From 0df349a67fadd01785b9d57c2410e3382a9d5324 Mon Sep 17 00:00:00 2001 From: mpitell Date: Thu, 2 Apr 2026 13:56:33 +0000 Subject: [PATCH] Delete README_DragForceParticleTracking.md --- README_DragForceParticleTracking.md | 58 ----------------------------- 1 file changed, 58 deletions(-) delete mode 100644 README_DragForceParticleTracking.md diff --git a/README_DragForceParticleTracking.md b/README_DragForceParticleTracking.md deleted file mode 100644 index 33c4650..0000000 --- a/README_DragForceParticleTracking.md +++ /dev/null @@ -1,58 +0,0 @@ -# Drag Force Particle Tracking Automatic - -Tracks brightfield particles across multiple stage speeds and outputs centroid data for drag force analysis. - ---- - -## Workflow Overview - -1. **Load images** — Scans a main folder for speed subfolders (e.g. `0.1`, `0.15`, `0.2`, `0.25`). Each subfolder contains a TIFF image sequence for one stage speed. Images are converted to grayscale, cropped, and inverted. - -2. **Set tracking parameters** — Configure the number of particles, bounding radius, mask radius, and initial ring radius guess in the setup cell. - -3. **Click particle centers** — An interactive figure opens for each speed. Click the center of each particle in frame 0. Clicks are stored and used as the initial guess for tracking. - -4. **Test run** — Tracks the first 10 frames per speed to verify settings before committing to a full run. - -5. **Verify** — Overlays the fitted rings on frame 0 for each speed. If the circles look off, adjust click positions or tracking parameters and re-run the test. - -6. **Full tracking** — Runs the centroid-fitting algorithm across all frames for every speed. Each frame uses the previous frame's result as the next initial guess. - -7. **Save output** — Choose an output folder using the widget. Saves one CSV and one JSON metadata file per speed. - ---- - -## Key Parameters (Setup Cell) - -| Parameter | Description | -|---|---| -| `MAIN_FOLDER` | Path to the folder containing speed subfolders | -| `TIFF_PATTERN` | Glob pattern for images (default: `*.tiff`) | -| `crop_dimensions` | Pixel crop region applied to every frame | -| `num_particles` | Number of particles to track per frame | -| `particle_r_bound` | Search radius (px) around each particle centroid | -| `mask_r` | Masks bright pixels near the particle center (px) | -| `r0` | Initial guess for the bright ring radius (px) | - ---- - -## Output Format - -For each speed subfolder, two files are saved: - -- **`{speed} mms.csv`** — No header. Each row is one frame. Columns are `cx0, cy0, r0, cx1, cy1, r1, cx2, cy2, r2, ...` (3 columns per particle). -- **`{speed} mms.json`** — Metadata: tracking parameters and initial click positions. - ---- - -## Dependencies - -`numpy`, `pandas`, `scipy`, `scikit-image`, `pims`, `trackpy`, `matplotlib`, `ipywidgets`, `ipympl` - -Install missing packages with `pip install `. - ---- - -## Analysis - -Load the output CSVs into `Drag_auto.ipynb` to select stationary/movement regions interactively and compute drag force vs. displacement per particle.