Feature/gui

.gitignore

@@ -1,3 +1,4 @@
+.DS_Store
 /data/*
 notebooks/gol_snaps/
 .idea/

documentation/first_time_setup.md

@@ -280,12 +280,34 @@ Pass `--config` if `pyclm_config.toml` is not in the experiment directory or rep
 uv run pyclm path/to/experiment_dir --config path/to/pyclm_config.toml
 ```
 
-Use `--dry` to do a full rehearsal without connecting to the microscope (images are read from a `tif-source/` folder in the working directory):
+Use `--dry` to run a full rehearsal without connecting to the microscope:
 
 ```bash
 uv run pyclm path/to/experiment_dir --dry
 ```
 
+In dry mode, PyCLM reads simulated images from TIF files placed inside the experiment directory. Positions are loaded from `PositionList.pos` or `multipoints.xml` if present, and each TIF is matched to a position by label (e.g. `on.00.tif` matches position `on.00`) or stem (e.g. `on.tif` matches any position with stem `on`). For explicit control, add a `dry_run.yml` to the experiment directory mapping position names to TIF files:
+
+```yaml
+positions:
+  - name: on.00
+    x: 0.0
+    y: 0.0
+    source: on.tif
+  - name: off.00
+    x: 500.0
+    y: 0.0
+    source: off.tif
+```
+
+Add `--gui` to open a live Napari viewer that updates as data is written:
+
+```bash
+uv run pyclm path/to/experiment_dir --dry --gui
+```
+
+`--gui` can also be used during a real experiment to monitor output in real time.
+
 **Programmatically** (required when using a custom `PositionMover` or custom pattern/segmentation methods):
 
 ```python

documentation/usage.md

@@ -17,7 +17,7 @@ Multiple experiments can be run simultaneously using PyCLM, without any programm
 Once a directory for the multi-experiment has been set up, close out of all existing microscope control software, activate your venv or conda environment, and run main.py with command-line arguments.
 
 - Data is saved continuously during the multi-experiment, and the code execution can be aborted at any time without data loss.
-- Experiment progress can be monitored through the experiment log, as well as through continuous .tif export.
+- Experiment progress can be monitored through the experiment log, or in real time using the `--gui` flag, which opens a live Napari viewer that updates as images are acquired.
 
 ## 3. Analyzing a completed multi-experiment
 Data is exported into separate .hdf5 files for each experiment, which alongside acquired images contain important metadata about timing and imaging configurations. These files also track the light pattern applied at each timepoint and the segmentation generated, if applicable.

pyproject.toml

@@ -9,18 +9,21 @@ authors = [
 requires-python = ">=3.11"
 dependencies = [
     "h5py>=3.14.0",
+    "napari>=0.6.0",
     "natsort>=8.4.0",
     "notebook>=7.5.1",
     "opencv-python>=4.12.0.88",
     "pandas-stubs==2.3.2.250827",
     "pymmcore-plus==0.13.7",
     "pymmcore==11.2.1.71.0",
+    "pyside6>=6.10.2",
+    "pyyaml>=6.0.3",
     "scikit-image>=0.25.2",
     "tifffile>=2025.9.20",
     "toml>=0.10.2",
 ]
 
-[optional-dependencies]
+[project.optional-dependencies]
 cellpose = [
     "cellpose>=4.0.6",
     "torch",
@@ -85,12 +88,6 @@ select = [
 pyclm = "pyclm.__main__:main"
 convert_hdf5s = "pyclm.convert_hdf5s:main"
 
-[project.optional-dependencies]
-analysis = [
-    "colorcet>=3.1.0",
-    "colorstamps>=0.1.3",
-    "seaborn>=0.13.2",
-]
 
 [build-system]
 requires = ["uv_build>=0.8.14,<0.9.0"]

src/pyclm/__main__.py

@@ -7,7 +7,7 @@
 def main():
     args = process_args()
     base_path = Path(args.directory)
-    run_pyclm(base_path, args.config, dry=args.dry)
+    run_pyclm(base_path, args.config, dry=args.dry, gui=args.gui)
 
 
 def process_args():
@@ -19,6 +19,11 @@ def process_args():
     parser.add_argument(
         "--dry", action="store_true", help="run without executing the experiment"
     )
+    parser.add_argument(
+        "--gui",
+        action="store_true",
+        help="run with an updating gui to track experiment progress",
+    )
 
     return parser.parse_args()
 

src/pyclm/controller.py

@@ -29,7 +29,6 @@
 from .core.position_mover import PositionMover
 from .core.real_core import RealMicroscopeCore
 from .core.virtual_microscope.simulated_core import SimulatedMicroscopeCore
-from .core.virtual_microscope.simulated_source import TimeSeriesImageSource
 
 logger = logging.getLogger(__name__)
 
@@ -40,19 +39,15 @@ def __init__(
         config="MMConfig_demo.cfg",
         dry=False,
         position_mover: PositionMover | None = None,
-        dry_image_source: TimeSeriesImageSource | None = None,
+        dry_image_source: Path | None = None,
     ):
         if not dry:
             # Applies if config specifies that a real microscope is in use
             self.core = RealMicroscopeCore()
         else:
             if dry_image_source is None:
-                image_source = TimeSeriesImageSource.from_folder(
-                    Path("tif-source"), pattern="*.tif", loop=True
-                )
-            else:
-                image_source = dry_image_source
-            self.core = SimulatedMicroscopeCore(image_source, slm_device=None)
+                raise ValueError("dry_image_source must be provided when dry=True.")
+            self.core = SimulatedMicroscopeCore(dry_image_source, slm_device=None)
         self.core.loadSystemConfiguration(config)
         self.all_queues = AllQueues()
 
@@ -141,7 +136,9 @@ def initialize(
         )
         self.microscope.declare_slm()
         self.outbox.base_path = out_path
-        self.outbox.initialize(schedule)
+        all_layers = self.outbox.initialize(schedule, self.core)
+
+        return all_layers
 
     def run(self):
         with ThreadPoolExecutor() as executor:

src/pyclm/convert_hdf5s.py

@@ -4,6 +4,7 @@
 from pathlib import Path
 
 import cv2
+import h5py
 import numpy as np
 import tifffile
 from h5py import File
@@ -117,6 +118,10 @@ def make_tif(fp, at, chan="channel_638", binning_override=None):
             if t_val not in f:
                 continue
             data_group = f[t_val]
+
+            if not isinstance(data_group, h5py.Group):
+                continue
+
             if channel_key not in data_group:
                 continue
 
@@ -135,6 +140,9 @@ def make_tif(fp, at, chan="channel_638", binning_override=None):
                 data_dset.refresh()
                 data = np.array(data_dset)
 
+                if data.shape == (0, 0):
+                    continue
+
             except Exception as e:
                 # might happen if writing is in progress for this specific frame
                 continue
@@ -207,7 +215,6 @@ def process_args():
         help="binning during experiment (autodetected if not sepcified)",
         default=None,
     )
-    # Removed binning, overlay_pattern, just_patterns args
 
     return parser.parse_args()