merge the changes of dashboard with GAP

show_plots.py

@@ -867,6 +867,176 @@ fig.subplots_adjust(hspace=0.7)
 plt.show()
 ##
 
+<<<<<<< Updated upstream
+=======
+
+
+
+# %% Dashboard Angepasst
+import pandas as pd
+import matplotlib.pyplot as plt
+import matplotlib.dates as mdates
+import numpy as np
+from matplotlib.gridspec import GridSpec
+
+def to_numeric_comma(s: pd.Series) -> pd.Series:
+    # accepts 1.5 and 1,5
+    return pd.to_numeric(s.astype(str).str.replace(",", ".", regex=False), errors="coerce")
+
+# Load the data
+file_path = '/home/shahin/Lab/Doktorarbeit/Barcelona/Data/Join_edssandsub.tsv'
+df = pd.read_csv(file_path, sep='\t')
+
+# Rename columns to remove 'result.' prefix and replace spaces
+column_mapping = {}
+for col in df.columns:
+    if col.startswith('result.'):
+        new_name = col.replace('result.', '').replace(' ', '_')
+        column_mapping[col] = new_name
+df = df.rename(columns=column_mapping)
+
+# Parse MedDatum safely
+df['MedDatum'] = pd.to_datetime(df['MedDatum'], errors='coerce')
+
+# Patient
+patient_id = '3d942c60'
+
+patient_data = df[df['unique_id'] == patient_id].sort_values('MedDatum').copy()
+if patient_data.empty:
+    raise ValueError(f"No data found for patient: {patient_id}")
+
+# Functional systems + EDSS
+edss_col, edss_title = ('GT.EDSS', 'EDSS')
+
+functional_systems = [
+    ('GT.VISUAL_OPTIC_FUNCTIONS', 'Visual / Optic'),
+    ('GT.CEREBELLAR_FUNCTIONS', 'Cerebellar'),
+    ('GT.BRAINSTEM_FUNCTIONS', 'Brainstem'),
+    ('GT.SENSORY_FUNCTIONS', 'Sensory'),
+    ('GT.PYRAMIDAL_FUNCTIONS', 'Pyramidal (Motor)'),
+    ('GT.AMBULATION', 'Ambulation'),
+    ('GT.CEREBRAL_FUNCTIONS', 'Cerebral'),
+    ('GT.BOWEL_AND_BLADDER_FUNCTIONS', 'Bowel & Bladder'),
+]
+
+# y-axis max rules
+ymax_by_col = {
+    'GT.PYRAMIDAL_FUNCTIONS': 6,
+    'GT.SENSORY_FUNCTIONS': 6,
+    'GT.BOWEL_AND_BLADDER_FUNCTIONS': 6,
+    'GT.VISUAL_OPTIC_FUNCTIONS': 6,
+    'GT.CEREBELLAR_FUNCTIONS': 5,
+    'GT.CEREBRAL_FUNCTIONS': 5,
+    'GT.BRAINSTEM_FUNCTIONS': 5,
+    'GT.EDSS': 10,
+}
+default_ymax = 6
+
+# ---------- Build shared visit dates ticks ----------
+# Use ALL patient visit dates, not only dates with valid numeric values
+event_dates = sorted(patient_data['MedDatum'].dropna().drop_duplicates().tolist())
+
+max_ticks = 8
+if len(event_dates) > max_ticks:
+    idx = np.linspace(0, len(event_dates) - 1, max_ticks, dtype=int)
+    event_dates = [event_dates[i] for i in idx]
+
+# Base timeline for plotting: one row per patient visit date
+timeline = (
+    patient_data[['MedDatum']]
+    .dropna()
+    .drop_duplicates()
+    .sort_values('MedDatum')
+    .rename(columns={'MedDatum': 'x'})
+)
+
+# ---------- A4 figure ----------
+fig = plt.figure(figsize=(11.69, 8.27))
+gs = GridSpec(nrows=3, ncols=4, figure=fig, height_ratios=[2.0, 1.0, 1.0], hspace=0.5, wspace=0.35)
+
