1936 lines
1.3 MiB
Executable File
1936 lines
1.3 MiB
Executable File
{
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"cells": [
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{
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"cell_type": "markdown",
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"id": "d8960e56",
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"metadata": {},
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"source": [
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"# Motor Imagery Decoder — Train OFFLINE, Evaluate ONLINE (FES vs NOFES)\n",
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"\n",
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"For each subject × offline-session, train a CSP + LDA classifier on the OFFLINE recording, then apply it to the two matched ONLINE sessions.\n",
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"\n",
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"**Pair 1:** train on `S001 OFFLINE_FES` → test on `S002 ONLINE_FES` and `S003 ONLINE_NOFES`\n",
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"**Pair 2:** train on `S004 OFFLINE_NOFES` → test on `S006 ONLINE_FES` and `S005 ONLINE_NOFES`\n",
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"\n",
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"**Metrics reported per (subject × pair × condition):**\n",
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"1. **Classification accuracy** — fraction of cued trials correctly classified\n",
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"2. **Classification amplitude** — mean |LDA decision-function value|\n",
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"3. **SNR** — (a) Fisher ratio of the LDA projection on online data, and (b) mu-band power ratio REST / MI over motor channels C3/Cz/C4"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 2,
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"id": "578c9128",
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"metadata": {
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"execution": {
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"iopub.execute_input": "2026-04-22T19:26:50.521758Z",
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"iopub.status.busy": "2026-04-22T19:26:50.521477Z",
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"iopub.status.idle": "2026-04-22T19:26:50.528154Z",
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"shell.execute_reply": "2026-04-22T19:26:50.527272Z"
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}
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},
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"outputs": [],
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"source": [
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"# Install dependencies if needed\n",
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"# !pip install pyxdf mne scipy numpy matplotlib"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 3,
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"id": "857b22c0",
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"metadata": {
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"execution": {
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"iopub.execute_input": "2026-04-22T19:26:50.530924Z",
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"iopub.status.busy": "2026-04-22T19:26:50.530685Z",
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"iopub.status.idle": "2026-04-22T19:26:51.596469Z",
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"shell.execute_reply": "2026-04-22T19:26:51.595934Z"
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}
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},
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"outputs": [],
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"source": [
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"import os\n",
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"import re\n",
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"import glob\n",
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"import numpy as np\n",
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"import matplotlib.pyplot as plt\n",
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"from matplotlib.patches import Patch\n",
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"import pyxdf\n",
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"from scipy.signal import welch, butter, filtfilt, iirnotch\n",
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"from scipy.linalg import eigh\n",
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"from scipy.stats import wasserstein_distance\n",
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"\n",
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"plt.rcParams.update({'font.size': 11, 'figure.dpi': 120})"
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]
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},
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{
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"cell_type": "markdown",
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"id": "fe68bf0e",
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"metadata": {},
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"source": [
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"## Configuration"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 4,
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"id": "dc4b2c55",
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"metadata": {
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"execution": {
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"iopub.execute_input": "2026-04-22T19:26:51.597901Z",
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"iopub.status.busy": "2026-04-22T19:26:51.597789Z",
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"iopub.status.idle": "2026-04-22T19:26:51.600886Z",
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"shell.execute_reply": "2026-04-22T19:26:51.600373Z"
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}
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},
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"outputs": [],
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"source": [
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"DATA_DIR = os.path.join(os.path.dirname(os.path.abspath('__file__')), 'Group 2 - Glove')\n",
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"\n",
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"# Marker codes (from experiment trigger table)\n",
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"MI_BEGIN = 200\n",
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"MI_END = 220\n",
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"MI_EARLYSTOP = 240 # online only: live classifier fired → successful MI detection\n",
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"REST_BEGIN = 100\n",
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"REST_END = 120\n",
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"REST_EARLYSTOP = 140 # online only: live classifier fired → successful REST detection\n",
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"ROBOT_BEGIN = 300\n",
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"ROBOT_END = 320\n",
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"\n",
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"TARGET_MARKERS = [100, 120, 140, 200, 220, 240]\n",
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"\n",
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"T_PRE = -1.0\n",
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"T_POST = 5.0\n",
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"\n",
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"# ── Preprocessing ────────────────────────────────────────────────────────────\n",
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"NOTCH_FREQ = 60.0\n",
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"NOTCH_Q = 30\n",
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"BP_LO, BP_HI = 8.0, 30.0\n",
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"USE_CAR = True\n",
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"PTP_REJECT_UV = 100.0\n",
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"\n",
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"N_CSP = 4\n",
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"\n",
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"NON_EEG = {'AUX1', 'AUX2', 'AUX3', 'AUX7', 'AUX8', 'AUX9', 'TRIGGER'}\n",
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"RENAME = {'FP1':'Fp1','FPZ':'Fpz','FP2':'Fp2','FZ':'Fz','CZ':'Cz',\n",
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" 'PZ':'Pz','POZ':'POz','OZ':'Oz'}\n",
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"\n",
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"MOTOR_CH = ['C3', 'Cz', 'C4']\n",
