From c40f1e89da5ed62341e5e83fa77f72d8df7eba7d Mon Sep 17 00:00:00 2001
From: max/sooulix <maxime@freepoteries.fr>
Date: Wed, 10 Sep 2025 15:48:29 +0200
Subject: [PATCH] initial commit

---
 .gitignore      |  3 ++
 __init__.py     |  0
 gant_project.py | 88 +++++++++++++++++++++++++++++++++++++++++++++++++
 main.py         | 44 +++++++++++++++++++++++++
 settings.py     | 15 +++++++++
 5 files changed, 150 insertions(+)
 create mode 100644 .gitignore
 create mode 100644 __init__.py
 create mode 100644 gant_project.py
 create mode 100644 main.py
 create mode 100644 settings.py

diff --git a/.gitignore b/.gitignore
new file mode 100644
index 0000000..354574b
--- /dev/null
+++ b/.gitignore
@@ -0,0 +1,3 @@
+**.pyc
+.*.swo
+.*.swp
diff --git a/__init__.py b/__init__.py
new file mode 100644
index 0000000..e69de29
diff --git a/gant_project.py b/gant_project.py
new file mode 100644
index 0000000..875f2e6
--- /dev/null
+++ b/gant_project.py
@@ -0,0 +1,88 @@
+work_packages = [{
+    'title': 'Inclusive Gesture Recognition Models (4 PM)',
+    'duration':9,
+    'start': 0,
+    'method': """
+        Develop an initial gesture recognition baseline using existing datasets (e.g.,
+        $Q, public gesture datasets with diverse motion pattern). Apply unsupervised ML
+        techniques like Dynamic Time Warping (DTW) for feature extraction. Build on
+        these techniques for pretraing supervised ML datasets while identifying biases.
+        Check disparity in model accuracy across participant groups. Assure user studies
+        will be conducted in compliance with GDPR and relevant ethics approvals.
+        """,
+}, {
+    'title': 'Motor Variability in Interaction',
+    'duration': 7,
+    'start': 6,
+    'method': """
+        Conduct at least 3 mixed-method user studies with ~30 participants across three
+        groups: (1) ageing adults (n≈10), (2) participants with motor
+        impairments/disabilities (n≈10), and (3) expert movers/performers (n≈10). Both
+        quantitative kinematic data (motion capture, wearable sensors) and qualitative
+        data (interviews, observations) will be collected. Motor variability will be
+        modelled using clustering algorithms (e.g., k-means, Gaussian mixture models)
+        and nonlinear statistical analyses to capture individual patterns. Build
+        statistical models to capture variability. The prototype developed in WP1 will
+        serve as the baseline architecture for the user studies in WP2. Fuse statistical
+        insights with supervised ML to allow the system to adapt rather than enforce
+        rigid categories.
+    """,
+} , {
+    'title': 'Inclusive, Embodied, and Ecofeminist System Refinement',
+    'duration': 5,
+    'start': 14,
+    'method': """
+    """
+} , {
+    'title': 'Dissemination and Public Engagement',
+    'start': 10,
+    'duration': 13,
+    'method': """
+    """
+}]
+
+deliverables = [{
+    'title': 'Framework specification',
+    'month': 4,
+    'wp': 1
+}, {
+    'title': 'Baseline prototype',
+    'month': 8,
+    'wp': 1
+}, {
+    'title': 'Annotated Dataset',
+    'month': 12,
+    'wp': 2,
+}, {
+    'title': 'Technical Report on Motor Variability',
+    'month': 13,
+    'wp': 2,
+}, {
+    'title': 'Updated prototype with integrated supervised ML and explainability mechanisms',
+    'month': 15,
+    'wp': 3,
+
+}, {
+    'title': 'Design and evaluation framework for inclusive, interpretable ML in movement systems',
+    'month': 18,
+    'wp': 3,
+}]
+
+milestones = [{
+    'title': 'Baseline Gesture Model and Bias Evaluation Metrics Defined',
+    'month': 8,
+    'wp': 1,
+}, {
+    'title': 'Completion of User Studies and Initial Statistical Variability Models',
+    'month': 12,
+    'wp': 2
+}, {
+    'title': 'Completion of Transparent Model Integration and Ethical Evaluation Setup',
+    'month': 13, 
+    'wp': 3
+}]
+
+
+
+
+
diff --git a/main.py b/main.py
new file mode 100644
index 0000000..93c65e5
--- /dev/null
+++ b/main.py
@@ -0,0 +1,44 @@
+import sys
+import pandas as pd
+import datetime
+import plotly.express as px
+from dateutil import relativedelta
+
+import matplotlib.pyplot as plt
+import matplotlib.dates as mdates
+import matplotlib.patches as mpatches
+import mplcursors
+
+from matplotlib import rcParams
+from matplotlib.widgets import CheckButtons
+from .settings import (
+    TITLE, TITLE_SIZE, TITLE_FONT_WEIGHT,
+    FONT_FAMILY, FONT_SANS_SERIF, FONT_COLOR,
+    LABEL_SIZE, DAY_FONT_SIZE, MONTH_FONT_SIZE, MONTH_FONT_WEIGHT,
+    X_LABEL, Y_LABEL, BAR_COLOR, TEAM_BAR_COLORS, DATE_FORMAT
+)
+from .gant_project import work_packages, deliverables, milestones
+
+# style confs
+rcParams['font.family'] = FONT_FAMILY
+rcParams['font.sans-serif'] = FONT_SANS_SERIF
+rcParams['axes.titlesize'] = TITLE_SIZE
+rcParams['axes.labelsize'] = LABEL_SIZE
+
+start = datetime.datetime.now()
+
+data_frame = pd.DataFrame(reversed([
+    {
+        'Work Package': f"WP {n+1}",
+        'Label': f"WP {n+1}: {elt['title']}",
+        'start_date': start + relativedelta.relativedelta(months=elt['start']),
+        'end_date': start + \
+            relativedelta.relativedelta(months=elt['start']) + \
+            relativedelta.relativedelta(months=elt['duration']),
+    }
+    for n, elt in enumerate(work_packages)
+]))
+fig = px.timeline(data_frame, x_start="start_date", x_end="end_date",
+    y="Work Package", color="Label")
+fig.update_yaxes(autorange="reversed") # otherwise tasks are listed from the bottom up
+fig.show()
diff --git a/settings.py b/settings.py
new file mode 100644
index 0000000..864673b
--- /dev/null
+++ b/settings.py
@@ -0,0 +1,15 @@
+TITLE=''
+TITLE_SIZE='12'
+TITLE_FONT_WEIGHT=''
+FONT_FAMILY=''
+FONT_SANS_SERIF=''
+FONT_COLOR='#FFFFFF'
+LABEL_SIZE='12'
+DAY_FONT_SIZE='12'
+MONTH_FONT_SIZE=''
+MONTH_FONT_WEIGHT=''
+X_LABEL=''
+Y_LABEL=''
+BAR_COLOR='#FFFFFF'
+TEAM_BAR_COLORS='#FFFFFF'
+DATE_FORMAT=''