_not_pickle = 'reader', 'key', 'jvm'
|
||||
|
||||
@staticmethod
|
||||
def _can_open(path: Path) -> bool:
|
||||
""" Use java BioFormats to make an ome metadata structure. """
|
||||
with multiprocessing.get_context('spawn').Pool(1) as pool:
|
||||
return pool.map(can_open, (path,))[0]
|
||||
|
||||
def open(self) -> None:
|
||||
self.reader = JVMReader(self.path, self.series)
|
||||
|
||||
def __frame__(self, c: int, z: int, t: int) -> np.ndarray:
|
||||
return self.reader.frame(c, z, t)
|
||||
|
||||
def close(self) -> None:
|
||||
self.reader.close()
|
||||
@@ -1,606 +0,0 @@
|
||||
import re
|
||||
import warnings
|
||||
from abc import ABC
|
||||
from functools import cached_property
|
||||
from io import BytesIO
|
||||
from itertools import product
|
||||
from pathlib import Path
|
||||
from typing import Any, Callable, Optional, TypeVar
|
||||
|
||||
import czifile
|
||||
import imagecodecs
|
||||
import numpy as np
|
||||
from lxml import etree
|
||||
from ome_types import OME, model
|
||||
from tifffile import repeat_nd
|
||||
|
||||
from .. import AbstractReader
|
||||
|
||||
try:
|
||||
# TODO: use zoom from imagecodecs implementation when available
|
||||
from scipy.ndimage.interpolation import zoom
|
||||
except ImportError:
|
||||
try:
|
||||
from ndimage.interpolation import zoom
|
||||
except ImportError:
|
||||
zoom = None
|
||||
|
||||
|
||||
Element = TypeVar('Element')
|
||||
|
||||
|
||||
def zstd_decode(data: bytes) -> bytes: # noqa
|
||||
""" decode zstd bytes, copied from BioFormats ZeissCZIReader """
|
||||
def read_var_int(stream: BytesIO) -> int: # noqa
|
||||
a = stream.read(1)[0]
|
||||
if a & 128:
|
||||
b = stream.read(1)[0]
|
||||
if b & 128:
|
||||
c = stream.read(1)[0]
|
||||
return (c << 14) | ((b & 127) << 7) | (a & 127)
|
||||
return (b << 7) | (a & 127)
|
||||
return a & 255
|
||||
|
||||
try:
|
||||
with BytesIO(data) as stream:
|
||||
size_of_header = read_var_int(stream)
|
||||
high_low_unpacking = False
|
||||
while stream.tell() < size_of_header:
|
||||
chunk_id = read_var_int(stream)
|
||||
# only one chunk ID defined so far
|
||||
if chunk_id == 1:
|
||||
high_low_unpacking = (stream.read(1)[0] & 1) == 1
|
||||
else:
|
||||
raise ValueError(f'Invalid chunk id: {chunk_id}')
|
||||
pointer = stream.tell()
|
||||
except Exception: # noqa
|
||||
high_low_unpacking = False
|
||||
pointer = 0
|
||||
|
||||
decoded = imagecodecs.zstd_decode(data[pointer:])
|
||||
if high_low_unpacking:
|
||||
second_half = len(decoded) // 2
|
||||
return bytes([decoded[second_half + i // 2] if i % 2 else decoded[i // 2] for i in range(len(decoded))])
|
||||
else:
|
||||
return decoded
|
||||
|
||||
|
||||
def data(self, raw: bool = False, resize: bool = True, order: int = 0) -> np.ndarray:
|
||||
"""Read image data from file and return as numpy array."""
|
||||
DECOMPRESS = czifile.czifile.DECOMPRESS # noqa
|
||||
DECOMPRESS[5] = imagecodecs.zstd_decode
|
||||
DECOMPRESS[6] = zstd_decode
|
||||
|
||||
de = self.directory_entry
|
||||
fh = self._fh
|
||||
if raw:
|
||||
with fh.lock:
|
||||
fh.seek(self.data_offset)
|
||||
data = fh.read(self.data_size) # noqa
|
||||
return data
|
||||
if de.compression:
|
||||
# if de.compression not in DECOMPRESS:
|
||||
# raise ValueError('compression unknown or not supported')
|
||||
with fh.lock:
|
||||
fh.seek(self.data_offset)
|
||||
data = fh.read(self.data_size) # noqa
|
||||
data = DECOMPRESS[de.compression](data) # noqa
|
||||
if de.compression == 2:
|
||||
# LZW
|
||||
data = np.fromstring(data, de.dtype) # noqa
|
||||
elif de.compression in (5, 6):
|
||||
# ZSTD
|
||||
data = np.frombuffer(data, de.dtype) # noqa
|
||||
else:
|
||||
dtype = np.dtype(de.dtype)
|
||||
with fh.lock:
|
||||
fh.seek(self.data_offset)
|
||||
data = fh.read_array(dtype, self.data_size // dtype.itemsize) # noqa
|
||||
|
||||
data = data.reshape(de.stored_shape) # noqa
|
||||
if de.compression != 4 and de.stored_shape[-1] in (3, 4):
|
||||
if de.stored_shape[-1] == 3:
|
||||
# BGR -> RGB
|
||||
data = data[..., ::-1] # noqa
|
||||
else:
|
||||
# BGRA -> RGBA
|
||||
tmp = data[..., 0].copy()
|
||||
data[..., 0] = data[..., 2]
|
||||
data[..., 2] = tmp
|
||||
if de.stored_shape == de.shape or not resize:
|
||||
return data
|
||||
|
||||
# sub / supersampling
|
||||
factors = [j / i for i, j in zip(de.stored_shape, de.shape)]
|
||||
factors = [(int(round(f)) if abs(f - round(f)) < 0.0001 else f)
|
||||
for f in factors]
|
||||
|
||||
# use repeat if possible
|
||||
if order == 0 and all(isinstance(f, int) for f in factors):
|
||||
data = repeat_nd(data, factors).copy() # noqa
|
||||
data.shape = de.shape
|
||||
return data
|
||||
|
||||
# remove leading dimensions with size 1 for speed
|
||||
shape = list(de.stored_shape)
|
||||
i = 0
|
||||
for s in shape:
|
||||
if s != 1:
|
||||
break
|
||||
i += 1
|
||||
shape = shape[i:]
|
||||
factors = factors[i:]
|
||||
data.shape = shape
|
||||
|
||||
# resize RGB components separately for speed
|
||||
if zoom is None:
|
||||
raise ImportError("cannot import 'zoom' from scipy or ndimage")
|
||||
if shape[-1] in (3, 4) and factors[-1] == 1.0:
|
||||
factors = factors[:-1]
|
||||
old = data
|
||||
data = np.empty(de.shape, de.dtype[-2:]) # noqa
|
||||
for i in range(shape[-1]):
|
||||
data[..., i] = zoom(old[..., i], zoom=factors, order=order)
|
||||
else:
|
||||
data = zoom(data, zoom=factors, order=order) # noqa
|
||||
|
||||
data.shape = de.shape
|
||||
return data
|
||||
|
||||
|
||||
# monkeypatch zstd into czifile
|
||||
czifile.czifile.SubBlockSegment.data = data
|
||||
|
||||
|
||||
class Reader(AbstractReader, ABC):
|
||||
priority = 0
|
||||
do_not_pickle = 'reader', 'filedict'
|
||||
|
||||
@staticmethod
|
||||
def _can_open(path: Path) -> bool:
|
||||
return isinstance(path, Path) and path.suffix == '.czi'
|
||||
|
||||
def open(self) -> None:
|
||||
self.reader = czifile.CziFile(self.path)
|
||||
filedict = {}
|
||||
for directory_entry in self.reader.filtered_subblock_directory:
|
||||
idx = self.get_index(directory_entry, self.reader.start)
|
||||
if 'S' not in self.reader.axes or self.series in range(*idx[self.reader.axes.index('S')]):
|
||||
for c in range(*idx[self.reader.axes.index('C')]):
|
||||
for z in range(*idx[self.reader.axes.index('Z')]):
|
||||
for t in range(*idx[self.reader.axes.index('T')]):
|
||||
if (c, z, t) in filedict:
|
||||
filedict[c, z, t].append(directory_entry)
|
||||
else:
|
||||
filedict[c, z, t] = [directory_entry]
|
||||
if len(filedict) == 0:
|
||||
raise FileNotFoundError(f'Series {self.series} not found in {self.path}.')
|
||||
self.filedict = filedict # noqa
|
||||
|
||||
def close(self) -> None:
|
||||
self.reader.close()
|
||||
|
||||
def get_ome(self) -> OME:
|
||||
return OmeParse.get_ome(self.reader, self.filedict)
|
||||
|
||||
def __frame__(self, c: int = 0, z: int = 0, t: int = 0) -> np.ndarray:
|
||||
f = np.zeros(self.base_shape['yx'], self.dtype)
|
||||
if (c, z, t) in self.filedict:
|
||||
directory_entries = self.filedict[c, z, t]
|
||||
x_min = min([f.start[f.axes.index('X')] for f in directory_entries])
|
||||
y_min = min([f.start[f.axes.index('Y')] for f in directory_entries])
|
||||
xy_min = {'X': x_min, 'Y': y_min}
|
||||
for directory_entry in directory_entries:
|
||||
subblock = directory_entry.data_segment()
|
||||
tile = subblock.data(resize=True, order=0)
|
||||
axes_min = [xy_min.get(ax, 0) for ax in directory_entry.axes]
|
||||
index = [slice(i - j - m, i - j + k)
|
||||
for i, j, k, m in zip(directory_entry.start, self.reader.start, tile.shape, axes_min)]
|
||||
index = tuple(index[self.reader.axes.index(i)] for i in 'YX')
|
||||
f[index] = tile.squeeze()
|
||||
return f
|
||||
|
||||
@staticmethod
|
||||
def get_index(directory_entry: czifile.DirectoryEntryDV, start: tuple[int]) -> list[tuple[int, int]]:
|
||||
return [(i - j, i - j + k) for i, j, k in zip(directory_entry.start, start, directory_entry.shape)]
|
||||
|
||||
|
||||
class OmeParse:
|
||||
size_x: int
|
||||
size_y: int
|
||||
size_c: int
|
||||
size_z: int
|
||||
size_t: int
|
||||
|
||||
nm = model.UnitsLength.NANOMETER
|
||||
um = model.UnitsLength.MICROMETER
|
||||
|
||||
@classmethod
|
||||
def get_ome(cls, reader: czifile.CziFile, filedict: dict[tuple[int, int, int], Any]) -> OME:
|
||||
new = cls(reader, filedict)
|
||||
new.parse()
|
||||
return new.ome
|
||||
|
||||
def __init__(self, reader: czifile.CziFile, filedict: dict[tuple[int, int, int], Any]) -> None:
|
||||
self.reader = reader
|
||||
self.filedict = filedict
|
||||
xml = reader.metadata()
|
||||
self.attachments = {i.attachment_entry.name: i.attachment_entry.data_segment()
|
||||
for i in reader.attachments()}
|
||||
self.tree = etree.fromstring(xml)
|
||||
self.metadata = self.tree.find('Metadata')
|
||||
version = self.metadata.find('Version')
|
||||
if version is not None:
|
||||
self.version = version.text
|
||||
else:
|
||||
self.version = self.metadata.find('Experiment').attrib['Version']
|
||||
|
||||
self.ome = OME()
|
||||
self.information = self.metadata.find('Information')
|
||||
self.display_setting = self.metadata.find('DisplaySetting')
|
||||
self.experiment = self.metadata.find('Experiment')
|
||||
self.acquisition_block = self.experiment.find('ExperimentBlocks').find('AcquisitionBlock')
|
||||
self.instrument = self.information.find('Instrument')
|
||||
self.image = self.information.find('Image')
|
||||
|
||||
if self.version == '1.0':
|
||||
self.experiment = self.metadata.find('Experiment')
|
||||
self.acquisition_block = self.experiment.find('ExperimentBlocks').find('AcquisitionBlock')
|
||||
self.multi_track_setup = self.acquisition_block.find('MultiTrackSetup')
|
||||
else:
|
||||
self.experiment = None
|
||||
self.acquisition_block = None
|
||||
self.multi_track_setup = None
|
||||
|
||||
def parse(self) -> None:
|
||||
self.get_experimenters()
|
||||
self.get_instruments()
|
||||
self.get_detectors()
|
||||
self.get_objectives()
|
||||
self.get_tubelenses()
|
||||
self.get_light_sources()
|
||||
self.get_filters()
|
||||
self.get_pixels()
|
||||
self.get_channels()
|
||||
self.get_planes()
|
||||
self.get_annotations()
|
||||
|
||||
@staticmethod
|
||||
def text(item: Optional[Element], default: str = "") -> str:
|
||||
return default if item is None else item.text
|
||||
|
||||
@staticmethod
|
||||
def def_list(item: Any) -> list[Any]:
|
||||
return [] if item is None else item
|
||||
|
||||
@staticmethod
|
||||
def try_default(fun: Callable[[Any, ...], Any] | type, default: Any = None, *args: Any, **kwargs: Any) -> Any:
|
||||
try:
|
||||
return fun(*args, **kwargs)
|
||||
except Exception: # noqa
|
||||
return default
|
||||
|
||||
def get_experimenters(self) -> None:
|
||||
if self.version == '1.0':
|
||||
self.ome.experimenters = [
|
||||
model.Experimenter(id='Experimenter:0',
|
||||
user_name=self.information.find('User').find('DisplayName').text)]
|
||||
elif self.version in ('1.1', '1.2'):
|
||||
self.ome.experimenters = [
|
||||
model.Experimenter(id='Experimenter:0',
|
||||
user_name=self.information.find('Document').find('UserName').text)]
|
||||
|
||||
def get_instruments(self) -> None:
|
||||
if self.version == '1.0':
|
||||
self.ome.instruments.append(model.Instrument(id=self.instrument.attrib['Id']))
|
||||
elif self.version in ('1.1', '1.2'):
|
||||
for _ in self.instrument.find('Microscopes'):
|
||||
self.ome.instruments.append(model.Instrument(id='Instrument:0'))
|
||||
|
||||
def get_detectors(self) -> None:
|
||||
if self.version == '1.0':
|
||||
for detector in self.instrument.find('Detectors'):
|
||||
try:
|
||||
detector_type = model.Detector_Type(self.text(detector.find('Type')).upper() or "")
|
||||
except ValueError:
|
||||
detector_type = model.Detector_Type.OTHER
|
||||
|
||||
self.ome.instruments[0].detectors.append(
|
||||
model.Detector(
|
||||
id=detector.attrib['Id'], model=self.text(detector.find('Manufacturer').find('Model')),
|
||||
amplification_gain=float(self.text(detector.find('AmplificationGain'))),
|
||||
gain=float(self.text(detector.find('Gain'))), zoom=float(self.text(detector.find('Zoom'))),
|
||||
type=detector_type
|
||||
))
|
||||
elif self.version in ('1.1', '1.2'):
|
||||
for detector in self.instrument.find('Detectors'):
|
||||
try:
|
||||
detector_type = model.Detector_Type(self.text(detector.find('Type')).upper() or "")
|
||||
except ValueError:
|
||||
detector_type = model.Detector_Type.OTHER
|
||||
|
||||
self.ome.instruments[0].detectors.append(
|
||||
model.Detector(
|
||||
id=detector.attrib['Id'].replace(' ', ''),
|
||||
model=self.text(detector.find('Manufacturer').find('Model')),
|
||||
type=detector_type
|
||||
))
|
||||
|
||||
def get_objectives(self) -> None:
|
||||
for objective in self.instrument.find('Objectives'):
|
||||
self.ome.instruments[0].objectives.append(
|
||||
model.Objective(
|
||||
id=objective.attrib['Id'],
|
||||
model=self.text(objective.find('Manufacturer').find('Model')),
|
||||
immersion=self.text(objective.find('Immersion')), # type: ignore
|
||||
lens_na=float(self.text(objective.find('LensNA'))),
|
||||
nominal_magnification=float(self.text(objective.find('NominalMagnification')))))
|
||||
|
||||
def get_tubelenses(self) -> None:
|
||||
if self.version == '1.0':
|
||||
for idx, tube_lens in enumerate({self.text(track_setup.find('TubeLensPosition'))
|
||||
for track_setup in self.multi_track_setup}):
|
||||
try:
|
||||
nominal_magnification = float(re.findall(r'\d+[,.]\d*', tube_lens)[0].replace(',', '.'))
|
||||
except Exception: # noqa
|
||||
nominal_magnification = 1.0
|
||||
|
||||
self.ome.instruments[0].objectives.append(
|
||||
model.Objective(id=f'Objective:Tubelens:{idx}', model=tube_lens,
|
||||
nominal_magnification=nominal_magnification))
|
||||
elif self.version in ('1.1', '1.2'):
|
||||
for tubelens in self.def_list(self.instrument.find('TubeLenses')):
|
||||
try:
|
||||
nominal_magnification = float(re.findall(r'\d+(?:[,.]\d*)?',
|
||||
tubelens.attrib['Name'])[0].replace(',', '.'))
|
||||
except Exception: # noqa
|
||||
nominal_magnification = 1.0
|
||||
|
||||
self.ome.instruments[0].objectives.append(
|
||||
model.Objective(
|
||||
id=f"Objective:{tubelens.attrib['Id']}",
|
||||
model=tubelens.attrib['Name'],
|
||||
nominal_magnification=nominal_magnification))
|
||||
|
||||
def get_light_sources(self) -> None:
|
||||
if self.version == '1.0':
|
||||
for light_source in self.def_list(self.instrument.find('LightSources')):
|
||||
try:
|
||||
if light_source.find('LightSourceType').find('Laser') is not None:
|
||||
self.ome.instruments[0].lasers.append(
|
||||
model.Laser(
|
||||
id=light_source.attrib['Id'],
|
||||
model=self.text(light_source.find('Manufacturer').find('Model')),
|
||||
power=float(self.text(light_source.find('Power'))),
|
||||
wavelength=float(
|
||||
self.text(light_source.find('LightSourceType').find('Laser').find('Wavelength')))))
|
||||
except AttributeError:
|
||||
pass
|
||||
elif self.version in ('1.1', '1.2'):
|
||||
for light_source in self.def_list(self.instrument.find('LightSources')):
|
||||
try:
|
||||
if light_source.find('LightSourceType').find('Laser') is not None:
|
||||
self.ome.instruments[0].lasers.append(
|
||||
model.Laser(
|
||||
id=f"LightSource:{light_source.attrib['Id']}",
|
||||
power=float(self.text(light_source.find('Power'))),
|
||||
wavelength=float(light_source.attrib['Id'][-3:]))) # TODO: follow Id reference
|
||||
except (AttributeError, ValueError):
|
||||
pass
|
||||
|
||||
def get_filters(self) -> None:
|
||||
if self.version == '1.0':
|
||||
for idx, filter_ in enumerate({self.text(beam_splitter.find('Filter'))
|
||||
for track_setup in self.multi_track_setup
|
||||
for beam_splitter in track_setup.find('BeamSplitters')}):
|
||||
self.ome.instruments[0].filter_sets.append(
|
||||
model.FilterSet(id=f'FilterSet:{idx}', model=filter_)
|
||||
)
|
||||
|
||||
def get_pixels(self) -> None:
|
||||
x_min = min([f.start[f.axes.index('X')] for f in self.filedict[0, 0, 0]])
|
||||
y_min = min([f.start[f.axes.index('Y')] for f in self.filedict[0, 0, 0]])
|
||||
x_max = max([f.start[f.axes.index('X')] + f.shape[f.axes.index('X')] for f in self.filedict[0, 0, 0]])
|
||||
y_max = max([f.start[f.axes.index('Y')] + f.shape[f.axes.index('Y')] for f in self.filedict[0, 0, 0]])
|
||||
self.size_x = x_max - x_min
|
||||
self.size_y = y_max - y_min
|
||||
self.size_c, self.size_z, self.size_t = (self.reader.shape[self.reader.axes.index(directory_entry)]
|
||||
for directory_entry in 'CZT')
|
||||
image = self.information.find('Image')
|
||||
pixel_type = self.text(image.find('PixelType'), 'Gray16')
|
||||
if pixel_type.startswith('Gray'):
|
||||
pixel_type = 'uint' + pixel_type[4:]
|
||||
objective_settings = image.find('ObjectiveSettings')
|
||||
|
||||
self.ome.images.append(
|
||||
model.Image(
|
||||
id='Image:0',
|
||||
name=f"{self.text(self.information.find('Document').find('Name'))} #1",
|
||||
pixels=model.Pixels(
|
||||
id='Pixels:0', size_x=self.size_x, size_y=self.size_y,
|
||||
size_c=self.size_c, size_z=self.size_z, size_t=self.size_t,
|
||||
dimension_order='XYCZT', type=pixel_type, # type: ignore
|
||||
significant_bits=int(self.text(image.find('ComponentBitCount'))),
|
||||
big_endian=False, interleaved=False, metadata_only=True), # type: ignore
|
||||
experimenter_ref=model.ExperimenterRef(id='Experimenter:0'),
|
||||
instrument_ref=model.InstrumentRef(id='Instrument:0'),
|
||||
objective_settings=model.ObjectiveSettings(
|
||||
id=objective_settings.find('ObjectiveRef').attrib['Id'],
|
||||
medium=self.text(objective_settings.find('Medium')), # type: ignore
|
||||
refractive_index=float(self.text(objective_settings.find('RefractiveIndex')))),
|
||||
stage_label=model.StageLabel(
|
||||
name=f'Scene position #0',
|
||||
x=self.positions[0], x_unit=self.um,
|
||||
y=self.positions[1], y_unit=self.um,
|
||||
z=self.positions[2], z_unit=self.um)))
|
||||
|
||||
for distance in self.metadata.find('Scaling').find('Items'):
|
||||
if distance.attrib['Id'] == 'X':
|
||||
self.ome.images[0].pixels.physical_size_x = float(self.text(distance.find('Value'))) * 1e6
|
||||
elif distance.attrib['Id'] == 'Y':
|
||||
self.ome.images[0].pixels.physical_size_y = float(self.text(distance.find('Value'))) * 1e6
|
||||
elif self.size_z > 1 and distance.attrib['Id'] == 'Z':
|
||||
self.ome.images[0].pixels.physical_size_z = float(self.text(distance.find('Value'))) * 1e6
|
||||
|
||||
@cached_property
|
||||
def positions(self) -> tuple[float, float, Optional[float]]:
|
||||
if self.version == '1.0':
|
||||
scenes = self.image.find('Dimensions').find('S').find('Scenes')
|
||||
positions = scenes[0].find('Positions')[0]
|
||||
return float(positions.attrib['X']), float(positions.attrib['Y']), float(positions.attrib['Z'])
|
||||
elif self.version in ('1.1', '1.2'):
|
||||
try: # TODO
|
||||
scenes = self.image.find('Dimensions').find('S').find('Scenes')
|
||||
center_position = [float(pos) for pos in self.text(scenes[0].find('CenterPosition')).split(',')]
|
||||
except AttributeError:
|
||||
center_position = [0, 0]
|
||||
return center_position[0], center_position[1], None
|
||||
|
||||
@cached_property
|
||||
def channels_im(self) -> dict:
|
||||
return {channel.attrib['Id']: channel for channel in self.image.find('Dimensions').find('Channels')}
|
||||
|
||||
@cached_property
|
||||
def channels_ds(self) -> dict:
|
||||
return {channel.attrib['Id']: channel for channel in self.display_setting.find('Channels')}
|
||||
|
||||
@cached_property
|
||||
def channels_ts(self) -> dict:
|
||||
return {detector.attrib['Id']: track_setup
|
||||
for track_setup in
|
||||
self.experiment.find('ExperimentBlocks').find('AcquisitionBlock').find('MultiTrackSetup')
|
||||
for detector in track_setup.find('Detectors')}
|
||||
|
||||
def get_channels(self) -> None:
|
||||
if self.version == '1.0':
|
||||
for idx, (key, channel) in enumerate(self.channels_im.items()):
|
||||
detector_settings = channel.find('DetectorSettings')
|
||||
laser_scan_info = channel.find('LaserScanInfo')
|
||||
detector = detector_settings.find('Detector')
|
||||
try:
|
||||
binning = model.Binning(self.text(detector_settings.find('Binning')))
|
||||
except ValueError:
|
||||
binning = model.Binning.OTHER
|
||||
|
||||
filterset = self.text(self.channels_ts[key].find('BeamSplitters')[0].find('Filter'))
|
||||
filterset_idx = [filterset.model for filterset in self.ome.instruments[0].filter_sets].index(filterset)
|
||||
|
||||
light_sources_settings = channel.find('LightSourcesSettings')
|
||||
# no space in ome for multiple lightsources simultaneously
|
||||
if len(light_sources_settings) > idx:
|
||||
light_source_settings = light_sources_settings[idx]
|
||||
else:
|
||||
light_source_settings = light_sources_settings[0]
|
||||
light_source_settings = model.LightSourceSettings(
|
||||
id=light_source_settings.find('LightSource').attrib['Id'],
|
||||
attenuation=float(self.text(light_source_settings.find('Attenuation'))),
|
||||
wavelength=float(self.text(light_source_settings.find('Wavelength'))),
|
||||
wavelength_unit=self.nm)
|
||||
|
||||
self.ome.images[0].pixels.channels.append(