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"MU_BAND = (8, 13)\n",
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"\n",
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"PAIRS = [\n",
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" {'name': 'Pair1 (train=OFFLINE_FES)',\n",
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" 'train': 'S001', 'online_fes': 'S002', 'online_nofes': 'S003'},\n",
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" {'name': 'Pair2 (train=OFFLINE_NOFES)',\n",
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" 'train': 'S004', 'online_fes': 'S006', 'online_nofes': 'S005'},\n",
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"]"
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]
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},
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{
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"cell_type": "markdown",
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"id": "21a40df3",
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"metadata": {},
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"source": [
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"## Helper Functions"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 5,
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"id": "e798b039",
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"metadata": {
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"execution": {
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"iopub.execute_input": "2026-04-22T19:26:51.602206Z",
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"iopub.status.busy": "2026-04-22T19:26:51.602130Z",
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"iopub.status.idle": "2026-04-22T19:26:51.616577Z",
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"shell.execute_reply": "2026-04-22T19:26:51.616072Z"
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}
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},
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"outputs": [],
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"source": [
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"# ── XDF loading + session parsing ─────────────────────────────────────────────\n",
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"\n",
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"def get_channel_names_from_xdf(eeg_stream):\n",
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" ch_desc = eeg_stream['info']['desc'][0]\n",
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" channels = ch_desc.get('channels', [{}])[0].get('channel', [])\n",
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" return [ch['label'][0] for ch in channels]\n",
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"\n",
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"\n",
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"_SESSION_RE = re.compile(r'ses-(S\\d+)(O[A-Z]*LINE)_(FES|NOFES)')\n",
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"_SUBJ_RE = re.compile(r'SUBJ_(\\d+)')\n",
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"\n",
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"def parse_session(path):\n",
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" base = os.path.basename(path)\n",
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" m_subj = _SUBJ_RE.search(base)\n",
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" m_ses = _SESSION_RE.search(base)\n",
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" if not (m_subj and m_ses):\n",
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" return None\n",
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" ses_id, raw_kind, stim = m_ses.group(1), m_ses.group(2), m_ses.group(3)\n",
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" kind = 'OFFLINE' if 'OFF' in raw_kind else 'ONLINE'\n",
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" return m_subj.group(1), ses_id, kind, stim\n",
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"\n",
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"\n",
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"def load_xdf_file(filepath):\n",
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" streams, _ = pyxdf.load_xdf(filepath)\n",
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"\n",
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" eeg_stream = marker_stream = None\n",
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" for s in streams:\n",
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" stype = s['info']['type'][0].lower()\n",
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" if stype == 'eeg': eeg_stream = s\n",
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" elif stype == 'markers': marker_stream = s\n",
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" if eeg_stream is None or marker_stream is None:\n",
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" eeg_stream = streams[0]\n",
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" marker_stream = streams[1] if len(streams) > 1 else None\n",
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"\n",
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" eeg_timestamps = np.array(eeg_stream['time_stamps'])\n",
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" eeg_data = np.array(eeg_stream['time_series']).T\n",
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" channel_names = get_channel_names_from_xdf(eeg_stream)\n",
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" sfreq = float(eeg_stream['info']['nominal_srate'][0])\n",
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"\n",
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" valid_idx = [i for i, ch in enumerate(channel_names) if ch not in NON_EEG]\n",
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" channel_names = [channel_names[i] for i in valid_idx]\n",
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" eeg_data = eeg_data[valid_idx, :]\n",
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" channel_names = [RENAME.get(ch, ch) for ch in channel_names]\n",
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"\n",
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" ts_arr = np.asarray(marker_stream['time_series'], dtype=float)\n",
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" marker_data = ts_arr[:, 0].astype(int)\n",
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" marker_ts = ts_arr[:, 1]\n",
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" keep = np.isin(marker_data, TARGET_MARKERS)\n",
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" return eeg_data, eeg_timestamps, marker_data[keep], marker_ts[keep], channel_names, sfreq\n",
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"\n",
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"\n",
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"# ── Preprocessing primitives ─────────────────────────────────────────────────\n",
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"\n",
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"def notch_filter(data, freq, sfreq, Q=NOTCH_Q):\n",
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" b, a = iirnotch(freq, Q, fs=sfreq)\n",
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" return filtfilt(b, a, data, axis=-1)\n",
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"\n",
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"\n",
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"def car(data):\n",
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" return data - data.mean(axis=0, keepdims=True)\n",
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"\n",
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"\n",
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"def bandpass(data, lo, hi, sfreq, order=4):\n",
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" nyq = sfreq / 2.0\n",
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" b, a = butter(order, [max(lo, 0.5) / nyq, min(hi, nyq - 0.1) / nyq], btype='band')\n",
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" return filtfilt(b, a, data, axis=-1)\n",
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"\n",
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"\n",
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"def reject_by_ptp(X, thresh_uv=PTP_REJECT_UV):\n",
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" if X.size == 0:\n",
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" return np.zeros(0, dtype=bool)\n",
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" ptp = X.max(axis=-1) - X.min(axis=-1)\n",
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" return ptp.max(axis=-1) < thresh_uv\n",
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"\n",
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"\n",
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"def extract_epochs(eeg_data, eeg_ts, marker_data, marker_ts, sfreq, begin_code,\n",