+def style_time_axis(ax, show_labels=True):
+    ax.set_xticks(event_dates)
+    ax.xaxis.set_major_formatter(mdates.DateFormatter('%Y-%m'))
+    ax.tick_params(axis='x', rotation=30, labelsize=8, pad=2)
+    if not show_labels:
+        ax.tick_params(labelbottom=False)
+
+def get_plot_df(patient_data, col):
+    """
+    Keep all visit dates.
+    Missing values stay NaN so matplotlib draws gaps instead of zeros.
+    """
+    tmp = patient_data[['MedDatum', col]].copy()
+    tmp = tmp.rename(columns={'MedDatum': 'x', col: 'raw_y'})
+    tmp['y'] = to_numeric_comma(tmp['raw_y'])
+
+    # aggregate if multiple rows exist on same date
+    tmp = tmp.groupby('x', as_index=False)['y'].max()
+
+    # merge onto full timeline so all dates remain visible
+    plot_df = timeline.merge(tmp, on='x', how='left').sort_values('x')
+    return plot_df
+
+# ---------- EDSS main plot ----------
+ax_main = fig.add_subplot(gs[0, :])
+ax_main.set_title(edss_title, fontsize=14, fontweight='bold')
+ax_main.set_ylabel("Score")
+ax_main.set_ylim(0, ymax_by_col.get(edss_col, default_ymax))
+ax_main.grid(True, alpha=0.3)
+
+if edss_col in patient_data.columns:
+    plot_df = get_plot_df(patient_data, edss_col)
+
+    if plot_df['y'].notna().any():
+        # NaNs create visible gaps in the line
+        ax_main.plot(plot_df["x"], plot_df["y"], marker='o', linewidth=3, color='tab:red')
+    else:
+        ax_main.set_title("EDSS (no numeric data)", fontsize=14, fontweight='bold')
+else:
+    ax_main.set_title("EDSS (missing column GT.EDSS)", fontsize=14, fontweight='bold')
+
+style_time_axis(ax_main)
+
+# ---------- Small aligned plots ----------
+small_axes = []
+for k, (col, title) in enumerate(functional_systems):
+    r = 1 + (k // 4)
+    c = (k % 4)
+    ax = fig.add_subplot(gs[r, c], sharex=ax_main)
+    small_axes.append(ax)
+
+    ymax = ymax_by_col.get(col, default_ymax)
+    ax.set_title(title, fontsize=10)
+    ax.set_ylabel("Score")
+    ax.set_ylim(0, ymax)
+    ax.grid(True, alpha=0.3)
+
+    if col in patient_data.columns:
+        plot_df = get_plot_df(patient_data, col)
+
+        if plot_df['y'].notna().any():
+            # NaNs remain in y -> line breaks where data is missing
+            ax.plot(plot_df["x"], plot_df["y"], marker='o', linewidth=2, color='tab:blue')
+        else:
+            ax.set_title(f"{title} (no numeric data)", fontsize=10)
+    else:
+        ax.set_title(f"{title} (missing)", fontsize=10)
+
+    style_time_axis(ax)
+
+# Hide x tick labels on first row of small plots
+for ax in small_axes[:4]:
+    ax.tick_params(labelbottom=False)
+
+plt.tight_layout()
+fig.subplots_adjust(hspace=0.7)
+plt.show()
+
+
+
+##
+
+>>>>>>> Stashed changes
 # %% Table 
 import pandas as pd
 import matplotlib.pyplot as plt
@@ -1982,6 +2152,157 @@ plt.savefig(figure_save_path, format='svg', bbox_inches='tight')
 plt.show()
 ##
 
