Pydantic Rework #47

multimeric · 2023-09-11T08:24:37Z

Pydantic

Rework the core of the application to use object oriented Pydantic dataclasses. This gives us reusable validation and encapsulation (closes https://github.com/orgs/BioimageAnalysisCoreWEHI/projects/2?pane=issue&itemId=30632792)
Subgroups of parameters such as deconvolution live in separate models (closes Refactor the deconvolution parameters into a separate class #31)
Default values now entirely live in the Pydantic models (closes Move the LatticeData defaults from the CLI #32)

CLI

Moved from argparse to typer for the CLI
YAML, JSON and CLI args are now merged (closes https://github.com/orgs/BioimageAnalysisCoreWEHI/projects/2/views/1?pane=issue&itemId=30632622)

GUI

Rework the GUI to offer the user a sequence of tabs they can sequentially configure
Consolidated some repeated GUI elements like the preview button, time range, channel range etc to simplify the codebase

Other

Migrate to XArray, which gives us labelled axis (closes Using xarray instead of dask array #41)
Created a large number of parameterised tests that capture most combinations of workflow, cropping, deconvolution features, for the Python API, CLI and GUI

Future Work

Make save_dir a mandatory parameter, so that the user has to consider the output location. This will involve making the output model optional, and also moving channel_range and time_range into the DeskewParams. This was deprioritised due to the large impact this change would have

…e into thin-wrapper

…attice into thin-wrapper

model generation

errors red

pr4deepr · 2023-09-14T02:58:06Z

I'm trying the plugin and I get this error when I try to start the plugin in napari:


---------------------------------------------------------------------------
ModuleNotFoundError                       Traceback (most recent call last)
File ~\Documents\Miniconda3\envs\napari_lattice_test\lib\site-packages\npe2\_command_registry.py:32, in CommandHandler.resolve(self=CommandHandler(id='napari-lattice.dock_widget', ...tice.dock_widget:_napari_lattice_widget_wrapper'))
     31 try:
---> 32     self.function = utils.import_python_name(self.python_name)
        self.function = None
        self.python_name = 'napari_lattice.dock_widget:_napari_lattice_widget_wrapper'
        self = CommandHandler(id='napari-lattice.dock_widget', function=None, python_name='napari_lattice.dock_widget:_napari_lattice_widget_wrapper')
        utils = <module 'npe2.manifest.utils' from 'C:\\Users\\rajasekhar.p\\Documents\\Miniconda3\\envs\\napari_lattice_test\\lib\\site-packages\\npe2\\manifest\\utils.py'>
     33 except Exception as e:

File ~\Documents\Miniconda3\envs\napari_lattice_test\lib\site-packages\npe2\manifest\utils.py:256, in import_python_name(python_name='napari_lattice.dock_widget:_napari_lattice_widget_wrapper')
    254 module_name, funcname = match.groups()  # type: ignore [union-attr]
--> 256 mod = import_module(module_name)
        module_name = 'napari_lattice.dock_widget'
    257 return getattr(mod, funcname)

File ~\Documents\Miniconda3\envs\napari_lattice_test\lib\importlib\__init__.py:126, in import_module(name='napari_lattice.dock_widget', package=None)
    125         level += 1
--> 126 return _bootstrap._gcd_import(name[level:], package, level)
        level = 0
        name = 'napari_lattice.dock_widget'
        name[level:] = 'napari_lattice.dock_widget'
        package = None
        _bootstrap = <module '_frozen_importlib' (frozen)>

File <frozen importlib._bootstrap>:1050, in _gcd_import(name='napari_lattice.dock_widget', package=None, level=0)

File <frozen importlib._bootstrap>:1027, in _find_and_load(name='napari_lattice.dock_widget', import_=<function _gcd_import>)

File <frozen importlib._bootstrap>:1006, in _find_and_load_unlocked(name='napari_lattice.dock_widget', import_=<function _gcd_import>)

File <frozen importlib._bootstrap>:688, in _load_unlocked(spec=ModuleSpec(name='napari_lattice.dock_widget', lo...lattice\\plugin\\napari_lattice\\dock_widget.py'))