|
||||
model.Channel(
|
||||
id=f'Channel:{idx}',
|
||||
name=channel.attrib['Name'],
|
||||
acquisition_mode=self.text(channel.find('AcquisitionMode')), # type: ignore
|
||||
color=model.Color(self.text(self.channels_ds[channel.attrib['Id']].find('Color'), 'white')),
|
||||
detector_settings=model.DetectorSettings(id=detector.attrib['Id'], binning=binning),
|
||||
# emission_wavelength=text(channel.find('EmissionWavelength')), # TODO: fix
|
||||
excitation_wavelength=light_source_settings.wavelength,
|
||||
filter_set_ref=model.FilterSetRef(id=self.ome.instruments[0].filter_sets[filterset_idx].id),
|
||||
illumination_type=self.text(channel.find('IlluminationType')), # type: ignore
|
||||
light_source_settings=light_source_settings,
|
||||
samples_per_pixel=int(self.text(laser_scan_info.find('Averaging')))))
|
||||
elif self.version in ('1.1', '1.2'):
|
||||
for idx, (key, channel) in enumerate(self.channels_im.items()):
|
||||
detector_settings = channel.find('DetectorSettings')
|
||||
laser_scan_info = channel.find('LaserScanInfo')
|
||||
detector = detector_settings.find('Detector')
|
||||
try:
|
||||
color = model.Color(self.text(self.channels_ds[channel.attrib['Id']].find('Color'), 'white'))
|
||||
except Exception: # noqa
|
||||
color = None
|
||||
try:
|
||||
if (i := self.text(channel.find('EmissionWavelength'))) != '0':
|
||||
emission_wavelength = float(i)
|
||||
else:
|
||||
emission_wavelength = None
|
||||
except Exception: # noqa
|
||||
emission_wavelength = None
|
||||
if laser_scan_info is not None:
|
||||
samples_per_pixel = int(self.text(laser_scan_info.find('Averaging'), '1'))
|
||||
else:
|
||||
samples_per_pixel = 1
|
||||
try:
|
||||
binning = model.Binning(self.text(detector_settings.find('Binning')))
|
||||
except ValueError:
|
||||
binning = model.Binning.OTHER
|
||||
|
||||
light_sources_settings = channel.find('LightSourcesSettings')
|
||||
# no space in ome for multiple lightsources simultaneously
|
||||
if light_sources_settings is not None:
|
||||
light_source_settings = light_sources_settings[0]
|
||||
light_source_settings = model.LightSourceSettings(
|
||||
id='LightSource:' + '_'.join([light_source_settings.find('LightSource').attrib['Id']
|
||||
for light_source_settings in light_sources_settings]),
|
||||
attenuation=self.try_default(float, None, self.text(light_source_settings.find('Attenuation'))),
|
||||
wavelength=self.try_default(float, None, self.text(light_source_settings.find('Wavelength'))),
|
||||
wavelength_unit=self.nm)
|
||||
else:
|
||||
light_source_settings = None
|
||||
|
||||
self.ome.images[0].pixels.channels.append(
|
||||
model.Channel(
|
||||
id=f'Channel:{idx}',
|
||||
name=channel.attrib['Name'],
|
||||
acquisition_mode=self.text(channel.find('AcquisitionMode')).replace( # type: ignore
|
||||
'SingleMoleculeLocalisation', 'SingleMoleculeImaging'),
|
||||
color=color,
|
||||
detector_settings=model.DetectorSettings(
|
||||
id=detector.attrib['Id'].replace(' ', ""),
|
||||
binning=binning),
|
||||
emission_wavelength=emission_wavelength,
|
||||
excitation_wavelength=self.try_default(float, None,
|
||||
self.text(channel.find('ExcitationWavelength'))),
|
||||
# filter_set_ref=model.FilterSetRef(id=ome.instruments[0].filter_sets[filterset_idx].id),
|
||||
illumination_type=self.text(channel.find('IlluminationType')), # type: ignore
|
||||
light_source_settings=light_source_settings,
|
||||
samples_per_pixel=samples_per_pixel))
|
||||
|
||||
def get_planes(self) -> None:
|
||||
try:
|
||||
exposure_times = [float(self.text(channel.find('LaserScanInfo').find('FrameTime')))
|
||||
for channel in self.channels_im.values()]
|
||||
except Exception: # noqa
|
||||
exposure_times = [None] * len(self.channels_im)
|
||||
delta_ts = self.attachments['TimeStamps'].data()
|
||||
dt = np.diff(delta_ts)
|
||||
if len(dt) and np.std(dt) / np.mean(dt) > 0.02:
|
||||
dt = np.median(dt[dt > 0])
|
||||
delta_ts = dt * np.arange(len(delta_ts))
|
||||
warnings.warn(f'delta_t is inconsistent, using median value: {dt}')
|
||||
|
||||
for t, z, c in product(range(self.size_t), range(self.size_z), range(self.size_c)):
|
||||
self.ome.images[0].pixels.planes.append(
|
||||
model.Plane(the_c=c, the_z=z, the_t=t, delta_t=delta_ts[t],
|
||||
exposure_time=exposure_times[c],
|
||||
position_x=self.positions[0], position_x_unit=self.um,
|
||||
position_y=self.positions[1], position_y_unit=self.um,
|
||||
position_z=self.positions[2], position_z_unit=self.um))
|
||||
|
||||
def get_annotations(self) -> None:
|
||||
idx = 0
|
||||
for layer in [] if (ml := self.metadata.find('Layers')) is None else ml:
|
||||
rectangle = layer.find('Elements').find('Rectangle')
|
||||
if rectangle is not None:
|
||||
geometry = rectangle.find('Geometry')
|
||||
roi = model.ROI(id=f'ROI:{idx}', description=self.text(layer.find('Usage')))
|
||||
roi.union.append(
|
||||
model.Rectangle(
|
||||
id='Shape:0:0',
|
||||
height=float(self.text(geometry.find('Height'))),
|
||||
width=float(self.text(geometry.find('Width'))),
|
||||
x=float(self.text(geometry.find('Left'))),
|
||||
y=float(self.text(geometry.find('Top')))))
|
||||
self.ome.rois.append(roi)
|
||||
self.ome.images[0].roi_refs.append(model.ROIRef(id=f'ROI:{idx}'))
|
||||
idx += 1
|
||||
@@ -1,59 +0,0 @@
|
||||
from abc import ABC
|
||||
from itertools import product
|
||||
from pathlib import Path
|
||||
from struct import unpack
|
||||
from warnings import warn
|
||||
|
||||
import numpy as np
|
||||
from ome_types import model
|
||||
from tifffile import TiffFile
|
||||
|
||||
from .. import AbstractReader
|
||||
|
||||
|
||||
class Reader(AbstractReader, ABC):
|
||||
""" Can read some tif files written with Fiji which are broken because Fiji didn't finish writing. """
|
||||
priority = 90
|
||||
do_not_pickle = 'reader'
|
||||
|
||||
@staticmethod
|
||||
def _can_open(path):
|
||||
if isinstance(path, Path) and path.suffix in ('.tif', '.tiff'):
|
||||
with TiffFile(path) as tif:
|
||||
return tif.is_imagej and not tif.is_bigtiff
|
||||
else:
|
||||
return False
|
||||
|
||||
def __frame__(self, c, z, t): # Override this, return the frame at c, z, t
|
||||
self.reader.filehandle.seek(self.offset + t * self.count)
|
||||
return np.reshape(unpack(self.fmt, self.reader.filehandle.read(self.count)), self.base_shape['yx'])
|
||||
|
||||
def open(self):
|
||||
warn(f'File {self.path.name} is probably damaged, opening with fijiread.')
|
||||
self.reader = TiffFile(self.path)
|
||||
assert self.reader.pages[0].compression == 1, 'Can only read uncompressed tiff files.'
|
||||
assert self.reader.pages[0].samplesperpixel == 1, 'Can only read 1 sample per pixel.'
|
||||
self.offset = self.reader.pages[0].dataoffsets[0] # noqa
|
||||
self.count = self.reader.pages[0].databytecounts[0] # noqa
|
||||
self.bytes_per_sample = self.reader.pages[0].bitspersample // 8 # noqa
|
||||
self.fmt = self.reader.byteorder + self.count // self.bytes_per_sample * 'BHILQ'[self.bytes_per_sample - 1] # noqa
|
||||
|
||||
def close(self):
|
||||
self.reader.close()
|
||||
|
||||
def get_ome(self):
|
||||
size_y, size_x = self.reader.pages[0].shape
|
||||
size_c, size_z = 1, 1
|
||||
size_t = int(np.floor((self.reader.filehandle.size - self.reader.pages[0].dataoffsets[0]) / self.count))
|
||||
pixel_type = model.PixelType(self.reader.pages[0].dtype.name)
|
||||
ome = model.OME()
|
||||
ome.instruments.append(model.Instrument())
|
||||
ome.images.append(
|
||||
model.Image(
|
||||
pixels=model.Pixels(
|
||||
size_c=size_c, size_z=size_z, size_t=size_t, size_x=size_x, size_y=size_y,
|
||||
dimension_order='XYCZT', type=pixel_type),
|
||||
objective_settings=model.ObjectiveSettings(id='Objective:0')))
|
||||
for c, z, t in product(range(size_c), range(size_z), range(size_t)):
|
||||
ome.images[0].pixels.planes.append(model.Plane(the_c=c, the_z=z, the_t=t, delta_t=0))
|
||||
return ome
|
||||
@@ -1,80 +0,0 @@
|
||||
import re
|
||||
from abc import ABC
|
||||
from pathlib import Path
|
||||
from typing import Optional
|
||||
|
||||
import tifffile
|
||||
from ome_types import model
|
||||
from ome_types.units import _quantity_property # noqa
|
||||
|
||||
from .. import AbstractReader
|
||||
|
||||
|
||||
class Reader(AbstractReader, ABC):
|
||||
priority = 20
|
||||
do_not_pickle = 'last_tif'
|
||||
|
||||
@staticmethod
|
||||
def _can_open(path):
|
||||
return isinstance(path, Path) and (path.is_dir() or
|
||||
(path.parent.is_dir() and path.name.lower().startswith('pos')))
|
||||
|
||||
@staticmethod
|
||||
def get_positions(path: str | Path) -> Optional[list[int]]:
|
||||
pat = re.compile(rf's(\d)_t\d+\.(tif|TIF)$')
|
||||
return sorted({int(m.group(1)) for file in Path(path).iterdir() if (m := pat.search(file.name))})
|
||||
|
||||
def get_ome(self):
|
||||
ome = model.OME()
|
||||
tif = self.get_tif(0)
|
||||
metadata = tif.metaseries_metadata
|
||||
size_z = len(tif.pages)
|
||||
page = tif.pages[0]
|
||||
shape = {axis.lower(): size for axis, size in zip(page.axes, page.shape)}
|
||||
size_x, size_y = shape['x'], shape['y']
|
||||
|
||||
ome.instruments.append(model.Instrument())
|
||||
|
||||
size_c = 1
|
||||
size_t = max(self.filedict.keys()) + 1
|
||||
pixel_type = f"uint{metadata['PlaneInfo']['bits-per-pixel']}"
|
||||
ome.images.append(
|
||||
model.Image(
|
||||
pixels=model.Pixels(
|
||||
size_c=size_c, size_z=size_z, size_t=size_t,
|
||||
size_x=size_x, size_y=size_y,
|
||||
dimension_order='XYCZT', type=pixel_type),
|
||||
objective_settings=model.ObjectiveSettings(id='Objective:0')))
|
||||
return ome
|
||||
|
||||
def open(self):
|
||||
pat = re.compile(rf's{self.series}_t\d+\.(tif|TIF)$')
|
||||
filelist = sorted([file for file in self.path.iterdir() if pat.search(file.name)])
|
||||
pattern = re.compile(r't(\d+)$')
|
||||
self.filedict = {int(pattern.search(file.stem).group(1)) - 1: file for file in filelist}
|
||||
if len(self.filedict) == 0:
|
||||
raise FileNotFoundError
|
||||
self.last_tif = 0, tifffile.TiffFile(self.filedict[0])
|
||||
|
||||
def close(self) -> None:
|
||||
self.last_tif[1].close()
|
||||
|
||||
def get_tif(self, t: int = None):
|
||||
last_t, tif = self.last_tif
|
||||
if (t is None or t == last_t) and not tif.filehandle.closed:
|
||||
return tif
|
||||
else:
|
||||
tif.close()
|
||||
tif = tifffile.TiffFile(self.filedict[t])
|
||||
self.last_tif = t, tif
|
||||
return tif
|
||||
|
||||
def __frame__(self, c=0, z=0, t=0):
|
||||
tif = self.get_tif(t)
|
||||
page = tif.pages[z]
|
||||
if page.axes.upper() == 'YX':
|
||||
return page.asarray()
|
||||
