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Remove hardcoded /home/gg paths so the project is portable

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Notebooks now use Path.home() / "cupido" for the repo root (works for
any user inside the JupyterLab container), and the offline-tracking
scripts read the ethoscope source-tree location from the new
ETHOSCOPE_SRC config constant — defaulting to ~/Code/ethoscope_project/...
and overridable via the ETHOSCOPE_SRC environment variable.

Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
This commit is contained in:
Giorgio Gilestro 2026-05-01 08:55:44 +01:00
parent 5934dce21e
commit 231c7a437f
8 changed files with 25 additions and 14 deletions
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2
notebooks/flies_analysis.ipynb
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@ -14,7 +14,7 @@
"execution_count": null,
"metadata": {},
"outputs": [],
"source": "import sys\nfrom pathlib import Path\n\nimport pandas as pd\nimport numpy as np\nimport sqlite3\nimport glob\nimport re\nimport matplotlib.pyplot as plt\nimport seaborn as sns\nfrom scipy.spatial.distance import euclidean\nfrom scipy import stats\n\n# Two locations to know about:\n# - DATA_DIR : where the project's bulky data lives (data volume)\n# - REPO_ROOT : where the code repository lives (this notebook is inside it)\nDATA_DIR = Path(\"/mnt/data/projects/cupido\")\nREPO_ROOT = Path(\"/home/gg/ownCloud/Work/Projects/coding/cupido/tracking\")\n\n# Pull every other path constant from scripts/config.py so this notebook\n# stays in sync with the rest of the codebase. (Reason: avoids drift when\n# paths change — config.py is the single source of truth.)\nsys.path.insert(0, str(REPO_ROOT / \"scripts\"))\nfrom config import DATA_RAW, DATA_METADATA, DATA_PROCESSED, FIGURES\n\n# Plotting style\nplt.style.use('seaborn-v0_8')\nsns.set_palette(\"husl\")\n"
"source": "import sys\nfrom pathlib import Path\n\nimport pandas as pd\nimport numpy as np\nimport sqlite3\nimport glob\nimport re\nimport matplotlib.pyplot as plt\nimport seaborn as sns\nfrom scipy.spatial.distance import euclidean\nfrom scipy import stats\n\n# Two locations to know about:\n# - DATA_DIR : where the project's bulky data lives (mounted into the container)\n# - REPO_ROOT : where the code repository is checked out (your home directory)\n# Path.home() expands to the current user's home, so this works for any\n# user running the container (no hard-coded usernames).\nDATA_DIR = Path(\"/mnt/data/projects/cupido\")\nREPO_ROOT = Path.home() / \"cupido\"\n\n# Pull every other path constant from scripts/config.py so this notebook\n# stays in sync with the rest of the codebase. (Reason: avoids drift when\n# paths change — config.py is the single source of truth.)\nsys.path.insert(0, str(REPO_ROOT / \"scripts\"))\nfrom config import DATA_RAW, DATA_METADATA, DATA_PROCESSED, FIGURES\n\n# Plotting style\nplt.style.use('seaborn-v0_8')\nsns.set_palette(\"husl\")\n"
},
{
"cell_type": "markdown",