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" t_pre=T_PRE, t_post=T_POST):\n",
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" epochs = []\n",
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" n_pre = int(abs(t_pre) * sfreq)\n",
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" for bi in np.where(marker_data == begin_code)[0]:\n",
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" t_start = marker_ts[bi]\n",
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" i0 = np.searchsorted(eeg_ts, t_start + t_pre)\n",
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" i1 = np.searchsorted(eeg_ts, t_start + t_post)\n",
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" if i0 < 0 or i1 > eeg_data.shape[1]:\n",
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" continue\n",
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" ep = eeg_data[:, i0:i1].copy()\n",
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" if ep.shape[1] > n_pre:\n",
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" ep -= ep[:, :n_pre].mean(axis=1, keepdims=True)\n",
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" epochs.append(ep)\n",
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" if not epochs:\n",
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" return np.empty((0, eeg_data.shape[0], 0))\n",
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" min_len = min(e.shape[-1] for e in epochs)\n",
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" return np.stack([e[:, :min_len] for e in epochs])\n",
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"\n",
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"\n",
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"# ── Trial-level parsing from markers ─────────────────────────────────────────\n",
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"\n",
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"def trial_events(marker_data, marker_ts):\n",
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" \"\"\"Parse marker stream into ordered per-trial records.\n",
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" Returns list of dicts with keys: cls ('MI'|'REST'), success (bool),\n",
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" latency (seconds from BEGIN to EARLYSTOP, or None on failure), t_begin.\n",
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" \"\"\"\n",
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" begin_codes = {MI_BEGIN: 'MI', REST_BEGIN: 'REST'}\n",
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" early_of = {'MI': MI_EARLYSTOP, 'REST': REST_EARLYSTOP}\n",
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"\n",
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" begin_idx = np.where(np.isin(marker_data, list(begin_codes.keys())))[0]\n",
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" trials = []\n",
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" for i, bi in enumerate(begin_idx):\n",
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" cls = begin_codes[int(marker_data[bi])]\n",
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" t_begin = float(marker_ts[bi])\n",
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" # Search until next BEGIN (or end of stream) for EARLYSTOP of matching class\n",
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" end = begin_idx[i + 1] if i + 1 < len(begin_idx) else len(marker_data)\n",
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" window = marker_data[bi + 1:end]\n",
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" wts = marker_ts[bi + 1:end]\n",
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" hit = np.where(window == early_of[cls])[0]\n",
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" if len(hit):\n",
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" trials.append(dict(cls=cls, success=True,\n",
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" latency=float(wts[hit[0]] - t_begin), t_begin=t_begin))\n",
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" else:\n",
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" trials.append(dict(cls=cls, success=False, latency=None, t_begin=t_begin))\n",
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" return trials\n",
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"\n",
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"\n",
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"def marker_stats(marker_data, marker_ts):\n",
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" \"\"\"Online performance summary from markers. Returns None for offline sessions.\n",
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" Fields: mk_acc, mi_acc, rest_acc, mi_latency, rest_latency, trials (ordered).\n",
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" \"\"\"\n",
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" trials = trial_events(marker_data, marker_ts)\n",
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" if not trials or not any(t['success'] for t in trials):\n",
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" return None # offline or no successful trials\n",
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" mi = [t for t in trials if t['cls'] == 'MI']\n",
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" rest = [t for t in trials if t['cls'] == 'REST']\n",
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"\n",
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" def _acc(ts): return sum(t['success'] for t in ts) / len(ts) if ts else None\n",
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" def _lat(ts):\n",
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" lats = [t['latency'] for t in ts if t['success']]\n",
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" return float(np.mean(lats)) if lats else None\n",
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"\n",
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" n_correct = sum(t['success'] for t in trials)\n",
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" return dict(mk_acc = n_correct / len(trials),\n",
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" mi_acc = _acc(mi), rest_acc = _acc(rest),\n",
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" mi_latency = _lat(mi), rest_latency = _lat(rest),\n",
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" trials = trials)\n",
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"\n",
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"\n",
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"def load_session_epochs(filepath):\n",
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" \"\"\"Preprocessing pipeline: notch → CAR → bandpass → epoch → PTP-reject.\n",
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" Returns X, y, ch_names, sfreq, n_rejected, stats\n",
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" where `stats` is the marker_stats() dict (None for offline sessions).\n",
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" \"\"\"\n",
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" eeg, eeg_ts, mk, mk_ts, ch_names, sfreq = load_xdf_file(filepath)\n",
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"\n",
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" stats = marker_stats(mk, mk_ts)\n",
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"\n",
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" eeg = notch_filter(eeg, NOTCH_FREQ, sfreq)\n",
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" if USE_CAR:\n",
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" eeg = car(eeg)\n",
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" eeg_bp = bandpass(eeg, BP_LO, BP_HI, sfreq)\n",
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"\n",
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" mi = extract_epochs(eeg_bp, eeg_ts, mk, mk_ts, sfreq, MI_BEGIN)\n",
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" rest = extract_epochs(eeg_bp, eeg_ts, mk, mk_ts, sfreq, REST_BEGIN)\n",
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"\n",
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" n_pre = int(abs(T_PRE) * sfreq)\n",
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" if mi.shape[-1] > n_pre: mi = mi[..., n_pre:]\n",
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" if rest.shape[-1] > n_pre: rest = rest[..., n_pre:]\n",
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"\n",
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" n = min(mi.shape[-1], rest.shape[-1]) if (mi.size and rest.size) else 0\n",
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" mi, rest = mi[..., :n], rest[..., :n]\n",
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"\n",
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" n0_mi, n0_rest = len(mi), len(rest)\n",
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" mi = mi[reject_by_ptp(mi)]\n",