elif page.axes.upper() == 'XY':
|
||||
return page.asarray().T
|
||||
else:
|
||||
raise NotImplementedError(f'reading axes {page.axes} is not implemented')
|
||||
@@ -1,53 +0,0 @@
|
||||
from abc import ABC
|
||||
from itertools import product
|
||||
|
||||
import numpy as np
|
||||
from ome_types import model
|
||||
|
||||
from .. import AbstractReader
|
||||
|
||||
|
||||
class Reader(AbstractReader, ABC):
|
||||
priority = 20
|
||||
|
||||
@staticmethod
|
||||
def _can_open(path):
|
||||
return isinstance(path, np.ndarray) and 1 <= path.ndim <= 5
|
||||
|
||||
def get_ome(self):
|
||||
def shape(size_x=1, size_y=1, size_c=1, size_z=1, size_t=1): # noqa
|
||||
return size_x, size_y, size_c, size_z, size_t
|
||||
size_x, size_y, size_c, size_z, size_t = shape(*self.array.shape)
|
||||
try:
|
||||
pixel_type = model.PixelType(self.array.dtype.name)
|
||||
except ValueError:
|
||||
if self.array.dtype.name.startswith('int'):
|
||||
pixel_type = model.PixelType('int32')
|
||||
else:
|
||||
pixel_type = model.PixelType('float')
|
||||
|
||||
ome = model.OME()
|
||||
ome.instruments.append(model.Instrument())
|
||||
ome.images.append(
|
||||
model.Image(
|
||||
pixels=model.Pixels(
|
||||
size_c=size_c, size_z=size_z, size_t=size_t, size_x=size_x, size_y=size_y,
|
||||
dimension_order='XYCZT', type=pixel_type),
|
||||
objective_settings=model.ObjectiveSettings(id='Objective:0')))
|
||||
for c, z, t in product(range(size_c), range(size_z), range(size_t)):
|
||||
ome.images[0].pixels.planes.append(model.Plane(the_c=c, the_z=z, the_t=t, delta_t=0))
|
||||
return ome
|
||||
|
||||
def open(self):
|
||||
if isinstance(self.path, np.ndarray):
|
||||
self.array = np.array(self.path)
|
||||
while self.array.ndim < 5:
|
||||
self.array = np.expand_dims(self.array, -1) # noqa
|
||||
self.path = 'numpy array'
|
||||
|
||||
def __frame__(self, c, z, t):
|
||||
frame = self.array[:, :, c, z, t]
|
||||
if self.axes.find('y') > self.axes.find('x'):
|
||||
return frame.T
|
||||
else:
|
||||
return frame
|
||||
@@ -1,146 +0,0 @@
|
||||
import re
|
||||
from abc import ABC
|
||||
from datetime import datetime
|
||||
from itertools import product
|
||||
from pathlib import Path
|
||||
|
||||
import tifffile
|
||||
import yaml
|
||||
from ome_types import model
|
||||
from ome_types.units import _quantity_property # noqa
|
||||
|
||||
from .. import AbstractReader
|
||||
|
||||
|
||||
def lazy_property(function, field, *arg_fields):
|
||||
def lazy(self):
|
||||
if self.__dict__.get(field) is None:
|
||||
self.__dict__[field] = function(*[getattr(self, arg_field) for arg_field in arg_fields])
|
||||
try:
|
||||
self.model_fields_set.add(field)
|
||||
except Exception: # noqa
|
||||
pass
|
||||
return self.__dict__[field]
|
||||
return property(lazy)
|
||||
|
||||
|
||||
class Plane(model.Plane):
|
||||
""" Lazily retrieve delta_t from metadata """
|
||||
def __init__(self, t0, file, **kwargs): # noqa
|
||||
super().__init__(**kwargs)
|
||||
# setting fields here because they would be removed by ome_types/pydantic after class definition
|
||||
setattr(self.__class__, 'delta_t', lazy_property(self.get_delta_t, 'delta_t', 't0', 'file'))
|
||||
setattr(self.__class__, 'delta_t_quantity', _quantity_property('delta_t'))
|
||||
self.__dict__['t0'] = t0 # noqa
|
||||
self.__dict__['file'] = file # noqa
|
||||
|
||||
@staticmethod
|
||||
def get_delta_t(t0, file):
|
||||
with tifffile.TiffFile(file) as tif:
|
||||
info = yaml.safe_load(tif.pages[0].tags[50839].value['Info'])
|
||||
return float((datetime.strptime(info['Time'], '%Y-%m-%d %H:%M:%S %z') - t0).seconds)
|
||||
|
||||
|
||||
class Reader(AbstractReader, ABC):
|
||||
priority = 10
|
||||
|
||||
@staticmethod
|
||||
def _can_open(path):
|
||||
pat = re.compile(r'(?:\d+-)?Pos.*', re.IGNORECASE)
|
||||
return (isinstance(path, Path) and path.is_dir() and
|
||||
(pat.match(path.name) or any(file.is_dir() and pat.match(file.stem) for file in path.iterdir())))
|
||||
|
||||
def get_ome(self):
|
||||
ome = model.OME()
|
||||
with tifffile.TiffFile(self.filedict[0, 0, 0]) as tif:
|
||||
metadata = {key: yaml.safe_load(value) for key, value in tif.pages[0].tags[50839].value.items()}
|
||||
ome.experimenters.append(
|
||||
model.Experimenter(id='Experimenter:0', user_name=metadata['Info']['Summary']['UserName']))
|
||||
objective_str = metadata['Info']['ZeissObjectiveTurret-Label']
|
||||
ome.instruments.append(model.Instrument())
|
||||
ome.instruments[0].objectives.append(
|
||||
model.Objective(
|
||||
id='Objective:0', manufacturer='Zeiss', model=objective_str,
|
||||
nominal_magnification=float(re.findall(r'(\d+)x', objective_str)[0]),
|
||||
lens_na=float(re.findall(r'/(\d\.\d+)', objective_str)[0]),
|
||||
immersion=model.Objective_Immersion.OIL if 'oil' in objective_str.lower() else None))
|
||||
tubelens_str = metadata['Info']['ZeissOptovar-Label']
|
||||
ome.instruments[0].objectives.append(
|
||||
model.Objective(
|
||||
id='Objective:Tubelens:0', manufacturer='Zeiss', model=tubelens_str,
|
||||
nominal_magnification=float(re.findall(r'\d?\d*[,.]?\d+(?=x$)', tubelens_str)[0].replace(',', '.'))))
|
||||
ome.instruments[0].detectors.append(
|
||||
model.Detector(
|
||||
id='Detector:0', amplification_gain=100))
|
||||
ome.instruments[0].filter_sets.append(
|
||||
model.FilterSet(id='FilterSet:0', model=metadata['Info']['ZeissReflectorTurret-Label']))
|
||||
|
||||
pxsize = metadata['Info']['PixelSizeUm']
|
||||
pxsize_cam = 6.5 if 'Hamamatsu' in metadata['Info']['Core-Camera'] else None
|
||||
if pxsize == 0:
|
||||
pxsize = pxsize_cam / ome.instruments[0].objectives[0].nominal_magnification
|
||||
pixel_type = metadata['Info']['PixelType'].lower()
|
||||
if pixel_type.startswith('gray'):
|
||||
pixel_type = 'uint' + pixel_type[4:]
|
||||
else:
|
||||
pixel_type = 'uint16' # assume
|
||||
|
||||
size_c, size_z, size_t = (max(i) + 1 for i in zip(*self.filedict.keys()))
|
||||
t0 = datetime.strptime(metadata['Info']['Time'], '%Y-%m-%d %H:%M:%S %z')
|
||||
ome.images.append(
|
||||
model.Image(
|
||||
pixels=model.Pixels(
|
||||
size_c=size_c, size_z=size_z, size_t=size_t,
|
||||
size_x=metadata['Info']['Width'], size_y=metadata['Info']['Height'],
|
||||
dimension_order='XYCZT', # type: ignore
|
||||
type=pixel_type, physical_size_x=pxsize, physical_size_y=pxsize,
|
||||
physical_size_z=metadata['Info']['Summary']['z-step_um']),
|
||||
objective_settings=model.ObjectiveSettings(id='Objective:0')))
|
||||
|
||||
for c, z, t in product(range(size_c), range(size_z), range(size_t)):
|
||||
ome.images[0].pixels.planes.append(
|
||||
Plane(t0, self.filedict[c, z, t],
|
||||
the_c=c, the_z=z, the_t=t, exposure_time=metadata['Info']['Exposure-ms'] / 1000))
|
||||
|
||||
# compare channel names from metadata with filenames
|
||||
pattern_c = re.compile(r'img_\d{3,}_(.*)_\d{3,}$', re.IGNORECASE)
|
||||
for c in range(size_c):
|
||||
ome.images[0].pixels.channels.append(
|
||||
model.Channel(
|
||||
id=f'Channel:{c}', name=pattern_c.findall(self.filedict[c, 0, 0].stem)[0],
|
||||
detector_settings=model.DetectorSettings(
|
||||
id='Detector:0', binning=metadata['Info']['Hamamatsu_sCMOS-Binning']),
|
||||
filter_set_ref=model.FilterSetRef(id='FilterSet:0')))
|
||||
return ome
|
||||
|
||||
def open(self):
|
||||
# /some_path/Pos4: path = /some_path, series = 4
|
||||
# /some_path/5-Pos_001_005: path = /some_path/5-Pos_001_005, series = 0
|
||||
if re.match(r'(?:\d+-)?Pos.*', self.path.name, re.IGNORECASE) is None:
|
||||
pat = re.compile(rf'^(?:\d+-)?Pos{self.series}$', re.IGNORECASE)
|
||||
files = sorted(file for file in self.path.iterdir() if pat.match(file.name))
|
||||
if len(files):
|
||||
path = files[0]
|
||||
else:
|
||||
raise FileNotFoundError(self.path / pat.pattern)
|
||||
else:
|
||||
path = self.path
|
||||
|
||||
pat = re.compile(r'^img_\d{3,}.*\d{3,}.*\.tif$', re.IGNORECASE)
|
||||
filelist = sorted([file for file in path.iterdir() if pat.search(file.name)])
|
||||
with tifffile.TiffFile(self.path / filelist[0]) as tif:
|
||||
metadata = {key: yaml.safe_load(value) for key, value in tif.pages[0].tags[50839].value.items()}
|
||||
|
||||
# compare channel names from metadata with filenames
|
||||
cnamelist = metadata['Info']['Summary']['ChNames']
|
||||
cnamelist = [c for c in cnamelist if any([c in f.name for f in filelist])]
|
||||
|
||||
pattern_c = re.compile(r'img_\d{3,}_(.*)_\d{3,}$', re.IGNORECASE)
|
||||
pattern_z = re.compile(r'(\d{3,})$')
|
||||
pattern_t = re.compile(r'img_(\d{3,})', re.IGNORECASE)
|
||||
self.filedict = {(cnamelist.index(pattern_c.findall(file.stem)[0]), # noqa
|
||||
int(pattern_z.findall(file.stem)[0]),
|
||||
int(pattern_t.findall(file.stem)[0])): file for file in filelist}
|
||||
|
||||
def __frame__(self, c=0, z=0, t=0):
|
||||
return tifffile.imread(self.path / self.filedict[(c, z, t)])
|
||||
@@ -1,85 +0,0 @@
|
||||
from abc import ABC
|
||||
from functools import cached_property
|
||||
from itertools import product
|
||||
from pathlib import Path
|
||||
|
||||
import numpy as np
|
||||
import tifffile
|
||||
import yaml
|
||||
from ome_types import model
|
||||
|
||||
from .. import AbstractReader
|
||||
|
||||
|
||||
class Reader(AbstractReader, ABC):
|
||||
priority = 0
|
||||
do_not_pickle = 'reader'
|
||||
|
||||
@staticmethod
|
||||
def _can_open(path):
|
||||
if isinstance(path, Path) and path.suffix in ('.tif', '.tiff'):
|
||||
with tifffile.TiffFile(path) as tif:
|
||||
return tif.is_imagej and tif.pages[-1]._nextifd() == 0 # noqa
|
||||
else:
|
||||
return False
|
||||
|
||||
@cached_property
|
||||
def metadata(self):
|
||||
return {key: yaml.safe_load(value) if isinstance(value, str) else value
|
||||
for key, value in self.reader.imagej_metadata.items()}
|
||||
|
||||
def get_ome(self):
|
||||
page = self.reader.pages[0]
|
||||
size_y = page.imagelength
|
||||
size_x = page.imagewidth
|
||||
if self.p_ndim == 3:
|
||||
size_c = page.samplesperpixel
|
||||
size_t = self.metadata.get('frames', 1) # // C
|
||||
else:
|
||||
size_c = self.metadata.get('channels', 1)
|
||||
size_t = self.metadata.get('frames', 1)
|
||||
size_z = self.metadata.get('slices', 1)
|
||||
if 282 in page.tags and 296 in page.tags and page.tags[296].value == 1:
|
||||
f = page.tags[282].value
|
||||
pxsize = f[1] / f[0]
|
||||
else:
|
||||
pxsize = None
|
||||
|
||||
dtype = page.dtype.name
|
||||
if dtype not in ('int8', 'int16', 'int32', 'uint8', 'uint16', 'uint32',
|
||||
'float', 'double', 'complex', 'double-complex', 'bit'):
|
||||
dtype = 'float'
|
||||
|
||||
interval_t = self.metadata.get('interval', 0)