2
notebooks/flies_analysis_simple.ipynb
View file

@ -14,7 +14,7 @@
"execution_count": null,
"metadata": {},
"outputs": [],
"source": "import sys\nfrom pathlib import Path\n\nimport pandas as pd\nimport numpy as np\nimport matplotlib.pyplot as plt\nimport seaborn as sns\nfrom scipy.spatial.distance import euclidean\nfrom scipy import stats\n\n# Two locations to know about:\n# - DATA_DIR : where the project's bulky data lives (data volume)\n# - REPO_ROOT : where the code repository lives (this notebook is inside it)\nDATA_DIR = Path(\"/mnt/data/projects/cupido\")\nREPO_ROOT = Path(\"/home/gg/ownCloud/Work/Projects/coding/cupido/tracking\")\n\n# Pull every other path constant from scripts/config.py so this notebook\n# stays in sync with the rest of the codebase. (Reason: avoids drift when\n# paths change — config.py is the single source of truth.)\nsys.path.insert(0, str(REPO_ROOT / \"scripts\"))\nfrom config import DATA_RAW, DATA_METADATA, DATA_PROCESSED, FIGURES\n\n# Plotting style\nplt.style.use('seaborn-v0_8')\nsns.set_palette(\"husl\")\n\nprint(f\"Data directory: {DATA_DIR}\")\nprint(f\"Repo root: {REPO_ROOT}\")\nprint(f\"Pandas version: {pd.__version__}\")\nprint(f\"NumPy version: {np.__version__}\")\n"
"source": "import sys\nfrom pathlib import Path\n\nimport pandas as pd\nimport numpy as np\nimport matplotlib.pyplot as plt\nimport seaborn as sns\nfrom scipy.spatial.distance import euclidean\nfrom scipy import stats\n\n# Two locations to know about:\n# - DATA_DIR : where the project's bulky data lives (mounted into the container)\n# - REPO_ROOT : where the code repository is checked out (your home directory)\n# Path.home() expands to the current user's home, so this works for any\n# user running the container (no hard-coded usernames).\nDATA_DIR = Path(\"/mnt/data/projects/cupido\")\nREPO_ROOT = Path.home() / \"cupido\"\n\n# Pull every other path constant from scripts/config.py so this notebook\n# stays in sync with the rest of the codebase. (Reason: avoids drift when\n# paths change — config.py is the single source of truth.)\nsys.path.insert(0, str(REPO_ROOT / \"scripts\"))\nfrom config import DATA_RAW, DATA_METADATA, DATA_PROCESSED, FIGURES\n\n# Plotting style\nplt.style.use('seaborn-v0_8')\nsns.set_palette(\"husl\")\n\nprint(f\"Data directory: {DATA_DIR}\")\nprint(f\"Repo root: {REPO_ROOT}\")\nprint(f\"Pandas version: {pd.__version__}\")\nprint(f\"NumPy version: {np.__version__}\")\n"
},
{
"cell_type": "markdown",