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" rest = rest[reject_by_ptp(rest)]\n",
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" n_rejected = (n0_mi - len(mi)) + (n0_rest - len(rest))\n",
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"\n",
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" X = np.concatenate([mi, rest], axis=0) if (len(mi) or len(rest)) else np.empty((0, len(ch_names), 0))\n",
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" y = np.concatenate([np.ones(len(mi), int), np.zeros(len(rest), int)])\n",
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" return X, y, ch_names, sfreq, n_rejected, stats\n",
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"\n",
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"\n",
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"# ── CSP + LDA (2-class, numpy/scipy only) ────────────────────────────────────\n",
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"\n",
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"def _mean_cov(X):\n",
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" covs = np.einsum('ijk,ilk->ijl', X, X)\n",
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" covs /= np.trace(covs, axis1=1, axis2=2)[:, None, None]\n",
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" return covs.mean(axis=0)\n",
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"\n",
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"\n",
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"class CSPLDA:\n",
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" \"\"\"CSP log-var features + LDA. Ramoser 2000; Blankertz 2008.\n",
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" Ledoit-Wolf shrinkage keeps the generalized eigenproblem well-posed after CAR.\n",
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" \"\"\"\n",
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"\n",
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" def __init__(self, n_csp=N_CSP, cov_shrink=0.05, lda_reg=1e-4):\n",
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" self.n_csp = n_csp\n",
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" self.cov_shrink = cov_shrink\n",
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" self.lda_reg = lda_reg\n",
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"\n",
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" def fit(self, X, y):\n",
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" assert set(np.unique(y)) == {0, 1}\n",
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" C1 = _mean_cov(X[y == 1])\n",
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" C0 = _mean_cov(X[y == 0])\n",
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" n_ch = C1.shape[0]\n",
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" s = self.cov_shrink\n",
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" C1 = (1 - s) * C1 + s * (np.trace(C1) / n_ch) * np.eye(n_ch)\n",
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" C0 = (1 - s) * C0 + s * (np.trace(C0) / n_ch) * np.eye(n_ch)\n",
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" evals, evecs = eigh(C1, C0 + C1)\n",
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" order = np.argsort(evals)\n",
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" k = self.n_csp // 2\n",
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" self.filters_ = np.concatenate([evecs[:, order[:k]],\n",
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" evecs[:, order[-k:]]], axis=1).T\n",
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" F = self._features(X)\n",
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" mu1, mu0 = F[y == 1].mean(0), F[y == 0].mean(0)\n",
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" Sw = np.cov(F[y == 1].T, ddof=1) + np.cov(F[y == 0].T, ddof=1)\n",
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" Sw += self.lda_reg * np.eye(Sw.shape[0])\n",
|
||
" self.coef_ = np.linalg.solve(Sw, mu1 - mu0)\n",
|
||
" self.intercept_ = -self.coef_ @ ((mu1 + mu0) / 2)\n",
|
||
" return self\n",
|
||
"\n",
|
||
" def _features(self, X):\n",
|
||
" Z = np.einsum('fc,ncs->nfs', self.filters_, X)\n",
|
||
" var = Z.var(axis=-1, ddof=1)\n",
|
||
" return np.log(var / var.sum(axis=1, keepdims=True))\n",
|
||
"\n",
|
||
" def decision_function(self, X):\n",
|
||
" return self._features(X) @ self.coef_ + self.intercept_\n",
|
||
"\n",
|
||
" def predict(self, X):\n",
|
||
" return (self.decision_function(X) > 0).astype(int)\n",
|
||
"\n",
|
||
"\n",
|
||
"# ── Evaluation metrics ───────────────────────────────────────────────────────\n",
|
||
"\n",
|
||
"def evaluate(clf, X, y):\n",
|
||
" margin = clf.decision_function(X)\n",
|
||
" pred = (margin > 0).astype(int)\n",
|
||
" amp = np.abs(margin).mean()\n",
|
||
" m1, m0 = margin[y == 1], margin[y == 0]\n",
|
||
" fisher = (m1.mean() - m0.mean()) ** 2 / (m1.var(ddof=1) + m0.var(ddof=1) + 1e-30)\n",
|
||
" return dict(amp=amp, fisher=fisher, margin=margin, y=y, pred=pred)\n",
|
||
"\n",
|
||
"\n",
|
||
"def spectral_snr(X, y, ch_idx, sfreq, band=MU_BAND):\n",
|
||
" def band_pwr(sig):\n",
|
||
" f, p = welch(sig, fs=sfreq,\n",
|
||
" nperseg=min(int(sfreq * 2), sig.shape[-1]),\n",
|
||
" noverlap=int(sfreq), axis=-1)\n",
|
||
" m = (f >= band[0]) & (f < band[1])\n",
|
||
" return np.trapezoid(p[..., m], f[m], axis=-1).mean()\n",
|
||
" return band_pwr(X[y == 0][:, ch_idx, :]) / (band_pwr(X[y == 1][:, ch_idx, :]) + 1e-30)"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"id": "98d225db",
|
||
"metadata": {},
|
||
"source": [
|
||
"## Load Data"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 6,
|
||
"id": "d266216b",
|
||
"metadata": {
|
||
"execution": {
|
||
"iopub.execute_input": "2026-04-22T19:26:51.617805Z",
|
||
"iopub.status.busy": "2026-04-22T19:26:51.617727Z",
|
||
"iopub.status.idle": "2026-04-22T19:27:24.179747Z",
|
||
"shell.execute_reply": "2026-04-22T19:27:24.179038Z"
|
||
}
|
||
},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"Found 24 XDF file(s).\n",
|
||
"Preprocessing: notch 60 Hz → CAR → bandpass 8–30 Hz → baseline-correct → PTP-reject @ 100 µV\n",
|
||
"\n",
|
||
" 002/S001 OFFLINE FES n= 85 (MI=43, REST=42) rej=5\n",
|
||
" 002/S002 ONLINE FES n= 53 (MI=27, REST=26) rej=7 acc=0.883 (MI=0.87, REST=0.90) lat(MI=2.74s, REST=2.46s)\n",
|
||
" 002/S003 ONLINE NOFES n= 52 (MI=26, REST=26) rej=8 acc=0.833 (MI=0.87, REST=0.80) lat(MI=2.26s, REST=2.29s)\n",
|
||
" 002/S004 OFFLINE NOFES n= 90 (MI=45, REST=45) rej=0\n",
|
||
" 002/S005 ONLINE NOFES n= 60 (MI=30, REST=30) rej=0 acc=0.850 (MI=0.83, REST=0.87) lat(MI=2.33s, REST=2.15s)\n",
|
||
" 002/S006 ONLINE FES n= 56 (MI=27, REST=29) rej=4 acc=0.917 (MI=1.00, REST=0.83) lat(MI=2.26s, REST=1.76s)\n",
|
||
" 003/S001 OFFLINE FES n= 89 (MI=44, REST=45) rej=1\n",
|
||
" 003/S002 ONLINE FES n= 59 (MI=29, REST=30) rej=1 acc=0.750 (MI=0.70, REST=0.80) lat(MI=2.59s, REST=2.12s)\n",
|
||
" 003/S003 ONLINE NOFES n= 38 (MI=17, REST=21) rej=0 acc=0.763 (MI=0.76, REST=0.76) lat(MI=2.15s, REST=2.74s)\n",
|
||
" 003/S004 OFFLINE NOFES n= 86 (MI=42, REST=44) rej=4\n",
|
||
" 003/S005 ONLINE NOFES n= 43 (MI=19, REST=24) rej=17 acc=0.717 (MI=0.67, REST=0.77) lat(MI=2.58s, REST=2.53s)\n",
|
||
" 003/S006 ONLINE FES n= 52 (MI=23, REST=29) rej=8 acc=0.767 (MI=0.77, REST=0.77) lat(MI=2.31s, REST=2.56s)\n",
|
||
" 005/S001 OFFLINE FES n= 90 (MI=45, REST=45) rej=0\n",
|
||
" 005/S002 ONLINE FES n= 60 (MI=30, REST=30) rej=0 acc=0.800 (MI=0.67, REST=0.93) lat(MI=2.77s, REST=2.13s)\n",
|
||
" 005/S003 ONLINE NOFES n= 59 (MI=29, REST=30) rej=1 acc=0.933 (MI=0.97, REST=0.90) lat(MI=1.86s, REST=2.23s)\n",
|
||
" 005/S004 OFFLINE NOFES n= 89 (MI=44, REST=45) rej=1\n",
|
||
" 005/S005 ONLINE NOFES n= 58 (MI=28, REST=30) rej=2 acc=0.783 (MI=0.67, REST=0.90) lat(MI=2.12s, REST=2.73s)\n",
|
||
" 005/S006 ONLINE FES n= 59 (MI=30, REST=29) rej=1 acc=0.917 (MI=0.90, REST=0.93) lat(MI=2.31s, REST=2.27s)\n",
|
||
" 009/S001 OFFLINE FES n= 57 (MI=33, REST=24) rej=33\n",
|
||
" 009/S002 ONLINE FES n= 42 (MI=21, REST=21) rej=18 acc=0.717 (MI=0.80, REST=0.63) lat(MI=2.56s, REST=2.09s)\n",
|
||
" 009/S003 ONLINE NOFES n= 1 (MI=1, REST=0) rej=59 acc=0.717 (MI=0.63, REST=0.80) lat(MI=2.36s, REST=2.47s)\n",
|
||
" 009/S004 OFFLINE NOFES n= 86 (MI=42, REST=44) rej=4\n",
|
||
" 009/S005 ONLINE NOFES n= 60 (MI=30, REST=30) rej=0 acc=0.850 (MI=0.80, REST=0.90) lat(MI=2.22s, REST=2.00s)\n",
|
||
" 009/S006 ONLINE FES n= 50 (MI=26, REST=24) rej=10 acc=0.817 (MI=0.83, REST=0.80) lat(MI=2.64s, REST=1.69s)\n",
|
||
"\n",
|
||
"Loaded 4 subject(s): ['002', '003', '005', '009'] | total artifact-rejected epochs: 184\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"xdf_files = sorted(glob.glob(os.path.join(DATA_DIR, '*.xdf')))\n",
|
||
"print(f'Found {len(xdf_files)} XDF file(s).')\n",
|
||
"print(f'Preprocessing: notch {NOTCH_FREQ:.0f} Hz → '\n",
|
||
" f'{\"CAR → \" if USE_CAR else \"\"}bandpass {BP_LO:.0f}–{BP_HI:.0f} Hz → '\n",
|
||
" f'baseline-correct → PTP-reject @ {PTP_REJECT_UV:.0f} µV\\n')\n",