|
||||
|
||||
ome = model.OME()
|
||||
ome.instruments.append(model.Instrument(id='Instrument:0'))
|
||||
ome.instruments[0].objectives.append(model.Objective(id='Objective:0'))
|
||||
ome.images.append(
|
||||
model.Image(
|
||||
id='Image:0',
|
||||
pixels=model.Pixels(
|
||||
id='Pixels:0',
|
||||
size_c=size_c, size_z=size_z, size_t=size_t, size_x=size_x, size_y=size_y,
|
||||
dimension_order='XYCZT', type=dtype, # type: ignore
|
||||
physical_size_x=pxsize, physical_size_y=pxsize),
|
||||
objective_settings=model.ObjectiveSettings(id='Objective:0')))
|
||||
for c, z, t in product(range(size_c), range(size_z), range(size_t)):
|
||||
ome.images[0].pixels.planes.append(model.Plane(the_c=c, the_z=z, the_t=t, delta_t=interval_t * t))
|
||||
return ome
|
||||
|
||||
def open(self):
|
||||
self.reader = tifffile.TiffFile(self.path)
|
||||
page = self.reader.pages[0]
|
||||
self.p_ndim = page.ndim # noqa
|
||||
if self.p_ndim == 3:
|
||||
self.p_transpose = [i for i in [page.axes.find(j) for j in 'SYX'] if i >= 0] # noqa
|
||||
|
||||
def close(self):
|
||||
self.reader.close()
|
||||
|
||||
def __frame__(self, c, z, t):
|
||||
if self.p_ndim == 3:
|
||||
return np.transpose(self.reader.asarray(z + t * self.base_shape['z']), self.p_transpose)[c]
|
||||
else:
|
||||
return self.reader.asarray(c + z * self.base_shape['c'] + t * self.base_shape['c'] * self.base_shape['z'])
|
||||
@@ -1,7 +0,0 @@
|
||||
#Insight Transform File V1.0
|
||||
#Transform 0
|
||||
Transform: CompositeTransform_double_2_2
|
||||
#Transform 1
|
||||
Transform: AffineTransform_double_2_2
|
||||
Parameters: 1 0 0 1 0 0
|
||||
FixedParameters: 255.5 255.5
|
||||
@@ -1,458 +0,0 @@
|
||||
import warnings
|
||||
from copy import deepcopy
|
||||
from pathlib import Path
|
||||
|
||||
import numpy as np
|
||||
import yaml
|
||||
from parfor import Chunks, pmap
|
||||
from skimage import filters
|
||||
from tiffwrite import IJTiffFile
|
||||
from tqdm.auto import tqdm
|
||||
|
||||
try:
|
||||
# best if SimpleElastix is installed: https://simpleelastix.readthedocs.io/GettingStarted.html
|
||||
import SimpleITK as sitk # noqa
|
||||
except ImportError:
|
||||
sitk = None
|
||||
|
||||
try:
|
||||
from pandas import DataFrame, Series, concat
|
||||
except ImportError:
|
||||
DataFrame, Series, concat = None, None, None
|
||||
|
||||
|
||||
if hasattr(yaml, 'full_load'):
|
||||
yamlload = yaml.full_load
|
||||
else:
|
||||
yamlload = yaml.load
|
||||
|
||||
|
||||
class Transforms(dict):
|
||||
def __init__(self, *args, **kwargs):
|
||||
super().__init__(*args, **kwargs)
|
||||
self.default = Transform()
|
||||
|
||||
@classmethod
|
||||
def from_file(cls, file, C=True, T=True):
|
||||
with open(Path(file).with_suffix('.yml')) as f:
|
||||
return cls.from_dict(yamlload(f), C, T)
|
||||
|
||||
@classmethod
|
||||
def from_dict(cls, d, C=True, T=True):
|
||||
new = cls()
|
||||
for key, value in d.items():
|
||||
if isinstance(key, str) and C:
|
||||
new[key.replace(r'\:', ':').replace('\\\\', '\\')] = Transform.from_dict(value)
|
||||
elif T:
|
||||
new[key] = Transform.from_dict(value)
|
||||
return new
|
||||
|
||||
@classmethod
|
||||
def from_shifts(cls, shifts):
|
||||
new = cls()
|
||||
for key, shift in shifts.items():
|
||||
new[key] = Transform.from_shift(shift)
|
||||
return new
|
||||
|
||||
def __mul__(self, other):
|
||||
new = Transforms()
|
||||
if isinstance(other, Transforms):
|
||||
for key0, value0 in self.items():
|
||||
for key1, value1 in other.items():
|
||||
new[key0 + key1] = value0 * value1
|
||||
return new
|
||||
elif other is None:
|
||||
return self
|
||||
else:
|
||||
for key in self.keys():
|
||||
new[key] = self[key] * other
|
||||
return new
|
||||
|
||||
def asdict(self):
|
||||
return {key.replace('\\', '\\\\').replace(':', r'\:') if isinstance(key, str) else key: value.asdict()
|
||||
for key, value in self.items()}
|
||||
|
||||
def __getitem__(self, item):
|
||||
return np.prod([self[i] for i in item[::-1]]) if isinstance(item, tuple) else super().__getitem__(item)
|
||||
|
||||
def __missing__(self, key):
|
||||
return self.default
|
||||
|
||||
def __getstate__(self):
|
||||
return self.__dict__
|
||||
|
||||
def __setstate__(self, state):
|
||||
self.__dict__.update(state)
|
||||
|
||||
def __hash__(self):
|
||||
return hash(frozenset((*self.__dict__.items(), *self.items())))
|
||||
|
||||
def save(self, file):
|
||||
with open(Path(file).with_suffix('.yml'), 'w') as f:
|
||||
yaml.safe_dump(self.asdict(), f, default_flow_style=None)
|
||||
|
||||
def copy(self):
|
||||
return deepcopy(self)
|
||||
|
||||
def adapt(self, origin, shape, channel_names):
|
||||
def key_map(a, b):
|
||||
def fun(b, key_a):
|
||||
for key_b in b:
|
||||
if key_b in key_a or key_a in key_b:
|
||||
return key_a, key_b
|
||||
|
||||
return {n[0]: n[1] for key_a in a if (n := fun(b, key_a))}
|
||||
|
||||
for value in self.values():
|
||||
value.adapt(origin, shape)
|
||||
self.default.adapt(origin, shape)
|
||||
transform_channels = {key for key in self.keys() if isinstance(key, str)}
|
||||
if set(channel_names) - transform_channels:
|
||||
mapping = key_map(channel_names, transform_channels)
|
||||
warnings.warn(f'The image file and the transform do not have the same channels,'
|
||||
f' creating a mapping: {mapping}')
|
||||
for key_im, key_t in mapping.items():
|
||||
self[key_im] = self[key_t]
|
||||
|
||||
@property
|
||||
def inverse(self):
|
||||
# TODO: check for C@T
|
||||
inverse = self.copy()
|
||||
for key, value in self.items():
|
||||
inverse[key] = value.inverse
|
||||
return inverse
|
||||
|
||||
def coords_pandas(self, array, channel_names, columns=None):
|
||||
if isinstance(array, DataFrame):
|
||||
return concat([self.coords_pandas(row, channel_names, columns) for _, row in array.iterrows()], axis=1).T
|
||||
elif isinstance(array, Series):
|
||||
key = []
|
||||
if 'C' in array:
|
||||
key.append(channel_names[int(array['C'])])
|
||||
if 'T' in array:
|
||||
key.append(int(array['T']))
|
||||
return self[tuple(key)].coords(array, columns)
|
||||
else:
|
||||
raise TypeError('Not a pandas DataFrame or Series.')
|
||||
|
||||
def with_beads(self, cyllens, bead_files):
|
||||
assert len(bead_files) > 0, 'At least one file is needed to calculate the registration.'
|
||||
transforms = [self.calculate_channel_transforms(file, cyllens) for file in bead_files]
|
||||
for key in {key for transform in transforms for key in transform.keys()}:
|
||||
new_transforms = [transform[key] for transform in transforms if key in transform]
|
||||
if len(new_transforms) == 1:
|
||||
self[key] = new_transforms[0]
|
||||
else:
|
||||
self[key] = Transform()
|
||||
self[key].parameters = np.mean([t.parameters for t in new_transforms], 0)
|
||||
self[key].dparameters = (np.std([t.parameters for t in new_transforms], 0) /
|
||||
np.sqrt(len(new_transforms))).tolist()
|
||||
return self
|
||||
|
||||
@staticmethod
|
||||
def get_bead_files(path):
|
||||
from . import Imread
|
||||
files = []
|
||||
for file in path.iterdir():
|
||||
if file.name.lower().startswith('beads'):
|
||||
try:
|
||||
with Imread(file):
|
||||
files.append(file)
|
||||
except Exception:
|
||||
pass
|
||||
files = sorted(files)
|
||||
if not files:
|
||||
raise Exception('No bead file found!')
|
||||
checked_files = []
|
||||
for file in files:
|
||||
try:
|
||||
if file.is_dir():
|
||||
file /= 'Pos0'
|
||||
with Imread(file): # check for errors opening the file
|
||||
checked_files.append(file)
|
||||
except (Exception,):
|
||||
continue
|
||||
if not checked_files:
|
||||
raise Exception('No bead file found!')
|
||||
return checked_files
|
||||
|
||||
@staticmethod
|
||||
def calculate_channel_transforms(bead_file, cyllens):
|
||||
""" When no channel is not transformed by a cylindrical lens, assume that the image is scaled by a factor 1.162
|
||||
in the horizontal direction """
|
||||
from . import Imread
|
||||
|
||||
with Imread(bead_file, axes='zcyx') as im: # noqa
|
||||
max_ims = im.max('z')
|
||||
goodch = [c for c, max_im in enumerate(max_ims) if not im.is_noise(max_im)]
|
||||
if not goodch:
|
||||
goodch = list(range(len(max_ims)))
|
||||
untransformed = [c for c in range(im.shape['c']) if cyllens[im.detector[c]].lower() == 'none']
|
||||
|
||||
good_and_untrans = sorted(set(goodch) & set(untransformed))
|
||||
if good_and_untrans:
|
||||
masterch = good_and_untrans[0]
|
||||
else:
|
||||
masterch = goodch[0]
|
||||
transform = Transform()
|
||||
if not good_and_untrans:
|
||||
matrix = transform.matrix
|
||||
matrix[0, 0] = 0.86
|
||||
transform.matrix = matrix
|
||||
transforms = Transforms()
|
||||
for c in tqdm(goodch, desc='Calculating channel transforms'): # noqa
|
||||
if c == masterch:
|
||||
transforms[im.channel_names[c]] = transform
|
||||
else:
|
||||
transforms[im.channel_names[c]] = Transform.register(max_ims[masterch], max_ims[c]) * transform
|
||||
return transforms
|
||||
|
||||
@staticmethod
|
||||
def save_channel_transform_tiff(bead_files, tiffile):
|
||||
from . import Imread
|
||||
n_channels = 0
|
||||
for file in bead_files:
|
||||
with Imread(file) as im:
|
||||
n_channels = max(n_channels, im.shape['c'])
|
||||
with IJTiffFile(tiffile) as tif:
|
||||
for t, file in enumerate(bead_files):
|
||||
with Imread(file) as im:
|
||||
with Imread(file).with_transform() as jm:
|
||||
for c in range(im.shape['c']):
|
||||
tif.save(np.hstack((im(c=c, t=0).max('z'), jm(c=c, t=0).max('z'))), c, 0, t)
|
||||
|
||||
def with_drift(self, im):
|
||||
""" Calculate shifts relative to the first frame
|
||||
divide the sequence into groups,
|
||||
compare each frame to the frame in the middle of the group and compare these middle frames to each other
|
||||
"""
|
||||
im = im.transpose('tzycx')
|
||||
t_groups = [list(chunk) for chunk in Chunks(range(im.shape['t']), size=round(np.sqrt(im.shape['t'])))]
|
||||
t_keys = [int(np.round(np.mean(t_group))) for t_group in t_groups]
|
||||
t_pairs = [(int(np.round(np.mean(t_group))), frame) for t_group in t_groups for frame in t_group]
|
||||
t_pairs.extend(zip(t_keys, t_keys[1:]))
|
||||
fmaxz_keys = {t_key: filters.gaussian(im[t_key].max('z'), 5) for t_key in t_keys}
|
||||
|
||||
def fun(t_key_t, im, fmaxz_keys):
|
||||
t_key, t = t_key_t
|
||||
if t_key == t:
|
||||
return 0, 0
|
||||
else:
|
||||
fmaxz = filters.gaussian(im[t].max('z'), 5)
|
||||
return Transform.register(fmaxz_keys[t_key], fmaxz, 'translation').parameters[4:]
|
||||
|
||||
shifts = np.array(pmap(fun, t_pairs, (im, fmaxz_keys), desc='Calculating image shifts.'))