4
notebooks/getting_started/00_welcome.ipynb
View file

@ -149,14 +149,14 @@
{
"cell_type": "markdown",
"metadata": {},
"source": "## Where everything lives\n\nTake a moment to memorize these locations — you'll come back to them often.\n\n| what | where |\n|---|---|\n| Tracking DBs (SQLite, one per video) | `/mnt/data/projects/cupido/tracked/` |\n| Target JSONs (the user-clicked reference points) | `/mnt/data/projects/cupido/targets/` |\n| The metadata table (xlsx + TSV) | `/mnt/data/projects/cupido/all_video_info_merged.tsv` |\n| Source video files | `/mnt/ethoscope_data/videos/` |\n| Project code (this repo) | `/home/gg/ownCloud/Work/Projects/coding/cupido/tracking/` |\n| Your notebooks | `notebooks/getting_started/` (this folder) |\n\nNotice the pattern: **everything bulky or regenerable lives under\n`/mnt/data/projects/cupido/`**. The repository itself only stores code,\ndocumentation, and small metadata files. We'll refer to that data\ndirectory as `DATA_DIR` from here on.\n\nLet's verify a couple of these from inside Python:\n"
"source": "## Where everything lives\n\nTake a moment to memorize these locations — you'll come back to them often.\n\n| what | where |\n|---|---|\n| Tracking DBs (SQLite, one per video) | `/mnt/data/projects/cupido/tracked/` |\n| Target JSONs (the user-clicked reference points) | `/mnt/data/projects/cupido/targets/` |\n| The metadata table (xlsx + TSV) | `/mnt/data/projects/cupido/all_video_info_merged.tsv` |\n| Source video files | `/mnt/ethoscope_data/videos/` |\n| Project code (this repo) | `~/cupido/` (your home directory inside the container) |\n| Your notebooks | `~/cupido/notebooks/getting_started/` (this folder) |\n\nNotice the pattern: **everything bulky or regenerable lives under\n`/mnt/data/projects/cupido/`**. The repository itself, with all the\ncode and notebooks, is checked out into your home directory inside the\nJupyterLab container — that's `~/cupido`, where `~` is shorthand for\nyour home directory (`/home/<your-username>`).\n\nWe'll refer to those two roots as `DATA_DIR` and `REPO_ROOT` from here on.\n\nLet's verify a couple of these from inside Python:\n"
},
{
"cell_type": "code",
"metadata": {},
"execution_count": null,
"outputs": [],
"source": "from pathlib import Path\n\n# Single root for all the bulky / regenerable project data.\nDATA_DIR = Path(\"/mnt/data/projects/cupido\")\n\ntracked_dir = DATA_DIR / \"tracked\"\ntargets_dir = DATA_DIR / \"targets\"\nmetadata_tsv = DATA_DIR / \"all_video_info_merged.tsv\"\n\nprint(f\"Tracking DBs available: {len(list(tracked_dir.glob('*_tracking.db')))}\")\nprint(f\"Target JSONs available: {len(list(targets_dir.glob('*.json')))}\")\nprint(f\"Metadata TSV exists: {metadata_tsv.exists()}\")\n"
"source": "from pathlib import Path\n\n# The two roots we keep coming back to.\nDATA_DIR = Path(\"/mnt/data/projects/cupido\") # bulky data, mounted into the container\nREPO_ROOT = Path.home() / \"cupido\" # the code repo in your home dir\n\ntracked_dir = DATA_DIR / \"tracked\"\ntargets_dir = DATA_DIR / \"targets\"\nmetadata_tsv = DATA_DIR / \"all_video_info_merged.tsv\"\n\nprint(f\"Repo root: {REPO_ROOT} (exists={REPO_ROOT.exists()})\")\nprint(f\"Tracking DBs available: {len(list(tracked_dir.glob('*_tracking.db')))}\")\nprint(f\"Target JSONs available: {len(list(targets_dir.glob('*.json')))}\")\nprint(f\"Metadata TSV exists: {metadata_tsv.exists()}\")\n"
},
{
"cell_type": "markdown",

2
notebooks/getting_started/03_compare_trained_vs_naive.ipynb
View file

@ -48,7 +48,7 @@
"metadata": {},
"execution_count": null,
"outputs": [],
"source": "import sys\nfrom pathlib import Path\n\nimport numpy as np\nimport pandas as pd\nimport matplotlib.pyplot as plt\nfrom scipy import stats\n\n# Two locations to know about:\n# - DATA_DIR : where the project's data files live (read-only data volume)\n# - REPO_ROOT : where the code repository lives (this notebook is inside it)\n# We build both as Path objects, then derive everything else from them.\nDATA_DIR = Path(\"/mnt/data/projects/cupido\")\nREPO_ROOT = Path(\"/home/gg/ownCloud/Work/Projects/coding/cupido/tracking\")\n\n# Tell Python where to find the project's helper modules (in scripts/).\nsys.path.insert(0, str(REPO_ROOT / \"scripts\"))\n\nfrom load_roi_data import load_roi_data\n"
"source": "import sys\nfrom pathlib import Path\n\nimport numpy as np\nimport pandas as pd\nimport matplotlib.pyplot as plt\nfrom scipy import stats\n\n# Two locations to know about:\n# - DATA_DIR : where the project's data files live (mounted into the container)\n# - REPO_ROOT : where the code repository is checked out (your home directory)\n# Path.home() expands to the current user's home directory, so this\n# works for any user running the container — no hard-coded usernames.\nDATA_DIR = Path(\"/mnt/data/projects/cupido\")\nREPO_ROOT = Path.home() / \"cupido\"\n\n# Tell Python where to find the project's helper modules (in scripts/).\nsys.path.insert(0, str(REPO_ROOT / \"scripts\"))\n\nfrom load_roi_data import load_roi_data\n"
},
{
"cell_type": "markdown",