+<<<<<<< Updated upstream
+=======
+# %% Functional System + EDSS Error Boxplots
+import pandas as pd
+import matplotlib.pyplot as plt
+import os
+import numpy as np
+from matplotlib.patches import Patch
+from matplotlib.lines import Line2D
+
+# --- Configuration & Theme ---
+plt.rcParams['font.family'] = 'Arial'
+figure_save_path = 'project/visuals/functional_systems_edss_boxplot.svg'
+
+# ------------------------------------------------------------
+# Expect functional_systems_to_plot like:
+# [
+#   ('GT.VISUAL_OPTIC_FUNCTIONS', 'result.VISUAL_OPTIC_FUNCTIONS'),
+#   ...
+# ]
+#
+# Add EDSS here:
+# ------------------------------------------------------------
+all_systems_to_plot = list(functional_systems_to_plot) + [
+    ('GT.EDSS', 'result.EDSS')
+]
+
+# --- 1. Build error data for boxplots ---
+boxplot_data = []
+system_labels = []
+sample_sizes = []
+
+for gt_col, res_col in all_systems_to_plot:
+    # Skip safely if a column is missing
+    if gt_col not in df.columns or res_col not in df.columns:
+        print(f"Skipping missing columns: {gt_col}, {res_col}")
+        continue
+
+    sys_name = gt_col.split('.')[1]
+
+    # Robust parsing
+    gt = df[gt_col].apply(safe_parse)
+    res = df[res_col].apply(safe_parse)
+
+    # Error = result - ground truth
+    error = (res - gt).dropna()
+
+    # Ignore all 0 errors
+    error = error[error != 0]
+
+    # Keep only systems that actually have non-zero data
+    if len(error) > 0:
+        if sys_name == 'EDSS':
+            clean_name = 'EDSS'
+        else:
+            clean_name = sys_name.replace('_', ' ').title()
+
+        boxplot_data.append(error.values)
+        system_labels.append(clean_name)
+        sample_sizes.append(len(error))
+
+# Safety check
+if not boxplot_data:
+    raise ValueError("No valid non-zero error data available for any functional system or EDSS.")
+
+# Put n into x-axis labels so it doesn't overlap the plot
+xtick_labels = [f"{label}\n(n={n})" for label, n in zip(system_labels, sample_sizes)]
+
+# --- 2. Plotting ---
+fig, ax = plt.subplots(figsize=(15, 8))
+
+bp = ax.boxplot(
+    boxplot_data,
+    vert=True,
+    patch_artist=True,
+    labels=xtick_labels,
+    showmeans=True,
+    meanline=False
+)
+
+# --- 3. Styling ---
+box_face = '#D6EAF8'
+box_edge = '#2980B9'
+whisker_col = '#7F8C8D'
+median_col = '#C0392B'
+mean_col = '#1ABC9C'
+flier_face = '#95A5A6'
+flier_edge = '#7F8C8D'
+
+for box in bp['boxes']:
+    box.set(facecolor=box_face, edgecolor=box_edge, linewidth=1.5)
+
+for whisker in bp['whiskers']:
+    whisker.set(color=whisker_col, linewidth=1.2)
+
+for cap in bp['caps']:
+    cap.set(color=whisker_col, linewidth=1.2)
+
+for median in bp['medians']:
+    median.set(color=median_col, linewidth=2)
+
+for mean in bp['means']:
+    mean.set(marker='o', markerfacecolor=mean_col, markeredgecolor='black', markersize=6)
+
+for flier in bp['fliers']:
+    flier.set(marker='o', markerfacecolor=flier_face, markeredgecolor=flier_edge, alpha=0.6, markersize=4)
+
+# Reference line at zero error
+ax.axhline(0, color='black', linewidth=1.2, linestyle='--')
+
+# Labels and formatting
+ax.set_xlabel('Functional System / EDSS', fontsize=11, fontweight='bold')
+ax.set_ylabel('Error (Result - Ground Truth)', fontsize=11, fontweight='bold')
+
+# Rotate x labels for readability
+plt.xticks(rotation=45, ha='right')
+
+# Grid and spines
+ax.yaxis.grid(True, linestyle='--', alpha=0.3)
+for spine in ['top', 'right']:
+    ax.spines[spine].set_visible(False)
+
+# --- 4. Legend above the plot, outside the axes ---
+legend_handles = [
+    Patch(facecolor=box_face, edgecolor=box_edge, label='IQR (25th-75th percentile)'),
+    Line2D([0], [0], color=median_col, lw=2, label='Median'),
+    Line2D([0], [0], marker='o', color='w', markerfacecolor=mean_col,
+           markeredgecolor='black', markersize=7, label='Mean'),
+    Line2D([0], [0], marker='o', color='w', markerfacecolor=flier_face,
+           markeredgecolor=flier_edge, alpha=0.8, markersize=6, label='Outlier'),
+    Line2D([0], [0], color='black', lw=1.2, linestyle='--', label='Zero error reference')
+]
+
+ax.legend(
+    handles=legend_handles,
+    loc='lower center',
+    bbox_to_anchor=(0.5, 1.02),
+    ncol=3,
+    frameon=False
+)
+
+# Leave room at the top for the legend
+plt.tight_layout(rect=[0, 0, 1, 0.90])
+
+# Optional save
+os.makedirs(os.path.dirname(figure_save_path), exist_ok=True)
+plt.savefig(figure_save_path, format='svg', bbox_inches='tight')
+
+plt.show()
+##
+>>>>>>> Stashed changes
 
 # %% test
 # Diagnose: what are the actual differences?