|
||||
shift_keys_cum = np.zeros(2)
|
||||
for shift_keys, t_group in zip(np.vstack((-shifts[0], shifts[im.shape['t']:])), t_groups):
|
||||
shift_keys_cum += shift_keys
|
||||
shifts[t_group] += shift_keys_cum
|
||||
|
||||
for i, shift in enumerate(shifts[:im.shape['t']]):
|
||||
self[i] = Transform.from_shift(shift)
|
||||
return self
|
||||
|
||||
|
||||
class Transform:
|
||||
def __init__(self):
|
||||
if sitk is None:
|
||||
self.transform = None
|
||||
else:
|
||||
self.transform = sitk.ReadTransform(str(Path(__file__).parent / 'transform.txt'))
|
||||
self.dparameters = [0., 0., 0., 0., 0., 0.]
|
||||
self.shape = [512., 512.]
|
||||
self.origin = [255.5, 255.5]
|
||||
self._last, self._inverse = None, None
|
||||
|
||||
def __reduce__(self):
|
||||
return self.from_dict, (self.asdict(),)
|
||||
|
||||
def __repr__(self):
|
||||
return self.asdict().__repr__()
|
||||
|
||||
def __str__(self):
|
||||
return self.asdict().__str__()
|
||||
|
||||
@classmethod
|
||||
def register(cls, fix, mov, kind=None):
|
||||
""" kind: 'affine', 'translation', 'rigid' """
|
||||
if sitk is None:
|
||||
raise ImportError('SimpleElastix is not installed: '
|
||||
'https://simpleelastix.readthedocs.io/GettingStarted.html')
|
||||
new = cls()
|
||||
kind = kind or 'affine'
|
||||
new.shape = fix.shape
|
||||
fix, mov = new.cast_image(fix), new.cast_image(mov)
|
||||
# TODO: implement RigidTransform
|
||||
tfilter = sitk.ElastixImageFilter()
|
||||
tfilter.LogToConsoleOff()
|
||||
tfilter.SetFixedImage(fix)
|
||||
tfilter.SetMovingImage(mov)
|
||||
tfilter.SetParameterMap(sitk.GetDefaultParameterMap(kind))
|
||||
tfilter.Execute()
|
||||
transform = tfilter.GetTransformParameterMap()[0]
|
||||
if kind == 'affine':
|
||||
new.parameters = [float(t) for t in transform['TransformParameters']]
|
||||
new.shape = [float(t) for t in transform['Size']]
|
||||
new.origin = [float(t) for t in transform['CenterOfRotationPoint']]
|
||||
elif kind == 'translation':
|
||||
new.parameters = [1.0, 0.0, 0.0, 1.0] + [float(t) for t in transform['TransformParameters']]
|
||||
new.shape = [float(t) for t in transform['Size']]
|
||||
new.origin = [(t - 1) / 2 for t in new.shape]
|
||||
else:
|
||||
raise NotImplementedError(f'{kind} tranforms not implemented (yet)')
|
||||
new.dparameters = 6 * [np.nan]
|
||||
return new
|
||||
|
||||
@classmethod
|
||||
def from_shift(cls, shift):
|
||||
return cls.from_array(np.array(((1, 0, shift[0]), (0, 1, shift[1]), (0, 0, 1))))
|
||||
|
||||
@classmethod
|
||||
def from_array(cls, array):
|
||||
new = cls()
|
||||
new.matrix = array
|
||||
return new
|
||||
|
||||
@classmethod
|
||||
def from_file(cls, file):
|
||||
with open(Path(file).with_suffix('.yml')) as f:
|
||||
return cls.from_dict(yamlload(f))
|
||||
|
||||
@classmethod
|
||||
def from_dict(cls, d):
|
||||
new = cls()
|
||||
new.origin = [float(i) for i in d['CenterOfRotationPoint']]
|
||||
new.parameters = [float(i) for i in d['TransformParameters']]
|
||||
new.dparameters = [float(i) for i in d['dTransformParameters']] if 'dTransformParameters' in d else 6 * [np.nan]
|
||||
new.shape = [float(i) for i in d['Size']]
|
||||
return new
|
||||
|
||||
def __mul__(self, other): # TODO: take care of dmatrix
|
||||
result = self.copy()
|
||||
if isinstance(other, Transform):
|
||||
result.matrix = self.matrix @ other.matrix
|
||||
result.dmatrix = self.dmatrix @ other.matrix + self.matrix @ other.dmatrix
|
||||
else:
|
||||
result.matrix = self.matrix @ other
|
||||
result.dmatrix = self.dmatrix @ other
|
||||
return result
|
||||
|
||||
def is_unity(self):
|
||||
return self.parameters == [1, 0, 0, 1, 0, 0]
|
||||
|
||||
def copy(self):
|
||||
return deepcopy(self)
|
||||
|
||||
@staticmethod
|
||||
def cast_image(im):
|
||||
if not isinstance(im, sitk.Image):
|
||||
im = sitk.GetImageFromArray(np.asarray(im))
|
||||
return im
|
||||
|
||||
@staticmethod
|
||||
def cast_array(im):
|
||||
if isinstance(im, sitk.Image):
|
||||
im = sitk.GetArrayFromImage(im)
|
||||
return im
|
||||
|
||||
@property
|
||||
def matrix(self):
|
||||
return np.array(((*self.parameters[:2], self.parameters[4]),
|
||||
(*self.parameters[2:4], self.parameters[5]),
|
||||
(0, 0, 1)))
|
||||
|
||||
@matrix.setter
|
||||
def matrix(self, value):
|
||||
value = np.asarray(value)
|
||||
self.parameters = [*value[0, :2], *value[1, :2], *value[:2, 2]]
|
||||
|
||||
@property
|
||||
def dmatrix(self):
|
||||
return np.array(((*self.dparameters[:2], self.dparameters[4]),
|
||||
(*self.dparameters[2:4], self.dparameters[5]),
|
||||
(0, 0, 0)))
|
||||
|
||||
@dmatrix.setter
|
||||
def dmatrix(self, value):
|
||||
value = np.asarray(value)
|
||||
self.dparameters = [*value[0, :2], *value[1, :2], *value[:2, 2]]
|
||||
|
||||
@property
|
||||
def parameters(self):
|
||||
if self.transform is not None:
|
||||
return list(self.transform.GetParameters())
|
||||
|
||||
@parameters.setter
|
||||
def parameters(self, value):
|
||||
if self.transform is not None:
|
||||
value = np.asarray(value)
|
||||
self.transform.SetParameters(value.tolist())
|
||||
|
||||
@property
|
||||
def origin(self):
|
||||
if self.transform is not None:
|
||||
return self.transform.GetFixedParameters()
|
||||
|
||||
@origin.setter
|
||||
def origin(self, value):
|
||||
if self.transform is not None:
|
||||
value = np.asarray(value)
|
||||
self.transform.SetFixedParameters(value.tolist())
|
||||
|
||||
@property
|
||||
def inverse(self):
|
||||
if self.is_unity():
|
||||
return self
|
||||
if self._last is None or self._last != self.asdict():
|
||||
self._last = self.asdict()
|
||||
self._inverse = Transform.from_dict(self.asdict())
|
||||
self._inverse.transform = self._inverse.transform.GetInverse()
|
||||
self._inverse._last = self._inverse.asdict()
|
||||
self._inverse._inverse = self
|
||||
return self._inverse
|
||||
|
||||
def adapt(self, origin, shape):
|
||||
self.origin -= np.array(origin) + (self.shape - np.array(shape)[:2]) / 2
|
||||
self.shape = shape[:2]
|
||||
|
||||
def asdict(self):
|
||||
return {'CenterOfRotationPoint': self.origin, 'Size': self.shape, 'TransformParameters': self.parameters,
|
||||
'dTransformParameters': np.nan_to_num(self.dparameters, nan=1e99).tolist()}
|
||||
|
||||
def frame(self, im, default=0):
|
||||
if self.is_unity():
|
||||
return im
|
||||
else:
|
||||
if sitk is None:
|
||||
raise ImportError('SimpleElastix is not installed: '
|
||||
'https://simpleelastix.readthedocs.io/GettingStarted.html')
|
||||
dtype = im.dtype
|
||||
im = im.astype('float')
|
||||
intp = sitk.sitkBSpline if np.issubdtype(dtype, np.floating) else sitk.sitkNearestNeighbor
|
||||
return self.cast_array(sitk.Resample(self.cast_image(im), self.transform, intp, default)).astype(dtype)
|
||||
|
||||
def coords(self, array, columns=None):
|
||||
""" Transform coordinates in 2 column numpy array,
|
||||
or in pandas DataFrame or Series objects in columns ['x', 'y']
|
||||
"""
|
||||
if self.is_unity():
|
||||
return array.copy()
|
||||
elif DataFrame is not None and isinstance(array, (DataFrame, Series)):
|
||||
columns = columns or ['x', 'y']
|
||||
array = array.copy()
|
||||
if isinstance(array, DataFrame):
|
||||
array[columns] = self.coords(np.atleast_2d(array[columns].to_numpy()))
|
||||
elif isinstance(array, Series):
|
||||
array[columns] = self.coords(np.atleast_2d(array[columns].to_numpy()))[0]
|
||||
return array
|
||||
else: # somehow we need to use the inverse here to get the same effect as when using self.frame
|
||||
return np.array([self.inverse.transform.TransformPoint(i.tolist()) for i in np.asarray(array)])
|
||||
|
||||
def save(self, file):
|
||||
""" save the parameters of the transform calculated
|
||||
with affine_registration to a yaml file
|
||||
"""
|
||||
if not file[-3:] == 'yml':
|
||||
file += '.yml'
|
||||
with open(file, 'w') as f:
|
||||
yaml.safe_dump(self.asdict(), f, default_flow_style=None)
|
||||
@@ -1,54 +1,15 @@
|
||||
[tool.poetry]
|
||||
name = "ndbioimage"
|
||||
version = "2025.1.2"
|
||||
description = "Bio image reading, metadata and some affine registration."