|
||
"\n",
|
||
"sessions = {}\n",
|
||
"total_rej = 0\n",
|
||
"\n",
|
||
"for fp in xdf_files:\n",
|
||
" meta = parse_session(fp)\n",
|
||
" if meta is None:\n",
|
||
" print(f' SKIP (unparsed): {os.path.basename(fp)}')\n",
|
||
" continue\n",
|
||
" subj, ses_id, kind, stim = meta\n",
|
||
" try:\n",
|
||
" X, y, ch_names, sfreq, n_rej, stats = load_session_epochs(fp)\n",
|
||
" except Exception as e:\n",
|
||
" print(f' ERROR {os.path.basename(fp)}: {e}')\n",
|
||
" continue\n",
|
||
"\n",
|
||
" sessions.setdefault(subj, {})[ses_id] = dict(\n",
|
||
" X=X, y=y, kind=kind, stim=stim,\n",
|
||
" ch_names=ch_names, sfreq=sfreq,\n",
|
||
" stats=stats, file=os.path.basename(fp))\n",
|
||
" total_rej += n_rej\n",
|
||
"\n",
|
||
" if stats is not None:\n",
|
||
" info = (f' acc={stats[\"mk_acc\"]:.3f} '\n",
|
||
" f'(MI={stats[\"mi_acc\"]:.2f}, REST={stats[\"rest_acc\"]:.2f}) '\n",
|
||
" f'lat(MI={stats[\"mi_latency\"]:.2f}s, REST={stats[\"rest_latency\"]:.2f}s)'\n",
|
||
" if stats['mi_acc'] is not None and stats['rest_acc'] is not None else '')\n",
|
||
" else:\n",
|
||
" info = ''\n",
|
||
" print(f' {subj}/{ses_id} {kind:<7} {stim:<5} '\n",
|
||
" f'n={len(y):3d} (MI={int(y.sum())}, REST={int((1-y).sum())}) '\n",
|
||
" f'rej={n_rej}{info}')\n",
|
||
"\n",
|
||
"subjects = sorted(sessions.keys())\n",
|
||
"print(f'\\nLoaded {len(subjects)} subject(s): {subjects} | '\n",
|
||
" f'total artifact-rejected epochs: {total_rej}')"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"id": "7b8c8bea",
|
||
"metadata": {},
|
||
"source": [
|
||
"## Verify Session Layout"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 7,
|
||
"id": "611baf23",
|
||
"metadata": {
|
||
"execution": {
|
||
"iopub.execute_input": "2026-04-22T19:27:24.182586Z",
|
||
"iopub.status.busy": "2026-04-22T19:27:24.182447Z",
|
||
"iopub.status.idle": "2026-04-22T19:27:24.188463Z",
|
||
"shell.execute_reply": "2026-04-22T19:27:24.188025Z"
|
||
}
|
||
},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"Channels (32): ['Fp1', 'Fpz', 'Fp2', 'F7', 'F3', 'Fz', 'F4', 'F8', 'FC5', 'FC1', 'FC2', 'FC6', 'M1', 'T7', 'C3', 'Cz', 'C4', 'T8', 'M2', 'CP5', 'CP1', 'CP2', 'CP6', 'P7', 'P3', 'Pz', 'P4', 'P8', 'POz', 'O1', 'Oz', 'O2']\n",
|
||
"Sampling rate: 512.0 Hz\n",
|
||
"Motor channels ['C3', 'Cz', 'C4'] → indices [14, 15, 16]\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"# Verify channel layout is consistent across sessions, locate motor channels\n",
|
||
"ref_subj = subjects[0]\n",
|
||
"ref_ses = next(iter(sessions[ref_subj].values()))\n",
|
||
"channel_names_global = ref_ses['ch_names']\n",
|
||
"sfreq_global = ref_ses['sfreq']\n",
|
||
"\n",
|
||
"mismatches = [f'{subj}/{sid}' for subj in subjects for sid, s in sessions[subj].items()\n",
|
||
" if s['ch_names'] != channel_names_global]\n",
|
||
"if mismatches:\n",
|
||
" print('!! channel mismatch in:', mismatches)\n",
|
||
"\n",
|
||
"motor_idx_global = [channel_names_global.index(c) for c in MOTOR_CH\n",
|
||
" if c in channel_names_global]\n",
|
||
"\n",
|
||
"print(f'Channels ({len(channel_names_global)}): {channel_names_global}')\n",
|
||
"print(f'Sampling rate: {sfreq_global} Hz')\n",
|
||
"print(f'Motor channels {MOTOR_CH} → indices {motor_idx_global}')"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"id": "70922abb",
|
||
"metadata": {},
|
||
"source": [
|
||
"## Train CSP + LDA on OFFLINE, Evaluate on ONLINE"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 8,
|
||
"id": "f5e80da3",
|
||
"metadata": {
|
||
"execution": {
|
||
"iopub.execute_input": "2026-04-22T19:27:24.190995Z",
|
||
"iopub.status.busy": "2026-04-22T19:27:24.190909Z",
|
||
"iopub.status.idle": "2026-04-22T19:27:26.129399Z",
|
||
"shell.execute_reply": "2026-04-22T19:27:26.128933Z"
|
||
}
|
||
},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"[009] Pair1 (train=OFFLINE_FES) / NOFES: only 1 clean epochs — acc=0.717, skipping EEG-derived metrics\n",
|
||
"\n",
|
||
"Subj Pair Cond n trainAcc mkAcc MIacc REacc MIlat RElat |marg| Fisher muSNR\n",
|
||
"----------------------------------------------------------------------------------------------------------------------\n",
|
||
"002 Pair1 (train=OFFLINE_FES) FES 53 0.659 0.883 0.87 0.90 2.74 2.46 0.778 0.288 1.197\n",
|
||
"002 Pair1 (train=OFFLINE_FES) NOFES 52 0.659 0.833 0.87 0.80 2.26 2.29 1.162 0.073 1.452\n",
|
||
"002 Pair2 (train=OFFLINE_NOFES) FES 56 0.811 0.917 1.00 0.83 2.26 1.76 1.012 3.133 1.665\n",
|
||
"002 Pair2 (train=OFFLINE_NOFES) NOFES 60 0.811 0.850 0.83 0.87 2.33 2.15 0.756 0.695 1.576\n",
|
||
"003 Pair1 (train=OFFLINE_FES) FES 59 0.843 0.750 0.70 0.80 2.59 2.12 0.879 0.017 1.347\n",
|
||
"003 Pair1 (train=OFFLINE_FES) NOFES 38 0.843 0.763 0.76 0.76 2.15 2.74 0.910 0.683 1.219\n",
|
||
"003 Pair2 (train=OFFLINE_NOFES) FES 52 0.907 0.767 0.77 0.77 2.31 2.56 1.166 0.000 1.273\n",
|
||
"003 Pair2 (train=OFFLINE_NOFES) NOFES 43 0.907 0.717 0.67 0.77 2.58 2.53 1.071 0.029 1.296\n",
|
||
"005 Pair1 (train=OFFLINE_FES) FES 60 0.978 0.800 0.67 0.93 2.77 2.13 3.346 2.498 2.695\n",
|
||
"005 Pair1 (train=OFFLINE_FES) NOFES 59 0.978 0.933 0.97 0.90 1.86 2.23 3.620 3.029 2.399\n",
|
||
"005 Pair2 (train=OFFLINE_NOFES) FES 59 1.000 0.917 0.90 0.93 2.31 2.27 5.740 6.291 2.911\n",
|
||
"005 Pair2 (train=OFFLINE_NOFES) NOFES 58 1.000 0.783 0.67 0.90 2.12 2.73 5.261 4.325 2.287\n",
|
||
"009 Pair1 (train=OFFLINE_FES) FES 42 0.667 0.717 0.80 0.63 2.56 2.09 0.304 0.040 1.326\n",
|
||
"009 Pair1 (train=OFFLINE_FES) NOFES 1 0.667 0.717 0.63 0.80 2.36 2.47 -- -- --\n",
|
||
"009 Pair2 (train=OFFLINE_NOFES) FES 50 1.000 0.817 0.83 0.80 2.64 1.69 4.673 6.192 1.594\n",
|
||
"009 Pair2 (train=OFFLINE_NOFES) NOFES 60 1.000 0.850 0.80 0.90 2.22 2.00 3.754 8.959 2.000\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"MIN_TEST_TRIALS = 10\n",
|
||
"\n",
|
||
"results = []\n",
|
||
"\n",
|
||
"for subj in subjects:\n",
|
||
" subj_ses = sessions[subj]\n",
|
||
"\n",
|
||
" for pair in PAIRS:\n",
|
||
" needed = (pair['train'], pair['online_fes'], pair['online_nofes'])\n",
|
||
" missing = [k for k in needed if k not in subj_ses]\n",
|
||
" if missing:\n",
|
||
" print(f'[{subj}] {pair[\"name\"]}: missing {missing} — skipping')\n",
|
||
" continue\n",
|
||
"\n",
|
||
" train = subj_ses[pair['train']]\n",
|
||
" if set(np.unique(train['y'])) != {0, 1}:\n",
|
||
" print(f'[{subj}] {pair[\"name\"]}: training set lacks both classes — skipping')\n",
|
||
" continue\n",
|
||
"\n",
|
||
" clf = CSPLDA(n_csp=N_CSP).fit(train['X'], train['y'])\n",
|
||
" train_acc = (clf.predict(train['X']) == train['y']).mean()\n",
|
||
"\n",
|
||
" for cond_key, cond_label in [('online_fes', 'FES'), ('online_nofes', 'NOFES')]:\n",
|
||
" te = subj_ses[pair[cond_key]]\n",
|
||
" st = te['stats']\n",
|
||
" if st is None:\n",
|
||
" print(f'[{subj}] {pair[\"name\"]} / {cond_label}: no EARLYSTOP markers — skipping')\n",
|
||
" continue\n",
|
||
"\n",
|
||
" row = dict(\n",
|
||
" subject=subj, pair=pair['name'], condition=cond_label,\n",
|
||
" train_file=train['file'], test_file=te['file'],\n",
|
||
" train_acc=train_acc, n_test=len(te['y']),\n",
|
||
" acc = st['mk_acc'],\n",
|
||
" mi_acc = st['mi_acc'],\n",
|
||
" rest_acc = st['rest_acc'],\n",
|
||
" mi_latency = st['mi_latency'],\n",
|
||
" rest_latency = st['rest_latency'],\n",
|
||
" trials = st['trials'], # ordered per-trial records for trajectory analysis\n",
|
||
" )\n",
|
||
"\n",
|
||
" # EEG-based metrics require enough clean epochs of both classes\n",
|
||
" if len(te['y']) >= MIN_TEST_TRIALS and set(np.unique(te['y'])) == {0, 1}:\n",
|
||
" res = evaluate(clf, te['X'], te['y'])\n",
|
||
" snr_s = spectral_snr(te['X'], te['y'], motor_idx_global, te['sfreq'])\n",
|
||
" row.update(amp=res['amp'], fisher=res['fisher'], mu_snr=snr_s,\n",
|
||
" margin=res['margin'], y_test=res['y'], pred=res['pred'])\n",
|
||
" else:\n",
|
||
" print(f'[{subj}] {pair[\"name\"]} / {cond_label}: only {len(te[\"y\"])} clean epochs — '\n",
|
||
" f'acc={st[\"mk_acc\"]:.3f}, skipping EEG-derived metrics')\n",
|
||
" row.update(amp=np.nan, fisher=np.nan, mu_snr=np.nan,\n",
|
||
" margin=np.array([]), y_test=np.array([]), pred=np.array([]))\n",
|
||
"\n",
|
||
" results.append(row)\n",
|
||
"\n",
|
||
"hdr = (f'{\"Subj\":<5} {\"Pair\":<28} {\"Cond\":<6} {\"n\":>4} '\n",
|
||
" f'{\"trainAcc\":>9} {\"mkAcc\":>7} {\"MIacc\":>6} {\"REacc\":>6} '\n",
|
||
" f'{\"MIlat\":>6} {\"RElat\":>6} {\"|marg|\":>8} {\"Fisher\":>8} {\"muSNR\":>7}')\n",
|
||
"print('\\n' + hdr)\n",
|
||
"print('-' * len(hdr))\n",
|
||
"for r in results:\n",
|
||
" fmt = lambda v, s: (f'{v:{s}}' if (v is not None and not (isinstance(v, float) and np.isnan(v))) else f'{\"--\":>{int(s.split(\".\")[0].lstrip(\">\"))}}')\n",
|
||
" print(f'{r[\"subject\"]:<5} {r[\"pair\"]:<28} {r[\"condition\"]:<6} {r[\"n_test\"]:>4} '\n",
|
||
" f'{r[\"train_acc\"]:>9.3f} {r[\"acc\"]:>7.3f} '\n",
|
||
" f'{r[\"mi_acc\"]:>6.2f} {r[\"rest_acc\"]:>6.2f} '\n",
|
||
" f'{r[\"mi_latency\"]:>6.2f} {r[\"rest_latency\"]:>6.2f} '\n",