File <frozen importlib._bootstrap_external>:883, in exec_module(self=<_frozen_importlib_external.SourceFileLoader object>, module=<module 'napari_lattice.dock_widget' from 'C:\\U...lattice\\plugin\\napari_lattice\\dock_widget.py'>)

File <frozen importlib._bootstrap>:241, in _call_with_frames_removed(f=<built-in function exec>, *args=(<code object <module> at 0x0000022B21959D10, fil...ce\plugin\napari_lattice\dock_widget.py", line 1>, {'Path': <class 'pathlib.Path'>, 'Union': typing.Union, '__builtins__': {'ArithmeticError': <class 'ArithmeticError'>, 'AssertionError': <class 'AssertionError'>, 'AttributeError': <class 'AttributeError'>, 'BaseException': <class 'BaseException'>, 'BlockingIOError': <class 'BlockingIOError'>, 'BrokenPipeError': <class 'BrokenPipeError'>, 'BufferError': <class 'BufferError'>, 'BytesWarning': <class 'BytesWarning'>, 'ChildProcessError': <class 'ChildProcessError'>, 'ConnectionAbortedError': <class 'ConnectionAbortedError'>, ...}, '__cached__': r'C:\Users\rajasekhar.p\test\napari_lattice\plugin...i_lattice\__pycache__\dock_widget.cpython-310.pyc', '__doc__': None, '__file__': r'C:\Users\rajasekhar.p\test\napari_lattice\plugin\napari_lattice\dock_widget.py', '__loader__': <_frozen_importlib_external.SourceFileLoader object>, '__name__': 'napari_lattice.dock_widget', '__package__': 'napari_lattice', '__spec__': ModuleSpec(name='napari_lattice.dock_widget', lo...lattice\\plugin\\napari_lattice\\dock_widget.py'), ...}), **kwds={})

File ~\test\napari_lattice\plugin\napari_lattice\dock_widget.py:7
      6 import numpy as np
----> 7 from lls_core.lattice_data import LatticeData
      8 from lls_core.workflow import import_workflow_modules

File ~\test\napari_lattice\core\lls_core\__init__.py:4
      2 __version__ = "0.2.6"
----> 4 from strenum import StrEnum
      5 from enum import Enum

ModuleNotFoundError: No module named 'strenum'

The above exception was the direct cause of the following exception:.....................
.
.
RuntimeError: Failed to import command at 'napari_lattice.dock_widget:_napari_lattice_widget_wrapper': No module named 'strenum'

pr4deepr · 2024-08-14T04:22:42Z

GUI:
Workflow tab: Crop and workflow is not working. It returns a deskewed image without workflow being applied to it.
pycudadecon: After installation, I was getting conflicts with numpy (upgraded to 2.0). May need to pin this version to the previous release.
- rename pyproject.toml key from psf to deconvolution

pr4deepr · 2024-08-14T06:56:28Z

deconvolution update:
With pycudadecon, I tried 0.4.0 on Windows, using pip install but was getting an error relating to needing cudadecon as pycudadecon is a python wrapper around it.
Developer recommends conda install as it has precompiled windows and linux binaries, and it works for me too.

But, now I get a different error:

│ C:\Users\Public\Miniconda3\envs\napari_lattice\lib\site-packages\lls_core\deconvolution.py:158   │
│ in pycuda_decon                                                                                  │
│                                                                                                  │
│   155 │   │   psf = np.squeeze(psf)  # remove unit dimensions                                    │
│   156 │   │   assert psf.ndim == 3, f"PSF needs to be 3D. Got {psf.ndim}"                        │
│   157 │   │   # Temporary OTF generation; RLContext ensures memory cleanup (runs rl_init and r   │
│ ❱ 158 │   │   with TemporaryOTF(psf) as otf:                                                     │
│   159 │   │   │   with RLContext(                                                                │
│   160 │   │   │   │   rawdata_shape=image.shape,                                                 │
│   161 │   │   │   │   otfpath=otf.path,                                                          │
│                                                                                                  │
│ ╭─────────────────────────────────────────── locals ───────────────────────────────────────────╮ │
│ │     background = 0                                                                           │ │
│ │       cropping = True                                                                        │ │
│ │         dxdata = 0.14499219272808386                                                         │ │
│ │          dxpsf = 0.14499219272808386                                                         │ │
│ │         dzdata = 0.3                                                                         │ │
│ │          dzpsf = 0.3                                                                         │ │
│ │          image = array([[[ 99,  99,  95, ...,  99, 101,  97],                                │ │
│ │                  │   │   [ 99,  99,  95, ...,  93,  98,  93],                                │ │
│ │                  │   │   [ 99,  99,  97, ...,  99,  97,  94],                                │ │
│ │                  │   │   ...,                                                                │ │
│ │                  │   │   [100, 100,  99, ...,  98,  96,  95],                                │ │
│ │                  │   │   [ 99,  98,  99, ...,  98,  95,  97],                                │ │
│ │                  │   │   [ 97,  97,  96, ...,  96,  96,  96]],                               │ │
│ │                  │                                                                           │ │
│ │                  │      [[ 99,  97,  97, ...,  99,  99,  99],                                │ │
│ │                  │   │   [100,  99,  97, ...,  95, 100,  99],                                │ │
│ │                  │   │   [101,  99,  99, ...,  99,  95, 102],                                │ │
│ │                  │   │   ...,                                                                │ │
│ │                  │   │   [ 97,  97,  97, ...,  98,  97,  96],                                │ │
│ │                  │   │   [ 94,  97,  93, ...,  97,  93,  97],                                │ │
│ │                  │   │   [ 96,  96,  99, ...,  96,  97,  95]],                               │ │
│ │                  │                                                                           │ │
│ │                  │      [[ 99,  99,  98, ...,  99,  99,  97],                                │ │
│ │                  │   │   [ 98, 103,  98, ...,  93, 100,  97],                                │ │
│ │                  │   │   [ 98,  97,  99, ...,  92,  98,  98],                                │ │
│ │                  │   │   ...,                                                                │ │
│ │                  │   │   [ 93, 100,  95, ...,  98,  94,  96],                                │ │
│ │                  │   │   [100,  98, 101, ..., 103,  96,  95],                                │ │
│ │                  │   │   [103,  98,  96, ..., 100,  94,  95]],                               │ │
│ │                  │                                                                           │ │
│ │                  │      ...,                                                                 │ │
│ │                  │                                                                           │ │
│ │                  │      [[ 99, 104,  97, ...,  98,  99,  95],                                │ │
│ │                  │   │   [102, 100,  95, ...,  99,  99,  97],                                │ │
│ │                  │   │   [ 99,  99,  99, ..., 102, 101, 100],                                │ │
│ │                  │   │   ...,                                                                │ │
│ │                  │   │   [ 97,  98,  98, ...,  98,  96,  95],                                │ │
│ │                  │   │   [ 97,  96,  99, ...,  94,  95,  97],                                │ │
│ │                  │   │   [ 98,  95,  92, ...,  99,  93,  98]],                               │ │
│ │                  │                                                                           │ │
│ │                  │      [[ 99,  97,  97, ...,  98,  99,  97],                                │ │