|
||||
authors = ["W. Pomp <w.pomp@nki.nl>"]
|
||||
license = "GPLv3"
|
||||
readme = "README.md"
|
||||
keywords = ["bioformats", "imread", "numpy", "metadata"]
|
||||
include = ["transform.txt"]
|
||||
repository = "https://github.com/wimpomp/ndbioimage"
|
||||
exclude = ["ndbioimage/jars"]
|
||||
|
||||
[tool.poetry.dependencies]
|
||||
python = "^3.10"
|
||||
numpy = ">=1.20.0"
|
||||
pandas = "*"
|
||||
tifffile = "*"
|
||||
czifile = "2019.7.2"
|
||||
tiffwrite = ">=2024.12.1"
|
||||
ome-types = ">=0.4.0"
|
||||
pint = "*"
|
||||
tqdm = "*"
|
||||
lxml = "*"
|
||||
pyyaml = "*"
|
||||
parfor = ">=2025.1.0"
|
||||
JPype1 = "*"
|
||||
SimpleITK-SimpleElastix = [
|
||||
{ version = "*", python = "<3.12" },
|
||||
{ version = "*", python = ">=3.12", markers = "sys_platform != 'darwin'" },
|
||||
{ version = "*", python = ">=3.12", markers = "platform_machine == 'aarch64'" },
|
||||
]
|
||||
scikit-image = "*"
|
||||
imagecodecs = "*"
|
||||
xsdata = "^23" # until pydantic is up-to-date
|
||||
matplotlib = { version = "*", optional = true }
|
||||
scikit-video = { version = "*", optional = true }
|
||||
pytest = { version = "*", optional = true }
|
||||
|
||||
[tool.poetry.extras]
|
||||
test = ["pytest"]
|
||||
write = ["matplotlib", "scikit-video"]
|
||||
|
||||
[tool.poetry.scripts]
|
||||
ndbioimage = "ndbioimage:main"
|
||||
|
||||
[tool.pytest.ini_options]
|
||||
filterwarnings = ["ignore:::(colorcet)"]
|
||||
|
||||
[tool.isort]
|
||||
line_length = 119
|
||||
|
||||
[build-system]
|
||||
requires = ["poetry-core"]
|
||||
build-backend = "poetry.core.masonry.api"
|
||||
requires = ["maturin>=1.8,<2.0"]
|
||||
build-backend = "maturin"
|
||||
|
||||
[project]
|
||||
name = "ndbioimage_rs"
|
||||
requires-python = ">=3.8"
|
||||
classifiers = [
|
||||
"Programming Language :: Rust",
|
||||
"Programming Language :: Python :: Implementation :: CPython",
|
||||
"Programming Language :: Python :: Implementation :: PyPy",
|
||||
]
|
||||
dynamic = ["version"]
|
||||
[tool.maturin]
|
||||
features = ["pyo3/extension-module"]
|
||||
|
||||
142
src/bioformats.rs
Normal file
142
src/bioformats.rs
Normal file
@@ -0,0 +1,142 @@
|
||||
use anyhow::Result;
|
||||
use j4rs::{Instance, InvocationArg, Jvm, JvmBuilder};
|
||||
use std::cell::OnceCell;
|
||||
use std::rc::Rc;
|
||||
|
||||
thread_local! {
|
||||
static JVM: OnceCell<Rc<Jvm>> = const { OnceCell::new() }
|
||||
}
|
||||
|
||||
/// Ensure 1 jvm per thread
|
||||
fn jvm() -> Rc<Jvm> {
|
||||
JVM.with(|cell| {
|
||||
cell.get_or_init(move || Rc::new(JvmBuilder::new().build().expect("Failed to build JVM")))
|
||||
.clone()
|
||||
})
|
||||
}
|
||||
|
||||
macro_rules! method_return {
|
||||
($R:ty$(|c)?) => { Result<$R> };
|
||||
() => { Result<()> };
|
||||
}
|
||||
|
||||
macro_rules! method_arg {
|
||||
($n:tt: $t:ty|p) => {
|
||||
InvocationArg::try_from($n)?.into_primitive()?
|
||||
};
|
||||
($n:tt: $t:ty) => {
|
||||
InvocationArg::try_from($n)?
|
||||
};
|
||||
}
|
||||
|
||||
macro_rules! method {
|
||||
($name:ident, $method:expr $(,[$($n:tt: $t:ty$(|$p:tt)?),*])? $(=> $tt:ty$(|$c:tt)?)?) => {
|
||||
pub fn $name(&self, $($($n: $t),*)?) -> method_return!($($tt)?) {
|
||||
let args: Vec<InvocationArg> = vec![$($( method_arg!($n:$t$(|$p)?) ),*)?];
|
||||
let _result = jvm().invoke(&self.0, $method, &args)?;
|
||||
|
||||
macro_rules! method_result {
|
||||
($R:ty|c) => {
|
||||
Ok(jvm().to_rust(_result)?)
|
||||
};
|
||||
($R:ty|d) => {
|
||||
Ok(jvm().to_rust_deserialized(_result)?)
|
||||
};
|
||||
($R:ty) => {
|
||||
Ok(_result)
|
||||
};
|
||||
() => {
|
||||
Ok(())
|
||||
};
|
||||
}
|
||||
|
||||
method_result!($($tt$(|$c)?)?)
|
||||
}
|
||||
};
|
||||
}
|
||||
|
||||
pub struct DebugTools;
|
||||
|
||||
impl DebugTools {
|
||||
pub fn set_root_level(level: &str) -> Result<()> {
|
||||
jvm().invoke_static(
|
||||
"loci.common.DebugTools",
|
||||
"setRootLevel",
|
||||
&[InvocationArg::try_from(level)?],
|
||||
)?;
|
||||
Ok(())
|
||||
}
|
||||
}
|
||||
|
||||
pub struct ChannelSeparator(Instance);
|
||||
|
||||
impl ChannelSeparator {
|
||||
pub fn new(image_reader: &ImageReader) -> Result<Self> {
|
||||
let jvm = jvm();
|
||||
let channel_separator = jvm.create_instance(
|
||||
"loci.formats.ChannelSeparator",
|
||||
&[InvocationArg::from(jvm.clone_instance(&image_reader.0)?)],
|
||||
)?;
|
||||
Ok(ChannelSeparator(channel_separator))
|
||||
}
|
||||
|
||||
pub fn open_bytes(&self, index: i32) -> Result<Vec<u8>> {
|
||||
let bi8 = self.open_bi8(index)?;
|
||||
Ok(unsafe { std::mem::transmute::<Vec<i8>, Vec<u8>>(bi8) })
|
||||
}
|
||||
|
||||
method!(open_bi8, "openBytes", [index: i32|p] => Vec<i8>|c);
|
||||
method!(get_index, "getIndex", [z: i32|p, c: i32|p, t: i32|p] => i32|c);
|
||||
}
|
||||
|
||||
pub struct ImageReader(Instance);
|
||||
|
||||
impl Drop for ImageReader {
|
||||
fn drop(&mut self) {
|
||||
self.close().unwrap()
|
||||
}
|
||||
}
|
||||
|
||||
impl ImageReader {
|
||||
pub fn new() -> Result<Self> {
|
||||
let reader = jvm().create_instance("loci.formats.ImageReader", InvocationArg::empty())?;
|
||||
Ok(ImageReader(reader))
|
||||
}
|
||||
|
||||
pub fn open_bytes(&self, index: i32) -> Result<Vec<u8>> {
|
||||
let bi8 = self.open_bi8(index)?;
|
||||
Ok(unsafe { std::mem::transmute::<Vec<i8>, Vec<u8>>(bi8) })
|
||||
}
|
||||
|
||||
method!(set_metadata_store, "setMetadataStore", [ome_data: Instance]);
|
||||
method!(set_id, "setId", [id: &str]);
|
||||
method!(set_series, "setSeries", [series: i32|p]);
|
||||
method!(open_bi8, "openBytes", [index: i32|p] => Vec<i8>|c);
|
||||
method!(get_size_x, "getSizeX" => i32|c);
|
||||
method!(get_size_y, "getSizeY" => i32|c);
|
||||
method!(get_size_c, "getSizeC" => i32|c);
|
||||
method!(get_size_t, "getSizeT" => i32|c);
|
||||
method!(get_size_z, "getSizeZ" => i32|c);
|
||||
method!(get_pixel_type, "getPixelType" => i32|c);
|
||||
method!(is_little_endian, "isLittleEndian" => bool|c);
|
||||
method!(is_rgb, "isRGB" => bool|c);
|
||||
method!(is_interleaved, "isInterleaved" => bool|c);
|
||||
method!(get_index, "getIndex", [z: i32|p, c: i32|p, t: i32|p] => i32|c);
|
||||
method!(get_rgb_channel_count, "getRGBChannelCount" => i32|c);
|
||||
method!(is_indexed, "isIndexed" => bool|c);
|
||||
method!(get_8bit_lookup_table, "get8BitLookupTable" => Instance);
|
||||
method!(get_16bit_lookup_table, "get16BitLookupTable" => Instance);
|
||||
method!(close, "close");
|
||||
}
|
||||
|
||||
pub struct MetadataTools(Instance);
|
||||
|
||||
impl MetadataTools {
|
||||
pub fn new() -> Result<Self> {
|
||||
let meta_data_tools =
|
||||
jvm().create_instance("loci.formats.MetadataTools", InvocationArg::empty())?;
|
||||
Ok(MetadataTools(meta_data_tools))
|
||||
}
|
||||
|
||||
method!(create_ome_xml_metadata, "createOMEXMLMetadata" => Instance);
|
||||
}
|
||||
366
src/lib.rs
Normal file
366
src/lib.rs
Normal file
@@ -0,0 +1,366 @@
|
||||
mod bioformats;
|
||||
|
||||
#[cfg(feature = "python")]
|
||||
mod py;
|
||||
|
||||
use anyhow::{anyhow, Result};
|
||||
use bioformats::{DebugTools, ImageReader, MetadataTools};
|
||||
use ndarray::Array2;
|
||||
use num::{FromPrimitive, Zero};
|
||||
use std::any::type_name;
|
||||
use std::fmt::Debug;
|
||||
use std::path::{Path, PathBuf};
|
||||
|
||||
/// Pixel types (u)int(8/16/32) or float(32/64)
|
||||
#[derive(Clone, Debug)]
|
||||
pub enum PixelType {
|
||||
INT8 = 0,
|
||||
UINT8 = 1,
|
||||
INT16 = 2,
|
||||
UINT16 = 3,
|
||||
INT32 = 4,
|
||||
UINT32 = 5,
|
||||
FLOAT = 6,
|
||||
DOUBLE = 7,
|
||||
}
|
||||
|
||||
impl TryFrom<i32> for PixelType {
|
||||
type Error = anyhow::Error;
|
||||
|
||||
fn try_from(value: i32) -> Result<Self, Self::Error> {
|
||||
match value {
|
||||
0 => Ok(PixelType::INT8),
|
||||
1 => Ok(PixelType::UINT8),
|
||||
2 => Ok(PixelType::INT16),
|
||||
3 => Ok(PixelType::UINT16),
|
||||
4 => Ok(PixelType::INT32),
|
||||
5 => Ok(PixelType::UINT32),
|
||||
6 => Ok(PixelType::FLOAT),
|
||||
7 => Ok(PixelType::DOUBLE),
|
||||
_ => Err(anyhow::anyhow!("Unknown pixel type {}", value)),
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
/// Struct containing frame data in one of eight pixel types. Cast to Array2<T> using try_into.
|
||||
#[derive(Clone, Debug)]
|
||||
pub enum Frame {
|
||||
INT8(Array2<i8>),
|
||||
UINT8(Array2<u8>),
|
||||
INT16(Array2<i16>),
|
||||
UINT16(Array2<u16>),
|
||||
INT32(Array2<i32>),
|
||||
UINT32(Array2<u32>),
|
||||
FLOAT(Array2<f32>),
|
||||
DOUBLE(Array2<f64>),
|
||||
}
|
||||
|
||||
macro_rules! impl_frame_cast {
|
||||
($t:tt, $s:ident) => {
|
||||
impl From<Array2<$t>> for Frame {
|
||||
fn from(value: Array2<$t>) -> Self {
|
||||
Frame::$s(value)
|
||||
}
|
||||
}
|
||||
};
|
||||
}
|
||||
|
||||
impl_frame_cast!(i8, INT8);
|
||||
impl_frame_cast!(u8, UINT8);
|
||||
impl_frame_cast!(i16, INT16);
|
||||
impl_frame_cast!(u16, UINT16);
|
||||
impl_frame_cast!(i32, INT32);
|
||||
impl_frame_cast!(u32, UINT32);
|
||||
impl_frame_cast!(f32, FLOAT);
|
||||
impl_frame_cast!(f64, DOUBLE);
|
||||
|
||||
impl<T> TryInto<Array2<T>> for Frame
|
||||
where
|
||||
T: FromPrimitive + Zero + 'static,
|
||||
{
|
||||
type Error = anyhow::Error;
|
||||
|
||||
fn try_into(self) -> std::result::Result<Array2<T>, Self::Error> {
|
||||
let mut err = Ok(());
|
||||
let arr = match self {
|
||||
Frame::INT8(v) => v.mapv_into_any(|x| {
|
||||
T::from_i8(x).unwrap_or_else(|| {
|
||||
err = Err(anyhow!("cannot convert {} into {}", x, type_name::<T>()));
|
||||
T::zero()
|
||||
})
|
||||
}),
|
||||
Frame::UINT8(v) => v.mapv_into_any(|x| {
|
||||
T::from_u8(x).unwrap_or_else(|| {
|
||||
err = Err(anyhow!("cannot convert {} into {}", x, type_name::<T>()));
|
||||
T::zero()
|
||||
})
|
||||
}),
|
||||
Frame::INT16(v) => v.mapv_into_any(|x| {
|
||||
T::from_i16(x).unwrap_or_else(|| {
|
||||
err = Err(anyhow!("cannot convert {} into {}", x, type_name::<T>()));
|
||||
T::zero()
|
||||
})
|
||||
}),
|
||||
Frame::UINT16(v) => v.mapv_into_any(|x| {
|
||||
T::from_u16(x).unwrap_or_else(|| {
|
||||
err = Err(anyhow!("cannot convert {} into {}", x, type_name::<T>()));
|
||||
T::zero()
|
||||
})
|
||||
}),
|
||||
Frame::INT32(v) => v.mapv_into_any(|x| {
|
||||
T::from_i32(x).unwrap_or_else(|| {
|
||||
err = Err(anyhow!("cannot convert {} into {}", x, type_name::<T>()));
|
||||
T::zero()
|
||||
})
|
||||
}),
|
||||
Frame::UINT32(v) => v.mapv_into_any(|x| {
|
||||
T::from_u32(x).unwrap_or_else(|| {
|
||||
err = Err(anyhow!("cannot convert {} into {}", x, type_name::<T>()));
|
||||
T::zero()
|
||||
})
|
||||
}),
|
||||
Frame::FLOAT(v) => v.mapv_into_any(|x| {
|
||||
T::from_f32(x).unwrap_or_else(|| {
|
||||
err = Err(anyhow!("cannot convert {} into {}", x, type_name::<T>()));
|
||||
T::zero()
|
||||
})
|
||||
}),
|
||||
Frame::DOUBLE(v) => v.mapv_into_any(|x| {
|
||||
T::from_f64(x).unwrap_or_else(|| {
|
||||
err = Err(anyhow!("cannot convert {} into {}", x, type_name::<T>()));
|
||||
T::zero()
|
||||
})
|
||||
}),
|
||||
};
|
||||
match err {
|
||||
Err(err) => Err(err),
|
||||
Ok(()) => Ok(arr),
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
/// Reader interface to file. Use get_frame to get data.