|
||
" f'{fmt(r[\"amp\"], \">8.3f\")} {fmt(r[\"fisher\"], \">8.3f\")} {fmt(r[\"mu_snr\"], \">7.3f\")}')"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"id": "2ab81600",
|
||
"metadata": {},
|
||
"source": [
|
||
"---\n",
|
||
"## Figure 1 — Per-metric comparison (FES vs NOFES)"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 9,
|
||
"id": "d53e63b9",
|
||
"metadata": {
|
||
"execution": {
|
||
"iopub.execute_input": "2026-04-22T19:27:26.130998Z",
|
||
"iopub.status.busy": "2026-04-22T19:27:26.130913Z",
|
||
"iopub.status.idle": "2026-04-22T19:27:26.627725Z",
|
||
"shell.execute_reply": "2026-04-22T19:27:26.627293Z"
|
||
}
|
||
},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"image/png": 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",
|
||
"text/plain": [
|
||
"<Figure size 1680x1080 with 4 Axes>"
|
||
]
|
||
},
|
||
"metadata": {},
|
||
"output_type": "display_data"
|
||
},
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"Saved: fes_vs_nofes_metrics.png\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"METRICS = [\n",
|
||
" ('acc', 'Classification accuracy', '0–1'),\n",
|
||
" ('amp', 'Classification amplitude (mean |decision fn|)', 'a.u.'),\n",
|
||
" ('fisher', 'Fisher ratio on LDA projection (test-set SNR)', 'a.u.'),\n",
|
||
" ('mu_snr', 'μ-band power ratio REST / MI @ C3/Cz/C4', 'ratio'),\n",
|
||
"]\n",
|
||
"\n",
|
||
"cond_color = {'FES': '#E05C2A', 'NOFES': '#2A7BE0'}\n",
|
||
"\n",
|
||
"fig, axes = plt.subplots(2, 2, figsize=(14, 9))\n",
|
||
"fig.suptitle('Online decoding: FES vs NOFES feedback (per subject × offline-trained model)',\n",
|
||
" fontsize=13, fontweight='bold', y=1.00)\n",
|
||
"\n",
|
||
"for ax, (key, title, unit) in zip(axes.ravel(), METRICS):\n",
|
||
" labels, vals, colors = [], [], []\n",
|
||
" for subj in subjects:\n",
|
||
" for pair in PAIRS:\n",
|
||
" tag = pair['name'].split()[0] # \"Pair1\" / \"Pair2\"\n",
|
||
" for cond in ('FES', 'NOFES'):\n",
|
||
" row = next((r for r in results\n",
|
||
" if r['subject']==subj and r['pair']==pair['name']\n",
|
||
" and r['condition']==cond), None)\n",
|
||
" if row is None: continue\n",
|
||
" labels.append(f'{subj}\\n{tag}\\n{cond}')\n",
|
||
" vals.append(row[key])\n",
|
||
" colors.append(cond_color[cond])\n",
|
||
" x = np.arange(len(vals))\n",
|
||
" ax.bar(x, vals, color=colors, edgecolor='white', zorder=2)\n",
|
||
" ax.set_xticks(x); ax.set_xticklabels(labels, fontsize=7.5)\n",
|
||
" ax.set_title(f'{title} ({unit})', fontsize=11, fontweight='bold')\n",
|
||
" ax.grid(axis='y', alpha=0.3)\n",
|
||
" ax.spines[['top','right']].set_visible(False)\n",
|
||
" if key == 'acc':\n",
|
||
" ax.axhline(0.5, color='gray', linestyle='--', lw=0.8, alpha=0.6)\n",
|
||
"\n",
|
||
"fig.legend(handles=[Patch(color=cond_color['FES'], label='ONLINE_FES'),\n",
|
||
" Patch(color=cond_color['NOFES'], label='ONLINE_NOFES')],\n",
|
||
" loc='upper right', ncol=2, bbox_to_anchor=(0.98, 1.0))\n",
|
||
"plt.tight_layout()\n",
|
||
"plt.savefig('fes_vs_nofes_metrics.png', dpi=150, bbox_inches='tight')\n",
|
||
"plt.show()\n",
|
||
"print('Saved: fes_vs_nofes_metrics.png')"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"id": "248740bd",
|
||
"metadata": {},
|
||
"source": [
|
||
"---\n",
|
||
"## Figure 2 — LDA decision-function distributions\n",
|
||
"\n",
|
||
"Visualizes classification amplitude and separability directly: wider FES vs NOFES spread between MI and REST curves = higher Fisher ratio and larger mean |margin|."
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 10,
|
||
"id": "393042a0",
|
||
"metadata": {
|
||
"execution": {
|
||
"iopub.execute_input": "2026-04-22T19:27:26.629009Z",
|
||
"iopub.status.busy": "2026-04-22T19:27:26.628916Z",
|
||
"iopub.status.idle": "2026-04-22T19:27:27.543034Z",
|
||
"shell.execute_reply": "2026-04-22T19:27:27.542546Z"
|
||
}
|
||
},
|
||
"outputs": [
|
||
{
|
||
"name": "stderr",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"/Users/adipu/ECE374N/Final Project/venv/lib/python3.13/site-packages/numpy/lib/_histograms_impl.py:897: RuntimeWarning: invalid value encountered in divide\n",
|
||
" return n / db / n.sum(), bin_edges\n"
|
||
]
|
||
},
|
||
{
|
||
"data": {
|
||
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aChipW+0OO+xgI0eOdEFKLWfQoEEuq0k/fKPRaLP5lNV07LHH2qhRo6ysrMzNM3ToUBd00g9adYVfmemzacmyFi5caBMnTnTTKLtW86ju4mGHHWZTp05tNn1q11z9EL/llltcF+HS0lK3fo4++mj74Ycf0mZ4/uIXv7Cf/OQnLntT3Ym1XjXv6aefbjNnzszZpVuBhZNPPtm1MRwOx7v3qtvxcccd536ka1vr/as9I0aMsP3339/++c9/pl3ud999F3/s7rvvTlu3N1e3cgWxlSWmAKL2N70vrQdlpeqHv7LIUvetxNfROtW22XnnnV3ty4qKCrevvv3229YS2qZ+mZdU9fX18cy2lujOn610JSD8WrYvv/xyfLp///vfzWrF5qqBrPX917/+1WX/an0pi1nrb4MNNnA9KbRf+xRgOvLII11W4pAhQ9y0CoAp+HX44YfbO++8k7YrfSJ9phPb4wfAc9W51UU6devfbLPN4scDtXffffd12Zr51Lp++OGHbZtttnH7sZax995722effWaF+Mtf/uIy/9dbbz23X6gdyvBeZ511XPd+Za6mSt0GCs7puKJgnNaf2vTiiy/GPyNazuDBg91xQseNZ555ptkyU9fX7Nmz3XFG+5HmU+bqH//4x4I+T+m2gX9c1THIp2NTtn0y076WrZSJ2nnzzTe79ar2a9vqs5C4/2VS6HdFPpT969P21fHy/PPPd8coHbP1WWsJbfu33nor/r+Oh8r2vfDCC93+rfuffPKJffXVV7brrrvmtUzN19DQ0KL26AKkLlApWPz6668n9ZzKFMRWwNt3xx13tOh1AQBocx4AAJ3Q2LFj1Yfc3X73u9+lnebFF1/0+vbtG58u9bbRRhvFp3355ZeTntP/vqeffjrjMvzbz372My8ajcbn+eyzz7zKysqs84wfP77F02fTkmVNnTrVGzx4cMbpQ6GQd/PNNyfNc9dddyVNs/POO6edd/jw4d7MmTOT5u3fv3/W9mm7ffLJJ0nzqM3+8wMGDPDWXnvtpHkmTJjgpjvjjDNybq8rrrgi7XIz3fz9IXHakSNHJrXvyy+/9NZYY42sy9lll1282tra+DzffPNN0vPbbbedFwgEms1XVlbmffrpp14hFixY4PZxzX/jjTc2e/6AAw5wzx155JFJ+24+uvtnK91+pb/ZlrHjjjumnS7RkiVLvO233z7rct5///1m2yjTLRgMevfdd198erUh1/rUPpc6rd9239tvv+0NHDgw63KOOOKIpO2Sup0zvU8td/78+Xnva5tttlnWdpSUlCTtU+m2weabb572mPbwww97a665Ztr1+tJLLyUtM3F9jR492lt11VXTtufoo4/O2pZMy/S3QepxNd0t0z6ZKt08PrUz3bK1PtZdd92M+0ZLvivyPV5VVFTk/F4v1KJFi5Lad/rpp3tNTU15zZu6Tw8dOjR+/+qrr067HVO/F1K3p/5P1K9fv/hzP/3pT9O244MPPkhaRur3KQAAnQElLAAAnY7qHidmZCoDMpUyWDXwTmK3V2U0KjNUI5krc2/58uV5vZ6yW5UBqMw0DbqjjKu6ujp7//33Xaaafqc/++yz9thjj9m4cePcPMpq8l9b9QqViatMW2VtKtNJtQ4TFTp9NoUuS1mzygzU86JMPHUf7tevn8vS0/TKAj3ttNNs4403tp/+9KdpX1dZnMqq3HTTTV2WprKr5Pvvv3ddbrV+fMpWU8adsk6VfakMOW0zZSyqq7FGn1etyXSZgIm1K5Wpq/ZoemUXirId1eVX2cx6D8o4rK6udu/lvffec9MoG2/8+PEu686va3zFFVe45Yi2dWIXf2V8ZqP1o/1NWdi+Aw880GUlar342XNqg9ZjpgGh3njjDTeokzKl1VX6H//4h3tc+5uyG2+77TbLh9bhLrvs4mp/jh492rUllWprPv/883bPPffE95tgMHfns5762fJrG2sb+Nt5jTXWcFmb+dYR1j7nfy78ebQutZ8qMzc1s1ft1XbUfqTPiTJFtd///e9/d9Mri1T70wEHHOCe82vqarAwn7Iq1XafXitXxqYGFZs/f358G6m7vj6zTz31lNunRBmi2leVJZqO3qcyVHfffXd3PNC+LVru5MmT7ZxzzrF8aL/Qe1prrbXiWf0aEO3xxx93xxZlgv761792ZQ4yUc3a448/3m0/9ZLQd4g+s8rs1GBmqq2r9afM+UgkEq83q2z6dL744guXLf+b3/zGZYXrM+QfP7W/aZtqHbaE1pl6aDz00EPx45Xed+J6XtkSKU8++aRrp0/HfGW6a13q8UyDQ7bWd0W6bHf1SEk8btxwww2ul9FNN90UPy4p61vHbNFrKhM6F6079RbxM++V0az3qHrLaqPOH7Sd86lpryz23//+9+4z8oc//MFloGv5LaFlKNs8sS6zMrjT0feTvsd0fBWVs8g0LQAAHaajI9gAAKRKzdr897//3WyaM888M2maq666qtk006dPzytLMnF6Zazdcsst3rXXXutdc8013iqrrBKf55hjjolPe9ppp8UfP/HEE5stq7Gx0fv2229bPH02hS5L2WKJ2XwzZsyIPxeLxbytttoq/vy+++6bMbMq8f0rM3HMmDHx55RVO3v27KR2LF261Hv++ee922+/3bv++uvd+tTyE9uitmbKFNb7zETtfu+997x77rnH++Mf/+iWfdlllyXNr+cSKXMsV7Z3pgzkp556KmnZF1xwQdK6SMyYV4aen4GZui8rW1vrxbfJJpvEn9t00029fCxcuDA+X1FRkXfdddd5DzzwQNrbKaecEl9+vpnIPeGzlS1zM1vmbras0GnTpiU9vsUWW3g1NTVJ82q/UJZyImVLvvHGG+7zpkxyrRtlUSYu67XXXsu7/bnex0033ZQ0/x133BF/rr6+3mXf+s8pCz0SiaTdzltuuWX886u/gwYNij+3//77e4Woq6tzy7/zzju9G264wa2D1AzaxONW6jbQZ9936KGHJj33hz/8If7cQQcdFH9cmaGZ1lfqOv/iiy/c5zoxaz5TW/LZBrl6O+Sz7Gz7wR577BF/PBwOu/b7Xn311aT5EtvV0u+KbLRP6bPgz7f66qt75eXl8f+1vfz9KLFt22yzjZevJ5980mWVJ76vxFtxcbE7xujYmSh1n9ZnUL1X/P/1OSw0AzndrbS01LvwwgvdOsxkrbXWik9/ySWX5P3eAQBoL2QgAwA6HT8zLl3tRF9iVqEyldINipUrqzSx/qQy8BIzB9NJrNu74447uoxRuf32290gParZqSw6ZVwqY1PZty2dPptCl5X4vpSBplrBmWSrQ6nsSp8yxrTO/NrBimUoC3DPPfd02X2qP6lMsGx1JPWcsi1VYzRTHcp0lPGrbMNvvvnGsklXZ7mlUteLslwT14XWjV87Vxl6yqBXVmUqrbPEgQCVPaxsXPGzo3PRtvfnUablGWeckdd8yqJUXd1cdUB78mdrZaRmOl9wwQUuWz6RMqMTPfjggy6bUxmaHbEvKztXmak+Zdsq89Gvp6t9UjWIlSGZStmZyhYW/V199dXj7yPffVm07VRrO3GAtUzrIFMW+C9/+cv4/dTa5YmZnKqR7cvWRr0X9XJInE9Zwf5+7GcOd1aJdYpVDzrxfaseud5fuuNna31XJNKAdH57dOzT50TZ5Mrg1vHrgQcesCVLlrhBc3Xfp89tvrQsZe1efvnlLlNaWeaJlOmsWtsa0E7H5mw9MdRzQ3WUZ82a5f4qC31l/fznP3fZzenqWCee50yfPj3tORAAAJ0BAWQAQKezIrEqu8RuoQoO5dM1PxN1rfUDctkkBkM1j4KkGtjN75KfuAx1l7722mvdoFktmT5XewtZVuK6ykXTKgCcbn2qO3O2//2AjLqQq/tvPjIFmBVoS3fhQAP2aZCvfEootHQQpHRS16EGPMv2f6Z1nhrcUsDOl+/gXCo10BL+gH+59OTP1spI3eYK0mWjNirwmc92b6t92R8csaP2ZZXMUMAuH9nWgV/eRlLfj18SwS/Xkc/3TOqxLfWxQgLkrUlt9oOQ2daHArK53ku6AHJrfVckeuGFF+L3dfFKxy/dVN5BF7T8MjbbbbddvEyJlpl4USAfKqeh5aicjS4i6abB+RIHxVQgW0FyXXTKRINwagA8DcqpdawLQYVQaSRduFKpH5USkUcffdRdTFOZl9T9M91nJp9zIAAA2lvLfxEAANBGVBMz14/axDqf+mGWb8AiXa3LxGCT6uWq7qaySPUjTvUqM1GtRGUKKeNJo90rEKIfjlJfX+8yCxNr5hY6fTaFLCtxXfXu3dvV38x0U13QTFlSfl3MTP+rnqufVZkYvHnrrbdcm7Q+ldGVj9TMTZ/q5iYGj9Vm7R9adr51eVsita6sarRm+z9THVo/Y9OXLSMtE2Vfn3vuufHlKTih95/u5teh1XSqP+3vI9n09M9WS6Vu81wZ8o888kh83Wo/uP/++10WrtbNJ5980i7tVCBU2ZkdtS8nHiv0mVcAUHVgtQ5UBzpfqW1JlBg0zlfqsS31Mf9Y19ZSg7O6QOL78ssvM86X2L5c7yVRa31XZApmq8dJYmb4jTfeGP9fNeH9zGEFltWLoCVUB1vZyzpGvvTSS+7iUSId03I56qij4ln3f/3rX+3zzz/P+/X32GMPO++88+yJJ55wxx2fstYT32+qxPOcfC70AQDQ3shABgB0OsomU9agAj+ioFMqdcNVhpH/w0sD8qR25VcAJ1cWYOIPWtFgZH6Gp7pu+wNKpdKy9SNdGXwa6E03vy1+5qwCZQqgaSCuQqfPptBlKTNLwUNRgGqzzTZLO3iUsr/0Yz9TUODuu+92610U+NIgWz7No+WmrlM9psGM/HkUNFsZqdvrmGOOiQ9ylBiMyhVk8gcrypey4xJpkKbLLrss/r60bhLLAvjvua34Gd5XXnmly3jTgFwamC+RBilUoEfvW+tdmdv56MmfrZXhfzZ8GrRRGZcaHMunNmn/0IBeiet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33Pi20HwbbrhhfP7jjz/eTjnlFBszZox9//331qtXr/jr3XvvvbbBBhvYI488Yn/4wx/cMrX+N910U/vrX//arH1Tpkyx3/3udzZy5Ei3jdZYYw2bPHmya6MU+hraN7bffns3XU1Njc2ePdvtO3LggQfaBRdcYB2deew1NZoFQx3aDgAAAKC9uczjiioLlpaz8gGghyCA3IkoeFw0bI20zylY1TR3hoX7DrJQ/6EWqqzKq1tRw6fvFtSGxx9/PB7UTaSA3UknnZT0mALB48aNs1dffdXWX39999j7778fD1CmUrBQAU85++yzXcDx2WefbfFrvP766+7/b7/91rbeemsXXG1LCh6vMSh3pnB1XdQaI54N7x+0Ef2KrDicOeD89fymvF+/urraHnjgATvssMOaPadgrILHWp8jRoywxYsX23777eeCshdeeGF8unfeecdKS0ubza+A+x577JH0mIK2p556qv3nP/+xVVZZxe1P2daxgv0PPvigm+7QQw+1iRMn2m233dai11Cg2X8tXXxQINzfdzoDZR4HBw23cL8VAXIAAACgp1DmcXjgqmZhelECQE9BDeQuwA8eWzRSUPC4rbsVKfu3trbWBg8eHH9sk002yRhATjR27Fj77rvv2vQ1Wl0er6ng8ewlUQuHLGfwuFCXXHKJTZgwwZqamged9fh1113ngsfSt29f+9Of/mRXXHGFywhuiTlz5lhRUZH169fP/a91rnWfi6ZTdng+27elr9HhgiErGjzCAmGuwQEAAKBnUeZxaMCwfH4eAQC6CQLI3Tl4XLus4G5Fv/jFL2zjjTd2Nz/DV1TKwn9ct88//9wFKY899lhba621bO+993YlJ1SmIBdlxT755JN20EEHJT3emq/REVoSPI5E86+rrCxrlelQaYjUIPs333zjnk+0zjrruOCsynv4ttpqq/j6/eqrr+KPq5RF4rrXMjfaaCPbbLPNXFBaWeA33XSTLVy4MGc7VVLkH//4hys1kag1X6OjKfM4UETGBQAAAHqeYNXAjknoAQB0GNLnunPwuLxXwd2KCilhIbfccoudfvrp9tJLL7nyCcp4fe+99+L1ahN9/PHHLnA4a9Ysq6ystKlTp7b6a3Sl4LHKXMxZGrGNLHcNZN9ll11mP/vZz2z8+PF5TZ96YldICQt54oknbNq0aa6EiO4rgK/t6GcMJ3r++efd9lUwe/To0XbIIYe0+mt0FmQeAwAAoKcidgwAPQ8ZyN04eNxe3Yo0YNpxxx1njz76qG277bb29NNPZ6yBrLq2CiCrTMHJJ5/c6q/RlYLHMxY1WTRa2GupDrTKfyhT16d6wauvvnqzGsGffvqpywZW9vbK0Gsqe/iFF15wA/mpJnGmGsjavjNnzrRwOOzKarT2awAAAAAAAKB9EUDu1sHjto0e19TU2D//+U/32rJkyRKXfapgZjbFxcVucLXnnnvODYjXFq/RFYLHkajZgF6FfwQ1ON0NN9xgdXV18ccUrD3zzDPj5T00iN6vfvUrN/hcuozjfCjQ/9Zbb8X/V2B4/vz5Ode9Atq33367TZo0yQ2S1xavAQAAAAAAgPZBCYtOxIs0WeOMLyyyaI5ZLGrBqgEWWLrQYkuz14RVbDVWPd8NmOdqHoeLzZv9TXyZrUH1iTUom++ss86yffbZx5UlOPXUU12QMhKJ2C9/+UtXRzkXDYqngKeCoSpb0Bav0dqaop59Pf//1+fyhqgtWBazUMhsSO+wzVwcyavmscpWRH8MHheHCw8gK7iqesFaLz6VtFBAWVnACrZrPR155JGuLEg+lP2rwK9PAWplfSswrcHwysrKXO1qldDIZ5C7DTfc0NW4VjmKG2+8sU1eAwAAAAAAAG0v4PmpnWgTn3zyieuerxqvGgDN9/XXX7u/CqBJ4/dfmNfU0CZtCBSVWPHw0W2y7J7iizmN1hBpm49KSThgo4cwIFtLpX6W2lrD1x9b4zefWNGwNazph6+tePX1rGSNDdrluAEAQGfC9xXQ86zsuTDHDQDomshA7iQI8HZuBHgBAAAAAADQE1EDGQAAAAAAAACQFgHkDkT1EKBrf468SO661wAAAEB3FK1b3tFNAAC0E0pYdJBgMGgNDQ1usLNwmM0AtIQ+P7qVlJS0ac3rdHWqvaZGN+BliW3Uqq8NAAAAdHbRmmqLVS/o6GYAANoJkcsOUlVVZXPmzLGvvvrKBZADgUBHNQXospnHCh7HYjH3eWpNCh5/MKPBikIBa4p6tvGIkmaZx01zZ5jFoq36ugAAAEBXyDxWMoUFQx3dFABAO6GERQfp27evDRkyxGVOEjwGCqfPjT4/+hzp89TaFDxeY2CR+5tKmccWjViwakCrvy4AAADQmbnM41DYwv2GdHRTAADthAzkDqSgV1sEvgC0sVjUQv2HWmDpQlY1AAAAepZgyIoGj7DI/Jkd3RIAQDshAxkACj1wVg2wUGXrls0AAAAAugJlHgeKkscHAQB0bwSQAaBAobIK1hkAAAB6pACDwANAj0MAGQCyiEQ91g8AAAAAAOixCCADQAaNEc/mLI2wfgAAHerKK6+0gw8+2EaNGmXBYNDCLcj+e/rpp+24446z9dZbz3r16mUDBw60bbbZxv7yl79YJMJ3HQAAADJjED0AyJB5PGNRk0WjrB4AQMc677zzrE+fPrbJJptYTU2NzZ8/v+BlHH/88VZRUWH77befrbPOOlZdXW0PPvigHXvssfboo4/aM888Y4FAoE3aDwAAgK6NADIApKHM40G9wjagFx01AAAda/r06bbmmmu6+2PGjGlRAPn++++3nXbaKSlI/Nvf/tYt7x//+Ic9++yztueee7ZquwEAANA9EBkBgDSUeTy0T8gqSkKsHwBAh/KDxytj5513bpZhHAqF7MADD3T3P/roo5V+DQAAAHRPZCADQBrKPK4qC9nCmhjrBwDQbc2aNcv9HTx4cNbp5s2b1yzzWZnRAAAA6P4IIANAGvlkHnseqw4A0HXNnDnTbr/9duvbt6/tu+++WaedNGmSTZw4sd3aBqDz8xiAEwB6DALIANACnudZrLrwGpQAAHQGGoxPQeOlS5e6QfT69euXdfqTTz45Xu4iMQNZg/IB6Hm8pkaLLJpjJbZRRzcFANAOCCADQIGUeRxd8IPF6mtZdwCALhk81oB577//vt1yyy32i1/8Iuc8gwYNcjcAUOZx09wZZrEoKwMAeggG0QOAAinzOFa7zIKl5aw7AECXsmzZMttjjz3s3//+t912220usxgACqHMY4tGLFg1gBUHAD0EGcgAUCBlHocHrmoWLmbdAQC6jOrqahc8fvfdd+3OO++0Y445pqObBKArikUt1H+oBZYu7OiWAADaCRnIAFDogbO03EIDhlkgwKoDAHQutbW19tlnn9ns2bObBY932203mzp1qk2ZMoXgMYAWU+ZxqLKKNQgAPQgZyABQoGDVQAsQPQYAtJN7773XvvvuO3dffzWQ62WXXRZ//sILL4zfV3bx2LFjbfz48S5Q7Ntll13svffecwPn6TvsvvvuS3qNDTfc0N0AIJdQWQUrCQB6GALIAJBrxLwUxI4BAO1p8uTJ9uqrryY9dtFFF6UNIGei4LE8+eST7pZqwoQJBJABAADQvQPIX375pd1///32wgsv2FdffeUGCBk5cqTLtjjvvPNs6NCheXf7u/TSS+3BBx90Xf8036GHHupO0svLGTAL6EmU4TW/JtbRzQAA9HCvvPJK3tOOGTPGfX+lSvcYAAAA0KMCyMrMuOWWW2zvvfe2gw46yMrKyuztt9+2SZMmuS56b775pq299tpZlxGNRm3PPfd0GR5HHHGE7bDDDvbhhx/aNddc47oDKjgdDFI2GugRPM9+WBK12gYCyAAAAAAAoOfqNgHkcePG2bnnnmt9+vSJP3bCCSfY1ltvbSeeeKJdfPHF9vDDD2ddxt133+2Cx6eeeqrddNNN8cdXW201O/PMM10g+sgjj2zT9wGgc1DmcVWZWXkJF40AAAAAAEDP1W0iI5tvvnlS8Nh3yCGHuL8fffRRzmXcc8897u8ZZ5yR9PjJJ5/sMpr95wF0f8o87lUatIGV3eYwCQAAAAAAULBuHxmZNWuW+zt48OCs06ku3NSpU23YsGGudnIiBY833nhj9zyAnkGZx8P6hBgxDwAAAAAA9GjdpoRFJv4I1UcffXTW6RYtWuQG0Ft//fXTPr/qqqvaW2+9ZUuXLrXevXunnWbevHk2f/78pMemT5/e4rYD6DjKPA4EAmwCAAAAIA3G5gSAnqNbB5CvuOIKe/TRR22//faz8ePHZ51WwWMpKSlJ+3xpaWl8ukwBZA3YN3HixJVuN4BOII/gcbRuebs0BQAAAOhM1IM3Vp2cPAUA6L66bQD5j3/8o11wwQU2ZswYu//++3NmEpaXl7u/DQ0NaZ+vr69Pmi4d1Uo+8MADm2UgK4ANoHuJ1lRbrHpBRzcDAAAAaPfM4+iCHyxWvyIJCwDQ/XXLAPL111/vBsLbeeed7amnnsoa9PX169fPTTdz5sy0z+txZR5nyj6WQYMGuRuA7k2Zx15To1kw1NFNAQAAANqVyzyuqLJgae7f2QCA7qHbDaJ31VVXueDxHnvsYc8880xewWNRhvLmm29uP/zwg3333XdJz9XV1dkHH3xgW2yxRRu1GkBX4jKPQ2EL9xvS0U0BAAAA2pUyj4PlvSxYNZA1DwA9RLC71Tw+99xzba+99rInnngiXrc4leoYf/bZZzZ79uykx4844gj397rrrkt6/LbbbnNBZP95AD1cMGRFg0dYINwtO3EAAAAAGSnzODRgWD5DhgAAuoluE/249dZbXc3jwYMH2/7772+PPPJI0vOVlZXxWsTvvvuujR071g2sN2XKlPg0Rx99tN1zzz128803W3V1te2www724YcfusHxVEv58MMPb/f3BaDzUeZxoKi4o5sBAAAAtDtlHucaYwgA0L10mwDy1KlT3d+5c+faMccc0+z5kSNH5hzMLhQK2T/+8Q+79NJL7aGHHrIHHnjAhg4d6kpiXHzxxe55ACDzGAAAAD0VsWMA6Hm6TQBZmcSJ2cTZKJvY09CxaShT+eqrr3Y3AFjeEGUlAAAAAACAHqtb1UAGgNZUXRe1BctirFQAAAAAANBjdZsMZABo7czjxohnmSrX1Lz2hEWXLbbi1ddjxQMAAAAAgG6LDGQASEOZx+GQ2ZDeXGcDAAAAAAA9FwFkAEhDmccj+hVZOMQI0wAAAAAAoOcigAwAaSjzuDhM8BgAAAAAAPRsBJABII18Mo+9GAPsAQAAoGeK1i3v6CYAANoJAWQAaAEvGjWvroZ1BwAAgB4nWlNtseoFHd0MAEA7YXQoACiQF4lYbHm1UpBZdwAAAOhxmcdeU6NZMNTRTQEAtBMykAGgQJFFc1zwOFBSzroDAABAj+Iyj0NhC/cb0tFNAQC0EwLIAFCoWNSCZZUWKCpm3QEAAKBnCYasaPAIC4Tp0AwAPQUBZAAo9MBZNcACxaWsNwAAAPQ4yjwmkQIAehYCyABQoFBZBesMAAAAPRKZxwDQ8xBABoAsIlGP9QMAAAAAAHosAsgAkEFjxLM5SyOsHwAAAAAA0GMRQAaADJnHMxY1WTTK6gEAdKwrr7zSDj74YBs1apQFg0ELt3DgqtraWjv33HNttdVWs5KSEvf3vPPOc48DAAAAmTBsKgCkoczjQb3CNqAX19kAAB1LQd4+ffrYJptsYjU1NTZ//vyClxGNRm3PPfe0V1991Y444gjbYYcd7MMPP7RrrrnG3n33XXvhhRdccBoAAABIRQAZANJQ5vHQPiFbWBNg/QAAOtT06dNtzTXXdPfHjBnTogDy3Xff7YLHp556qt10003xx5WFfOaZZ9p9991nRx55ZKu2GwAAAN0DaQYAkIYyj6vKQqwbAECH84PHK+Oee+5xf88444ykx08++WQrKyuLPw8AAACkIgMZANKoKMkdPPY8j3UHAOj09H01depUGzZsmI0cOTLpOQWPN954Y/d8NvPmzWuW+azMaAA9lxdhsGkA6CkIIANAC7jgcT2DDgEAOr9Fixa5gfLWX3/9tM+vuuqq9tZbb9nSpUutd+/eaaeZNGmSTZw4sY1bCqCr8JoaLbJojpXYRh3dFABAOyCADAAFUuzYq11mXqSJdQcA6PQUPJaSkpK0z5eWlsanyxRAVqmLAw88sFkG8n777dfq7QXQ+TOPm+bOMItFO7opAIB2QgAZAAoUq57vsi4C4SLWHQCg0ysvL3d/Gxoa0j5fX1+fNF06gwYNcjcAUOZxuO8gC1YNYGUAQA9BABkAChSrr7VAUbF5QcYhBQB0fv369XPB4ZkzZ6Z9Xo8r8zhT9jEAJIlFLdR/qAWWLsx7xXwxp9EaIp5Nn9MY/7+of6ONHlLMygWALoDoBwAUeuAsLbdAeS/z6mutadZX1vD1x9b4/ResRwBApxQIBGzzzTe3H374wb777ruk5+rq6uyDDz6wLbbYosPaB6BrUeZxqLKqoHkUPH7/u3qbPm9FCbjPZq8IKAMAugYCyABQ6IGzaqD7MW5ezBpmfG4NX35gXlP6bsEAALQn1TH+7LPPbPbs2UmPH3HEEe7vddddl/T4bbfd5oLI/vMAkEuorKJFK6k4HLThfVd0gg6HAqxoAOhCKGEBALlGzEuh2HH8friIWsgAgDZ17733xjOH9dfzPLvsssviz1944YXx+++++66NHTvWxo8fb1OmTIk/fvTRR9s999xjN998s1VXV9sOO+xgH374oU2aNMnGjBljhx9+OFsRAAAAaRFABoAM9AN9fk2M9QMA6FCTJ0+2V199Nemxiy66KG0AOZNQKGT/+Mc/7NJLL7WHHnrIHnjgARs6dKidccYZdvHFF7vnAQAAgHQIIANAOp5nPyyJWm0DAWQAQMd65ZVX8p5W2cS6AJpOZWWlXX311e4GAAAA5IsayACQhjKPl9XHrLyEwyQAAAAAAOi5iIwAQBrKPO5VGrSBlRwmAQAAAABAz0VkBADSUObxsD6h5BHzMojWLWcdAgAAAHmqa4yyrgCgC6EGMgCkoczjQB7B41h9rVmkiXUIAACAHiVDufW8LFm+EjMDANodGcgAkE4ewWMv0mSx5dVmQUauBwAAQM+hwTpj1fMLnm9Zw4rMY06fAaBrIYAMAC3gNda7WyAQtHC/IaxDAAAA9JjM4+iCH1b0xCvA8oaozV8ac/cHVJCAAQBdCQFkACiQah7H6mrMAkEL9u5vgTDVgAAAANAzKPM4VrvMgqXlBc23YFnMwj/GjUOh3L39AACdB1EPAChQrHqBCx4HSsoIHgMAAKBHUeZxeOCqZuHiguYLhcwGVxGCAICuiKM3ABQqGLJgRdWKLGQAAACgB1HmcWjAMPNmfxN/rPH7L8xraoj/HygqseLho5PmG9I7bOGlZB4DQFdEABkACj1w9htisaWLWG8AAADocYJVAy2QMuC0gscNX35ggXCRG2i6ZNTGzeYLU7YCALosaiADQIGoeQwAAICeKiV2/P+Ph4usaNga7i8AoHshgAwAOUaLBgAAAJD/gNMAgO6FADIAZFBdF3WjRQMAAADILVpTvWLAaQBAt0INZADIkHncGPHcaNEAAAAAcmcee02NbsBpAED3QgYyAKShzONwaMVo0QAAAACyc5nHobAbcBoA0L0QQAaANJR5PKJfUV6jRXuRCOsQAAAAPVswZEWDR+Q14HQ06rVLkwAArYMAMgCkoczj4nB+wePIojmsQwAAAPRoyjwOFBXnNe2C5QxUDQBdSbcJIF955ZV28MEH26hRoywYDFo4j6ueqaZMmWKBQCDtbfPNN2+TdgPonPLKPI7FLLZ0oVmME2AAAAD0vJrHifLJPG76MfOY02cA6Fo6pLjnokWLrF+/fq26zPPOO8/69Oljm2yyidXU1Nj8+fNbvKzzzz/f1llnnaTH+vfv3wqtBNBdeNGoeQ115nkxC1YNsGUvP2J1H7wWf77P/qd0aPsAAACAthKtqV5R87gAkahns6tXlH7rU5E7WQMA0MMDyKuuuqodcMABdsIJJ9j222/fKsucPn26rbnmmu7+mDFjViqAvOuuu7plAECmshWx5dVKQbZgRZWFyiqMKsgAAADoKZnHXlOjq3lciDlLIxb5seNeWXFh8wIAemAJi1122cUefPBBF6RVpu8NN9zgspJXhh88bi3KYm5oaGjVZQLoHlzNYy9mgeJSC5aWd3RzAAAAgHbjMo9DYVfzuBDRqNnA3t2miiYA9CgdcvR+6qmn7LvvvrOJEye6IO0ZZ5xhq6yyih1++OH22mv/3wW8o+y7777Wq1cvKy0tdTWVr776aotEcucXzps3zz755JOkmzKjAXQzsagFyyotEC7q6JYAAAAA7SsYsqLBI/KqeZxoQK+g9Soh8xgAuqIOu/w3bNgwu/DCC+3rr7+25557zvbaay975JFHbOzYsbb22mvb9ddfbwsXLmzXNpWXl9tBBx1k1157rT399NP2pz/9yQYPHmznnHOO/eIXv7BYLJZ1/kmTJtn666+fdNtvv/3arf0A2odqHiv7GAAAAOhplHkcKCoueL4KgscA0GV1SA3kVLvttpu7qW7xWWedZffcc4/7e8EFF9i4ceNcAFfB2Lam4LFuiVSn+bDDDnMlNx5++GE75JBDMs5/8skn24EHHpj0mDKQCSID3Qs1jwEAANBTFZp5nM2t/1rS7LFTdu7TassHALSOTlGAqK6