│ │                  │   │   [ 99,  99,  99, ...,  98, 100,  98],                                │ │
│ │                  │   │   [ 99, 101,  95, ..., 100,  99,  98],                                │ │
│ │                  │   │   ...,                                                                │ │
│ │                  │   │   [100,  97,  93, ...,  97,  97,  97],                                │ │
│ │                  │   │   [ 96,  99,  95, ..., 100,  96,  94],                                │ │
│ │                  │   │   [104,  95,  96, ...,  99,  94,  94]],                               │ │
│ │                  │                                                                           │ │
│ │                  │      [[ 99,  99,  98, ...,  98,  99,  98],                                │ │
│ │                  │   │   [ 97,  98,  98, ...,  95,  97, 102],                                │ │
│ │                  │   │   [ 98,  99,  97, ..., 101,  98,  98],                                │ │
│ │                  │   │   ...,                                                                │ │
│ │                  │   │   [ 97,  97, 102, ..., 100,  98,  95],                                │ │
│ │                  │   │   [ 94,  94,  95, ...,  98,  98, 100],                                │ │
│ │                  │   │   [ 98, 100,  94, ...,  97,  94,  95]]], dtype=uint16)                │ │
│ │       num_iter = 10                                                                          │ │
│ │ orig_img_shape = (216, 300, 210)                                                             │ │
│ │       otf_path = None                                                                        │ │
│ │            psf = <xarray.DataArray 'transpose-145d955afd724ac26b38452f33885fcd' (Z: 36, Y:   │ │
│ │                  12,                                                                         │ │
│ │                  │   │   │   │   │   │   │   │   │   │   │   │   │   │   │   │   X: 12)>     │ │
│ │                  dask.array<getitem, shape=(36, 12, 12), dtype=float32, chunksize=(36, 12,   │ │
│ │                  12), chunktype=numpy.ndarray>                                               │ │
│ │                  Coordinates:                                                                │ │
│ │                  │   C        <U11 'Channel:0:0'                                             │ │
│ │                  Dimensions without coordinates: Z, Y, X                                     │ │
│ │                  Attributes:                                                                 │ │
│ │                  │   unprocessed:  {254: <FILETYPE.UNDEFINED: 0>, 256: 12, 257: 12, 258: 32, │ │
│ │                  2...                                                                        │ │
│ │                  │   processed:                                                              │ │
│ │                  ImageJ=1.53t\nimages=36\nslices=36\nunit=micron\nspacing=0....              │ │
│ │       rl_decon = <function rl_decon at 0x0000029CE2750670>                                   │ │
│ │      RLContext = <class 'pycudadecon.deconvolution.RLContext'>                               │ │
│ │   TemporaryOTF = <class 'pycudadecon.otf.TemporaryOTF'>                                      │ │
│ │      x_psf_pad = 6                                                                           │ │
│ │      y_psf_pad = 6                                                                           │ │
│ │      z_psf_pad = 18                                                                          │ │
│ ╰──────────────────────────────────────────────────────────────────────────────────────────────╯ │
│                                                                                                  │
│ C:\Users\Public\Miniconda3\envs\napari_lattice\lib\site-packages\pycudadecon\otf.py:269 in       │
│ __enter__                                                                                        │
│                                                                                                  │
│   266 │   │   │   elif isinstance(self.psf, str) and os.path.isfile(self.psf):                   │
│   267 │   │   │   │   make_otf(self.psf, self.tempotf.name, **self.kwargs)                       │
│   268 │   │   │   else:                                                                          │
│ ❱ 269 │   │   │   │   raise ValueError(f"Did not expect PSF file as {type(self.psf)}")           │
│   270 │   │   │   self.path = self.tempotf.name                                                  │
│   271 │   │   elif is_otf(self.psf) and os.path.isfile(self.psf):                                │
│   272 │   │   │   self.path = self.psf                                                           │
│                                                                                                  │
│ ╭────────────────────────────── locals ──────────────────────────────╮                           │
│ │ self = <pycudadecon.otf.TemporaryOTF object at 0x0000029CE1B7CC40> │                           │
│ ╰────────────────────────────────────────────────────────────────────╯                           │
╰──────────────────────────────────────────────────────────────────────────────────────────────────╯
ValueError: Did not expect PSF file as <class 'xarray.core.dataarray.DataArray'>