|
||||
pub struct Reader {
|
||||
image_reader: ImageReader,
|
||||
/// path to file
|
||||
pub path: PathBuf,
|
||||
/// which (if more) than 1 of the series in the file to open
|
||||
pub series: i32,
|
||||
/// size x (horizontal)
|
||||
pub size_x: usize,
|
||||
/// size y (vertical)
|
||||
pub size_y: usize,
|
||||
/// size c (# channels)
|
||||
pub size_c: usize,
|
||||
/// size z (# slices)
|
||||
pub size_z: usize,
|
||||
/// size t (time/frames)
|
||||
pub size_t: usize,
|
||||
/// pixel type ((u)int(8/16/32) or float(32/64))
|
||||
pub pixel_type: PixelType,
|
||||
little_endian: bool,
|
||||
}
|
||||
|
||||
impl Clone for Reader {
|
||||
fn clone(&self) -> Self {
|
||||
Reader::new(&self.path, self.series).unwrap()
|
||||
}
|
||||
}
|
||||
|
||||
impl Debug for Reader {
|
||||
fn fmt(&self, f: &mut std::fmt::Formatter<'_>) -> std::fmt::Result {
|
||||
f.debug_struct("Reader")
|
||||
.field("path", &self.path)
|
||||
.field("series", &self.series)
|
||||
.field("size_x", &self.size_x)
|
||||
.field("size_y", &self.size_y)
|
||||
.field("size_c", &self.size_c)
|
||||
.field("size_z", &self.size_z)
|
||||
.field("size_t", &self.size_t)
|
||||
.field("pixel_type", &self.pixel_type)
|
||||
.field("little_endian", &self.little_endian)
|
||||
.finish()
|
||||
}
|
||||
}
|
||||
|
||||
impl Reader {
|
||||
/// Create new reader for image file at path.
|
||||
pub fn new(path: &Path, series: i32) -> Result<Self> {
|
||||
DebugTools::set_root_level("ERROR")?;
|
||||
let reader = ImageReader::new()?;
|
||||
let meta_data_tools = MetadataTools::new()?;
|
||||
let ome_meta = meta_data_tools.create_ome_xml_metadata()?;
|
||||
reader.set_metadata_store(ome_meta)?;
|
||||
reader.set_id(path.to_str().unwrap())?;
|
||||
reader.set_series(series)?;
|
||||
let size_x = reader.get_size_x()?;
|
||||
let size_y = reader.get_size_y()?;
|
||||
let size_c = reader.get_size_c()?;
|
||||
let size_z = reader.get_size_z()?;
|
||||
let size_t = reader.get_size_t()?;
|
||||
let pixel_type = PixelType::try_from(reader.get_pixel_type()?)?;
|
||||
let little_endian = reader.is_little_endian()?;
|
||||
Ok(Reader {
|
||||
image_reader: reader,
|
||||
path: PathBuf::from(path),
|
||||
series,
|
||||
size_x: size_x as usize,
|
||||
size_y: size_y as usize,
|
||||
size_c: size_c as usize,
|
||||
size_z: size_z as usize,
|
||||
size_t: size_t as usize,
|
||||
pixel_type,
|
||||
little_endian,
|
||||
})
|
||||
}
|
||||
|
||||
fn deinterleave(&self, bytes: Vec<u8>, channel: usize) -> Result<Vec<u8>> {
|
||||
let chunk_size = match self.pixel_type {
|
||||
PixelType::INT8 => 1,
|
||||
PixelType::UINT8 => 1,
|
||||
PixelType::INT16 => 2,
|
||||
PixelType::UINT16 => 2,
|
||||
PixelType::INT32 => 4,
|
||||
PixelType::UINT32 => 4,
|
||||
PixelType::FLOAT => 4,
|
||||
PixelType::DOUBLE => 8,
|
||||
};
|
||||
Ok(bytes
|
||||
.chunks(chunk_size)
|
||||
.skip(channel)
|
||||
.step_by(self.size_c)
|
||||
.flat_map(|a| a.to_vec())
|
||||
.collect())
|
||||
}
|
||||
|
||||
/// Retrieve fame at channel c, slize z and time t.
|
||||
pub fn get_frame(&self, c: usize, z: usize, t: usize) -> Result<Frame> {
|
||||
let bytes = if self.image_reader.is_rgb()? & self.image_reader.is_interleaved()? {
|
||||
let index = self.image_reader.get_index(z as i32, 0, t as i32)?;
|
||||
self.deinterleave(self.image_reader.open_bytes(index)?, c)?
|
||||
} else if self.image_reader.get_rgb_channel_count()? > 1 {
|
||||
let channel_separator = bioformats::ChannelSeparator::new(&self.image_reader)?;
|
||||
let index = channel_separator.get_index(z as i32, c as i32, t as i32)?;
|
||||
channel_separator.open_bytes(index)?
|
||||
} else if self.image_reader.is_indexed()? {
|
||||
let index = self.image_reader.get_index(z as i32, 0, t as i32)?;
|
||||
self.image_reader.open_bytes(index)?
|
||||
// TODO: apply LUT
|
||||
// let _bytes_lut = match self.pixel_type {
|
||||
// PixelType::INT8 | PixelType::UINT8 => {
|
||||
// let _lut = self.image_reader.get_8bit_lookup_table()?;
|
||||
// }
|
||||
// PixelType::INT16 | PixelType::UINT16 => {
|
||||
// let _lut = self.image_reader.get_16bit_lookup_table()?;
|
||||
// }
|
||||
// _ => {}
|
||||
// };
|
||||
} else {
|
||||
let index = self.image_reader.get_index(z as i32, c as i32, t as i32)?;
|
||||
self.image_reader.open_bytes(index)?
|
||||
};
|
||||
self.bytes_to_frame(bytes)
|
||||
}
|
||||
|
||||
fn bytes_to_frame(&self, bytes: Vec<u8>) -> Result<Frame> {
|
||||
macro_rules! get_frame {
|
||||
($t:tt, <$n:expr) => {
|
||||
Ok(Frame::from(Array2::from_shape_vec(
|
||||
(self.size_y, self.size_x),
|
||||
bytes
|
||||
.chunks($n)
|
||||
.map(|x| $t::from_le_bytes(x.try_into().unwrap()))
|
||||
.collect(),
|
||||
)?))
|
||||
};
|
||||
($t:tt, >$n:expr) => {
|
||||
Ok(Frame::from(Array2::from_shape_vec(
|
||||
(self.size_y, self.size_x),
|
||||
bytes
|
||||
.chunks($n)
|
||||
.map(|x| $t::from_be_bytes(x.try_into().unwrap()))
|
||||
.collect(),
|
||||
)?))
|
||||
};
|
||||
}
|
||||
|
||||
match (&self.pixel_type, self.little_endian) {
|
||||
(PixelType::INT8, true) => get_frame!(i8, <1),
|
||||
(PixelType::UINT8, true) => get_frame!(u8, <1),
|
||||
(PixelType::INT16, true) => get_frame!(i16, <2),
|
||||
(PixelType::UINT16, true) => get_frame!(u16, <2),
|
||||
(PixelType::INT32, true) => get_frame!(i32, <4),
|
||||
(PixelType::UINT32, true) => get_frame!(u32, <4),
|
||||
(PixelType::FLOAT, true) => get_frame!(f32, <4),
|
||||
(PixelType::DOUBLE, true) => get_frame!(f64, <8),
|
||||
(PixelType::INT8, false) => get_frame!(i8, >1),
|
||||
(PixelType::UINT8, false) => get_frame!(u8, >1),
|
||||
(PixelType::INT16, false) => get_frame!(i16, >2),
|
||||
(PixelType::UINT16, false) => get_frame!(u16, >2),
|
||||
(PixelType::INT32, false) => get_frame!(i32, >4),
|
||||
(PixelType::UINT32, false) => get_frame!(u32, >4),
|
||||
(PixelType::FLOAT, false) => get_frame!(f32, >4),
|
||||
(PixelType::DOUBLE, false) => get_frame!(f64, >8),
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
#[cfg(test)]
|
||||
mod tests {
|
||||
use super::*;
|
||||
use rayon::prelude::*;
|
||||
|
||||
fn open(file: &str) -> Result<Reader> {
|
||||
let path = std::env::current_dir()?.join("tests").join("files").join(file);
|
||||
Reader::new(&path, 0)
|
||||
}
|
||||
|
||||
fn get_pixel_type(file: &str) -> Result<String> {
|
||||
let reader = open(file)?;
|
||||
Ok(format!(
|
||||
"file: {}, pixel type: {:?}",
|
||||
file, reader.pixel_type
|
||||
))
|
||||
}
|
||||
|
||||
fn get_frame(file: &str) -> Result<Frame> {
|
||||
let reader = open(file)?;
|
||||
reader.get_frame(0, 0, 0)
|
||||
}
|
||||
|
||||
#[test]
|
||||
fn read_ser() -> Result<()> {
|
||||
let file = "Experiment-2029.czi";
|
||||
let reader = open(file)?;
|
||||
println!("size: {}, {}", reader.size_y, reader.size_y);
|
||||
let frame = reader.get_frame(0, 0, 0)?;
|
||||
if let Ok(arr) = <Frame as TryInto<Array2<i8>>>::try_into(frame) {
|
||||
println!("{:?}", arr);
|
||||
} else {
|
||||
println!("could not convert Frame to Array<i8>");
|
||||
}
|
||||
Ok(())
|
||||
}
|
||||
|
||||
#[test]
|
||||
fn read_par() -> Result<()> {
|
||||
let files = vec!["Experiment-2029.czi", "test.tif"];
|
||||
let pixel_type = files
|
||||
.into_par_iter()
|
||||
.map(|file| get_pixel_type(file).unwrap())
|
||||
.collect::<Vec<_>>();
|
||||
println!("{:?}", pixel_type);
|
||||
Ok(())
|
||||
}
|
||||
|
||||
#[test]
|
||||
fn read_frame_par() -> Result<()> {
|
||||
let files = vec!["Experiment-2029.czi", "test.tif"];
|
||||
let frames = files
|
||||
.into_par_iter()
|
||||
.map(|file| get_frame(file).unwrap())
|
||||
.collect::<Vec<_>>();
|
||||
println!("{:?}", frames);
|
||||
Ok(())
|
||||
}
|
||||
}
|
||||
14
src/py.rs
Normal file
14
src/py.rs
Normal file
@@ -0,0 +1,14 @@
|
||||
use pyo3::prelude::*;
|
||||
|
||||
/// Formats the sum of two numbers as string.
|
||||
#[pyfunction]
|
||||
fn sum_as_string(a: usize, b: usize) -> PyResult<String> {
|
||||
Ok((a + b).to_string())
|
||||
}
|
||||
|
||||
/// A Python module implemented in Rust.
|
||||
#[pymodule]
|
||||
fn ndbioimage_rs(m: &Bound<'_, PyModule>) -> PyResult<()> {
|
||||
m.add_function(wrap_pyfunction!(sum_as_string, m)?)?;
|
||||
Ok(())
|
||||
}
|
||||
Reference in New Issue
Block a user