Looks like we need to convert psf files into numpy arrays..

multimeric · 2024-08-15T07:28:07Z

The workflow rework is now in 91c7ea9. I'll document it more thoroughly in the docs PR, but the gist is that we now enforce that the workflow has exactly one parameter called deskewed_image, which will be connected to the output of the deskewing step. Users can also utilise channel, channel_index, roi_index etc if they need the appropriate metadata. Finally, if the workflow has multiple "leaf" (output) tasks, it will be rejected at the validation stage.

Workflow tab: Crop and workflow is not working. It returns a deskewed image without workflow being applied to it.

I couldn't reproduce this, at least after my changes. Did you use the preview or save button?

multimeric · 2024-08-16T00:35:39Z

Looks like we need to convert psf files into numpy arrays..

This is hard to reproduce because I don't have access to anything cuda compatible myself. Were you running the crop workflow? Because I think I can identify a point where I neglected to convert back to numpy there.

pr4deepr · 2024-08-19T11:01:14Z

I'm running into environment configuration issues when I install pycudadecon, even with version 0.4.0. I believe it may be to do with numpy being upgraded to 2.0, and perhaps with napari being configured to 0.5.0. pycudadecon is being installed using conda instead of pip.

pr4deepr · 2024-08-19T20:36:02Z

I've figured out the error and I've posted it here: tlambert03/pycudadecon#64

To get around a few dependency errors , I've used following installation commands in python 3.10

pip install git+https://github.com/multimeric/napari_lattice.git@thin-wrapper#subdirectory=core

restrict napari to 0.4.*
pip install git+https://github.com/multimeric/napari_lattice.git@thin-wrapper#subdirectory=plugin napari==0.4.*

install napari-aiscimageio without updating dependencies (otherwise this caused a lot of issues with scikit-image and tifffile)
pip install napari-aicsimageio --no-deps

pycudadecon
ensure numpy<2, cudadecon is 0.6.*
mamba install -c conda-forge pycudadecon==0.4.* numpy==1.24.* cudadecon==0.6.*

tlambert03 · 2024-08-19T20:36:48Z

pycudadecon==0.4.*

or pycudadecon v0.5 from pip and you'll be fine. (but the numpy bit is up to you)

pr4deepr · 2024-08-19T20:49:47Z

I couldn't reproduce this, at least after my changes. Did you use the preview or save button?

When using Preview, I still get the deskewed image without processing

It works with save...

pr4deepr · 2024-08-21T02:27:22Z

pycudadecon
ensure numpy<2, cudadecon is 0.6.*
mamba install -c conda-forge pycudadecon==0.4.* numpy==1.24.* cudadecon==0.6.*

I can confirm that mamba install -c conda-forge pycudadecon numpy==1.24.* works now..

multimeric · 2024-08-21T06:15:14Z

So to clarify, I'm going to:

Pin numpy to < 2. Currently it's unpinned and working fine on the CI, but the CI isn't testing pycudadecon, so this must be related to our own code that uses pycudadecon
Pin napari < 0.5. This is probably happening automatically by virtue of our pydantic pin, but I'm happy to be explicit about this
Pin pycudadecon >= 0.5
Suggest that the user installs cudadecon >= 0.6 in conda (I can't control this using our pyproject.toml).

multimeric · 2024-08-21T06:27:24Z

When using Preview, I still get the deskewed image without processing

Right, this is a bit tricky. The workflow can produce multiple outputs, including multiple images or no images. Should I add the "first" image output by the workflow, or all of them maybe? The non-image stuff can get thrown away I assume.

pr4deepr · 2024-08-21T07:05:39Z

Pin numpy to < 2. Currently it's unpinned and working fine on the CI, but the CI isn't testing pycudadecon, so this must be related to our own code that uses pycudadecon

No, not in pyproject.toml. I believe when we run a conda install with pycudadecon, numpy gets upgraded to v2. To prevent this we need to pin it only during pycudadecon installation.

So, command to use for pycudadecon: conda install -c conda-forge pycudadecon numpy==1.24.*

Pin napari < 0.5. This is probably happening automatically by virtue of our pydantic pin, but I'm happy to be explicit about this

yes

Pin pycudadecon >= 0.5

yes

Suggest that the user installs cudadecon >= 0.6 in conda (I can't control this using our pyproject.toml).

No, its working now with pycudadecon 0.5, so we don't need to specify this anymore.

Right, this is a bit tricky. The workflow can produce multiple outputs, including multiple images or no images. Should I add the "first" image output by the workflow, or all of them maybe? The non-image stuff can get thrown away I assume.

We would like only the 'final' image output, if thats what you meant by 'first'..

With non-image stuff, I wanted them to be displayed as a table in napari, but I couldn't really get it working using napari-spreadsheet at this line in napari_lattice here.

Not an immediate priority for now and we could include this as a separate PR..

multimeric · 2024-08-22T03:41:17Z

When using Preview, I still get the deskewed image without processing

Hopefully fixed in 3ddc78c.

pr4deepr · 2024-08-22T07:06:21Z

Hopefully fixed in 3ddc78c.

I'm getting another error now..

This works when I run Save, but when I use Preview, I get the following error with an empty array.

---------------------------------------------------------------------------
TypeError                                 Traceback (most recent call last)
File C:\Users\Public\Documents\Miniconda3\envs\napari_lattice_py310\lib\site-packages\napari_lattice\dock_widget.py:164, in LLSZWidget.preview(self=<napari_lattice.dock_widget.LLSZWidget object>, header='', time=0, channel=0)
    161     preview = lattice.process_workflow().extract_preview()
    163 self.parent_viewer.add_image(preview, scale=scale, name="Napari Lattice Preview")
--> 164 max_z = np.argmax(np.sum(preview, axis=(1, 2)))
        preview = <class 'numpy.ndarray'> (150, 224, 207) uint8
        np = <module 'numpy' from 'C:\\Users\\Public\\Documents\\Miniconda3\\envs\\napari_lattice_py310\\lib\\site-packages\\numpy\\__init__.py'>
    165 self.parent_viewer.dims.set_current_step(0, max_z)

File <__array_function__ internals>:180, in sum(*args=(<class 'numpy.ndarray'> (150, 224, 207) uint8,), **kwargs={'axis': (1, 2)})

File C:\Users\Public\Documents\Miniconda3\envs\napari_lattice_py310\lib\site-packages\numpy\core\fromnumeric.py:2296, in sum(a=<class 'numpy.ndarray'> (150, 224, 207) uint8, axis=(1, 2), dtype=None, out=None, keepdims=<no value>, initial=<no value>, where=<no value>)
   2293         return out
   2294     return res
-> 2296 return _wrapreduction(a, np.add, 'sum', axis, dtype, out, keepdims=keepdims,
        np = <module 'numpy' from 'C:\\Users\\Public\\Documents\\Miniconda3\\envs\\napari_lattice_py310\\lib\\site-packages\\numpy\\__init__.py'>
        a = <class 'numpy.ndarray'> (150, 224, 207) uint8
        np.add = <ufunc 'add'>
        axis = (1, 2)
        dtype = None
        out = None
        keepdims = <no value>
        initial = <no value>
        where = <no value>
   2297                       initial=initial, where=where)

File C:\Users\Public\Documents\Miniconda3\envs\napari_lattice_py310\lib\site-packages\numpy\core\fromnumeric.py:84, in _wrapreduction(obj=<class 'numpy.ndarray'> (150, 224, 207) uint8, ufunc=<ufunc 'add'>, method='sum', axis=(1, 2), dtype=None, out=None, **kwargs={'initial': <no value>, 'keepdims': <no value>, 'where': <no value>})
     82             return reduction(axis=axis, dtype=dtype, out=out, **passkwargs)
     83         else:
---> 84             return reduction(axis=axis, out=out, **passkwargs)
        passkwargs = {}
        axis = (1, 2)
        out = None
        reduction = <bound method ArrayOperators.sum of <class 'numpy.ndarray'> (150, 224, 207) uint8>
     86 return ufunc.reduce(obj, axis, dtype, out, **passkwargs)

File C:\Users\Public\Documents\Miniconda3\envs\napari_lattice_py310\lib\site-packages\pyclesperanto_prototype\_tier0\_array_operators.py:89, in ArrayOperators.sum(self=<class 'numpy.ndarray'> (150, 224, 207) uint8, axis=(1, 2), out=None)
     87     result = sum_of_all_pixels(self)
     88 else:
---> 89     raise ValueError("Axis " + axis + " not supported")
        axis = (1, 2)
     90 if out is not None:
     91     np.copyto(out, result.get().astype(out.dtype))

TypeError: can only concatenate str (not "tuple") to str

Workflow I tried:

!!python/object:napari_workflows._workflow.Workflow
_tasks:
  binarisation: !!python/tuple
  - !!python/name:pyclesperanto_prototype.greater_constant ''
  - median
  - null
  - 100
  median: !!python/tuple
  - !!python/name:pyclesperanto_prototype.median_sphere ''
  - deskewed_image
  - null
  - 2
  - 2
  - 2

This workflow should return a binary image.. I was using it in Crop and Preview Workflow.

multimeric · 2024-08-22T07:20:50Z

~~That's weird. It seems to be np.sum is failing with a tuple of axes, but that functionality has been in numpy for ages. Do you have a really old version of numpy?~~

Oh wait actually it's the pyclesperanto_prototype array that doesn't understand the sum. Can you remind me how you got an array in that format?

pr4deepr · 2024-08-22T07:27:54Z

Sorry, which format?
CL array?

multimeric · 2024-08-22T08:04:57Z

Yeah that's it. What happened was that your workflow returned a CL array, which doesn't know how to be summed. I've now fixed that with a test.

pr4deepr · 2024-08-23T01:25:04Z

Yeah that's it. What happened was that your workflow returned a CL array, which doesn't know how to be summed. I've now fixed that with a test.

Confirm its working!

pr4deepr

All Changes look good and most of core functionality of the plugin and CLI are confirmed to be working...

Great work @multimeric

multimeric added 27 commits July 19, 2023 17:11

Rename underscore modules

43cb4a2

Merge branch 'optional-napari' into thin-wrapper

7f35ac4

Clean up global variables and types in dock_widget

943fb69

Clean up dock_widget

7e3a78f

Fix missing imports in deconvolution

e3742c7

Merge branch 'optional-napari' of github.com:multimeric/napari_lattic…

da2a363

…e into thin-wrapper

Merge branch 'master' of github.com:BioimageAnalysisCoreWEHI/napari_l…

3a9f357

…attice into thin-wrapper

More dock_widget cleanup

248a645

Type signature tidying, and remove an unused function

695b0ea

Refactor workflow augmentation

9752c68

Object oriented system

5db9120

Move to Pydantic, and add field validations for LatticeData and similar

e9f3866

Refactor process() to return a ProcessedSlices object

ba63f39

Fix breaking plugin errors

c02ea40

Initial Restructure of GUI

eee538f

Finish draft of one-page GUI

48b971a

First pass of preview working in the GUI

2370be8

Implemented traffic light system for first two field sets

1e41627

Refactor field validation into mixin

d43bce7

Metaclass attempt

73f248e

Code cleanup, dimension stacking, use mixin for validation logic

af02a25

Implement "disabled", greyed-out steps, fix some bugs in the Lattice

28e62b9

model generation

Add new tab icons, filter down to only images in the layer select, make

39f798b

errors red

Rework the dimension merging

23224b1

Cleanup old code

17e10b6

Use pydantic-cli for CLI

df6513a

Refactor submodels into different files

652a6de

multimeric added 2 commits September 15, 2023 00:35

Rewrite to use typer, all in on pydantic validators

a0e4bb1

Clean up commented/unused code

4a91550

Rework workflow handling: validation, fixed input name etc

91c7ea9

multimeric added 2 commits August 15, 2024 17:36

Old python type issues

2512d3c

Use "deskewed_image" in all workflow tests

5f29bc7

Convert psf to numpy in crop workflow

785010e

Workflow previews

3ddc78c

multimeric added 2 commits August 22, 2024 13:46

pycudadecon dependencies

35baf42

Limit max napari version

938d2ed

Add fix for CLE array output by workflow

399fd74

multimeric mentioned this pull request Aug 22, 2024

Docs #62

Merged

Add binarisation workflow for testing

b7dad44

pr4deepr approved these changes Aug 23, 2024

View reviewed changes

pr4deepr merged commit f0e2349 into BioimageAnalysisCoreWEHI:master Aug 23, 2024
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Pydantic Rework #47

Pydantic Rework #47

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Pydantic Rework #47

Pydantic Rework #47

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