uzqZMmeICrQoeh8Nhd183BW033XRT++tf/9ohbQsEAjZhwgR3/5lnnsk67aBBg2y99dZLuq211lrt1FIAbUGjRQMAAADIf8BpAED30qEB5Pfff99l7Q4dOtSOOeYYmzlzpquLrPrIjz76qD3wwAOuxIUCyBdddFGHtXP11VeP1zgG0HM0Rjw3WjQAAACA3LymxhUDTgMAupUOKWGh2sJ33nmnCyArw3ePPfawk046yfbcc08LBpNj2hpc71e/+pUde+yx1lG++OIL93fIkMJGmQXQtTOPZyxqcqNFAwAAAMidedw0d4YbcBoA0L10SAayso5/+OEHO++881yGsUpDaBC91OCxb5111rEjjjii1V6/trbWPvvsM5s9e3bS4+kG7YtEIq6dQi1joOdQ5nEkumK0aAAAOoPHHnvMtt56a6uoqLC+ffvaPvvsY9OmTct7/o8++siN57HaaqtZaWmpjRgxwg0U/eabb7ZpuwH0DC7zOBpxA04DALqXDslAfuSRR2zfffd1tY7zseWWW7pbNvfee68rfSH663meXXbZZfHnL7zwwvj9d99918aOHWvjx493tZd9G2ywgf30pz91f1VWQ0FuDZ736aefupNtnWAD6BmUeTy0T8gW1gRyTutRJhkA0MYmT55sxx13nBtY+qqrrrL6+nq7+eabbdttt7U33njDnb9mo/PfHXbYwfr372/HH3+8DR8+3J0z//nPf7btt9/enn32WTeoNQC0WCxqof5DLbC0eWJWM5xAA0CX0iEB5OXLl7t6x8p+SOfbb7+11157zY488siCTqpfffXVpMcS6yYnBpAzOeyww9wyXnrpJauurnbZHRtuuKHdddddLtischsAegZlHleVKYAcyzqdLlbFque3W7sAAD3P4sWL7fTTT7dVV13VBYt79+7tHj/ooINs3XXXtdNOO82dv2Zz0003WUNDgz3//PMuCO1TD7vNNtvM7rjjDgLIAFaKMo9DlVUWyyOAvLg2+zk2AKBz6ZAA8tFHH+0yhjMFkN955x03TSEB5FdeeSXvaceMGeOCPqmuvfbavJcBoHurKAnlnEbHEW/ZYouV92qXNgEAeqYnn3zSli5d6oLIfvBYVIJi3Lhxdvfdd9v333/vsoozUXKEDBs2rNl4I1JeXt5m7QfQfWseJwqVVeSe58ff4fWNdOEDgK6kQ4p7pgveJmpqaspYDxkAOgN3HGust1hjvQVL+dENAGg7Sq4QlatI5T82derUrMvYfffd4z3utDyVanvrrbfsl7/8paunfOaZZ7ZJ2wF0T15T44qaxwXN5Nm8ZSsyj0uL6d0LAF1Jh2QgS6ZyEEuWLLG///3vrgYxAHRGih17tctc1kWwuNSCVQPNllDGAgDQNlT6TVTCIpX/mD9NJr/61a9s1qxZdsstt7iB+HwqZ6GA8qhRo7LOP2/ePJs/P/m7bvr06QW9DwDdg86Bm+bOcDWPCzG/JmbLG1YEkPuWkzAGAF1Jux21J06caKFQyN0UPD788MPj/yfeNLDHww8/7AatA4DOSDWPlXURCIct0KuvUR4dANCWamtr3d+SkpJmz5WWliZNk4l696lcxUYbbWTXXHONK4uhvwoM77HHHvHBqDOZNGmSCzYn3lQ/GUDP4zKPoxFX87gQtQ0xqyj5MQTBCTQAdCntloG88cYbu5rG6vZ9zz33uNGe11hjjaRpFFiurKx0WRGHHnpoezUNAAoSq6+1QFGxWXEpg2sCANqcX59Yg+Clqq+vT5omk/POO8+uu+46e//995MG0VNpi0033dTOOussl8SRycknn2wHHnhgswxkgshADxSLWqj/UAvkMVheovKSoA3owFKVSx67Ne3jffY/pd3bAgBdTbsFkPfdd193k1dffdXOOOMM22effdrr5QGg1ajmcaC8lwVqlrBWAQBtLrFMxTrrrJN3eYvE8UVuuOEGW3vttZOCx7LBBhu4x19++eWsbRg0aJC7AejevpjTaA2R5DGLSsIBGz2kOP6/Mo9DlVUWSwkgT68pt9jCsEWWVljR/KAVFTckzTuwMmi2hNrHANAVdcjlv2+++YbgMYBO6dZ/LbFHpi6zVz/P3BVYNY8z1XEHAKC1bbnllu6vBr1L5T+2xRZbZJx/wYIF1tjYaNFo+nqlkUjE3QBAweMPZjTYJ7Ma3U33UwPKobKKtCuqMRawD+cX2WfLKux/C0L2wie1yfNy/gwAXRaV6wEg14h5KTj3BQC0J5WJ6NWrl91xxx22dOnS+OMzZsywRx55xMaMGWPDhw+P10L+7LPPbPbs2fHpBg8ebAMGDLDPP//c3n777WYB6C+++MK22mqrdnxHADqzolDA1hhY5G6FpkwUBz0bUVpvJSHPmlICzwCArqtdSlisvvrqbuAOncwWFRU1q32cjrL7vvrqq/ZoHgCkpZrtGi0aAICO1LdvXzfg3UknnWTbbbednXjiia4e8s033+zOmW+88cb4tO+++66NHTvWxo8fb1OmTHGP6TxcA1qfcsoptuuuu7rljBo1yr788ku77bbbrLi42C699NIOfIcAOqPGiGdzlkZsI2s+gGcmMc/sh8UN1lAasPJy8tUAoLtolwDyyJEj3cmt3+V7xIgRdP8G0OmDxz8sibrRogEA6GgKGvfv398Fks8++2wX9NWg1JdffrltuOGGOefXIHjDhg1zQec777zTli1b5pb3s5/9zC688ELbaKON2uV9AOg6weMZi5osQ+WbjB335i9ebhUNZv2LPStXzWMAQLfQLgHkV155Jev/ANDZ1DaYLauPudGiAQDoDMaNG+du2aichS6CZiqFoRsAZBOJrggeR6JmA3rlfy7s1Syx5XV9bUiJ2dBKz2ZS9w0Aug0iIwCQRlPUs16lwRWjRQMAAAA9hMpWKHg8tE/IKkpCec8Xa6y3irKQDetbwpghANDNdEhkRDXbFi1alPTYwoULXe210047zdVuA4COHjxkWJ9QXiPmReuWt0ubAAAAgLYW/TF4XFWWf/BYgsWlNrBfhQXyiDLUNRZQGwMA0DNKWKSrwaYg8ccffxwPKG+99dbxQfP+9Kc/2RtvvGGbb755RzQPAKy8ZMVgnrnE6mvNIk2sMQAAAHQLKluRT/A4tVpOoLKPBXOfPjtLlqcvtQMA6Jw6JANZweG99tor/v8jjzzigscaBfqdd96xoUOH2rXXXtsRTQMAJ5/gsRdpstjyarNgYdkZAAAAQGeVT9kK1VqPVc9PeiyfksfLGlZkHnP6DABdS4cEkGfPnm2rr756/P/nn3/e1llnHTe69BZbbGHHH3+8vfXWWx3RNADIi9dY726BQNDC/Yaw1gAAANAjKPM4uuCHFT3xCrC8IWrzl8bc/QEVJGAAQFfSIQHkqIoqJXj99dfdiNG+YcOG2bx58zqgZQBgedU8jtXVmAq8BXv3t0C4Q6oBAQAAAO1Omcex2mUWLC0vaL4Fy2IW/jFuHArlWesCANBzA8gjR450ZSzko48+shkzZiQFkJWh3Lt3745oGgDkFKte4ILHgZIygscAAADoUZR5HCzvZcGqgQXNFwqZDa0i8QIAuqIOOXofcsghNmHCBFuwYIF98skn1qdPH9t9993jz3/wwQe25pprdkTTACC3YMiCFVUrspABAACAHkSZx6EBw8yb/U1B8w3pHbbwUjKPAaAr6pAM5HPOOceOPfZYe/vtty0UCtk999wTzzhesmSJPf3007bTTjt1RNMAICfVPA4ohQIAAADoYZR5nM+A06p5nChM2QoA6LI6JAO5uLjY7rjjDndLpUDynDlzrLy8sHpKANBeqHkMAACAHjNiXoo8Yse2tMFsQd2KAfMAAF1fpytAFAwGraqqqqObAQBpMycAAACAnsDzPJtfU3gQeMnyiC0qDlqouE2aBQDoaQHk6dOn2xdffGELFy50X06pjjzyyA5pFwBIdV3UjRYNAAAA9CT6ff7DkqjVNhR2LryspsFqqqNW3n9FzWMAQPfQIUf0+fPn2/jx4+355593/6cLHqumEgFkAB2lMeLZ7CVRN1o0AAAA0GP8GDxeVh+z8pL8h02KNdTbgup6Gxo0G947ZnOpeQwA3UaHBJB/85vfuODxCSecYLvuuqv179+/I5oBABnVNnoWDpE5AQAAgJ5FZSuqysx6lQatuIBkiljNEgsFh9mIvkUFzQcA6Pw6JID83HPP2fHHH2+33XZbR7w8AOQUDJiN6FdkMxdHck7rRXJPAwAAAHQFKluxat+wDesTsm8WNO8tnFEwaEMGlFuxVeecNBotYLkAgJ4ZQI5EIrbZZpt1xEsDQF4qSwJWHA7kFTyOLJrDWgUAAEC3oLIVCh6rrGR0yVxrsgZraFxRC7lp1lcWWTzPioat0Wy+UO/+VlwUsuiixRYoKrZoOGhNFnXzRhaXmtmQ+LQLljNQNQB0JR0SQN5yyy3ts88+64iXBoC8BJWCnIMXi1ls6UIL9e7HWgUAAEC3MLAy6ILHTiRijd9/YY01De7fpjkzzMIrwgjRuuVJ8wX8wUNiUWua+71FSoPW1LjcGpYsMa/Ppivm/zHzOEb8GAC6lA4JIF955ZW255572kEHHWRbbbVVRzQBAFaKF42a11BnnhezYNUAi9Unn0ADAAAAXZIfPPb/DYWtaNgq7n5kwQ+mEHC0ptpi1QsyLyIUslDVAAv372OBhhXnyZGoZ7OrV5R+61ORO1mjNd36ryVW/8PotM+V/muJnbJzn3ZtDwB0NR0SQFbt4+HDh9t2221n22yzja2xxhoW8q9W/khXPCdPntwRzQOAnGUrYsurlYJswYoqC5VVGFWQAQAA0BPE6mstunC2WbCwkfLmLI1Y5MfM4zJG2QOALqVDAshTpkyJ33/jjTfcLRUBZACdlat57MUsUFxqwdLyjm4OAAAA0C6i9XUrEilCYQv3+/+axvkMOB2Nmg3sHWzjFgIA2kKHHL1jqhua4xbVtwsAdEaxqAXLKi0QLurolgAAAADtQmUrvOVLLBAIWtHgERb4sRZyvgNOD+gVtF4lhWUtAwA6By7/AUChB86qAS77GAAAAOgpwWNXtiIQtGDv/hYoKs45T2NT1CIL58RHzKsgeAwAXVaHBpCXL19uL774ot1///02d+7cjmwKAORNNY9zWfLYre4GAAAAdGWxhvoVweNQ2EIKHueRedzQ5NmcBbUreu5VDWiXdgIAumEA+c9//rOtuuqqtttuu9mRRx5pn3zyiXt83rx5VlJSYnfccUdHNQ0A4jRaNAAAANAT1TSZxWqWuOBxvmUrGps8m7ksYNFYzEJV/fNKvgAAdG4dEkB+8skn7aSTTrIddtjB7rzzTvO8/w/QDBo0yPbYYw83DQB0pMaI50aLBgAAAHqa6rqoLawNmAV/rHmcZ9mK75cFLOIFbEBVqQXLK9ulrQCAbhhAvvrqq23HHXd0QeJ999232fObb765TZs2rSOaBgBOLObZjEVNbrRoAAAAoKcFj2cviVooaCvKVuQRPPaiUVe2QsHjIeUx61VZ0i5tBQB00wDyhx9+aPvvv3/G54cNG0ZNZAAdqqbBs0h0xWjRAAAAQE+xvGFF8DgcMhtc4VkgFMprvujSha5sxZByz6rKAm3eTgBA+8ldwKgDzJkzx8rKyjq6GQB6sJhnNrRPyP73Q9S+mtcUfzywKGgjU6ZNqMIDAAAAdGkLlsVseP+gjehXZN8tLGDGWMyVraiqz2NaTqABoEvpkNS69dZbz1555ZWMzz/xxBO2ySabtGubAPRct/5rSfzmKy8O2Muf1tnUb+rtoXeX2SezGu2DGQ3WmFLSQjXcY9Xz27/RAIAe57HHHrOtt97aKioqrG/fvrbPPvsUXPbtv//9rx144IE2ZMgQN3D1Kqus4pbz7bfftlm7AXQtSjhW8Lg4XFgWcbCyT95lKxbXxlrYOgBAjwkgH3fccS5IfNNNN1lT04rMvkAgYIsXL7bjjz/endiecMIJHdE0AHAST5hV+22NgUVWFAo0Cx57yxZbrL6WtQYAaFOTJ0+2Aw44wJYvX25XXXWVXXDBBa4s3Lbbbmsff/xxXst44IEHbMstt7RvvvnGfve739ltt91mp556qhUVFdmiRYvYggCcIb3DeQWPvUjyYNPBktLc8/yYeVzfSBc+AOhKOqSEhYLEb7zxhv32t7+1888/3wWPdUJcXV3tvlD0/MEHH9wRTQOAvLiT38Z6izXWW7jfYIvVL2fNAQDahJIsTj/9dFt11VXdOXTv3r3d4wcddJCtu+66dtppp9lLL72UdRlffPGFHXPMMXbYYYfZlClTLBikxj+A9MIpSRPpeE2NFlk0x0pso/xXo+fZvGUrMo9Li6mRDABdSYedOerE9fHHH7c99tjD1llnHdeNbu+997a//e1vdvvtt3dUswAgJ8WOvdplLusiWFxqwaqBrDUAQJt58sknbenSpa4Xnx88lhEjRti4cePs5Zdftu+//z7rMq655hqLRCJ2/fXXu+BxbW2tNTY2stUAFEznwE1zZ5jFUmq75TC/JmbLG1YEkPuWcxELALqSDh1Eb99993U3AOhKVPNYWReBcNgCvfpagAQKAEAbeuedd9xflatIpcfuvvtumzp1qg0fPjzjMv7+97/b2muvbW+//badffbZ9umnn7pAskpa/OEPf7AxY8ZkbcO8efNs/vzkmv/Tp09v8XsC0HWDx7GlC836D7Fg1YD85vmxWkVtQ8wqSn4MHHMCDQBdSrtf9qupqXF127bffnsbNGiQG7xDf3fYYQeXGaG6bgDQKf149quax4GiYrPiUleCBwCAtjRz5kz3VyUsUvmP+dOkozJxs2fPth9++MF+8Ytf2E477eQG5FPg+H//+5/tuuuu9uqrr2Ztw6RJk2z99ddPuu23334r/d4AdB1KoIguXWieF7NQ/6EWKqvIPU/CgNPlJUEb1IvMYwDoito1A/mzzz5zJSvUxU5fJL169XLBY3XJ+/e//+1uGszjueees9GjR7dn0wAgKx2z1O1udC+zYGm5Bcp7WaBmCWsNANDmVG5ClHiRqrS0NGmadJYtW+b+aqC88847z6644or4c5tttpntsssu7vE333wz4zJOPvlkO/DAA5tlIBNEBnpO8NiVrfBiFqyoslBl1YpM5CxinllsyYL4gNMDK4NmS0i+AICuqN0u/zU1NbmB8mbNmmVnnXWWffXVVy4bQsFk/dX/elz/azpNX4grr7zSDbw3atQo1x0vHG5ZbFwn3+eee66tttpq7iRdf3VCne2kHED3Dx7P+GaWLZs31yLzZ1ks5pF5DABoN+Xl5e5vQ0NDs+fq6+uTpkmnrKwsfv/oo49Oem7nnXd2tZRVJiPb+a6SPtZbb72k21prrdWi9wOga/Gi0RXB42jEvg6vZp/HVrFPFobtn3P727Nfhe3jmQ32yfygfbO8zObVhtw8sZjZ/EXLXfBYyRdOlp57C2uiNndpxN20vC/mUKMdAHpkAFmD46nW2uTJk12wd/XVV096Xv+rtMUdd9xhn3zyietWVwgFef/5z3+62m+DBw9uURuj0ajtueeerh0qqXHrrbe6gf1UWkN/Y/oWBNDjgsf1TZ4tq41YeP7X1jjnO7NYpKObBQDoQbKVqchW3sLXr18/q6hY0dV86NChzZ7XYzrPXbKEnjUAkjXFzJWtUPBYZSuiReU2bXk/+3Rh2P63tMI+XRCyT2Y1ur9f1pRbJOaSlG12jWfL66IueJzPgNORmGczFkbsy7lN9vcPa6wh8mPhZABAzwogP/HEE7bhhhvakUcemXW6o446yk33+OOPF7R8daFbvHixvfTSS/aTn/ykRW3UACSq/3bqqafaPffc40a6vvnmm11AWcu97777WrRcAF04eNy44oS2V7Fng6pKLBjq0LFHAQA9kAa6k7feeqvZc/5jW2yxRcb5Va/fX4Z6+6XSY+q9p0AzAPgaI57NXR5w6cSu5nFllXu8KBiz1aqiVhT0LBz0bI2BRbZan5j7X2HfH2rMahqDVlEWsmCfAXmPl6egcVVZ0FbtW8RGAICeGkD+8MMP7Wc/+1le02q6Dz74oKDlr7nmmrayFDSWM844o1nNN3X9858H0DOCx8vqPRc8DgcDNrTSswBjfgAAOoDqDGvsEPXU09ghvhkzZtgjjzxiY8aMcb3wRGUoNO6IBs1LNH78ePdXPexSkzw0uJ7qIPv1lAFAweMZi5osGjMLVvaJB4+zUebx4up6q2kKWmVxzAb2qyio7FswYC6AHA5RJxkAOpt2S6WbM2dOs7IVmWg6Td/ewaKpU6fasGHDbOTIkUnPKXi88cYbu+ezmTdvns2fv2KE2cTMaABdT22DWWnRiuBxaVHWkm0AALSpvn37upJqJ510km233XZ24oknunrI6imn4MyNN94Yn/bdd9+1sWPHuoDxlClT4o8fccQRdv/997sAss5ZNY3GILnlllusqqrKrrvuOrYiACcSXRE8jkTN+pd7FvRyX1zyPLMlyyNWH4paZVHMhlYGbG6B58+VJQELKYoMAOi5AeSamhqrrKzMa1rVaNP07UmjUitjY/3110/7vOrKqYugsj569+6ddppJkybZxIkT27ilANpDU9Sz3mVBKy1e0fUXAICOpKBx//79XSD57LPPtuLiYtt+++3t8ssvd+XfctEg00899ZQrzaaybMo81jmtspsvvfRSGz16dLu8DwCd35ylERvUK2xD+4RsnkqjN+ZOxppdE7D6iJKvQjZMyRct6LkXJHgMAJ1WuwWQCx2ATl9C7ckfdbqkpCTt836XPk2XKYCsUhcHHnhgswxknZgD6FqKQgHrVRqwJXW5g8fRuuXt0iYAQM82btw4d8tG5SwynUfrfHbChAnuBgCZRKPmgsdVZSGbl2M16XDzw5KoLWsMWGnYrG9VqQXqc6/busYoGwAAupB2HQ3qySeftG+//TbndIXWP24N5eXl7q+6A6ZTX1+fNF06gwYNcjcAXV95SX6Zx7H6WrNIU7u0CQAAAGhrA3oFXfA4n5rH1Q0BW1YfcwNO96kIW7799pYsb9+EMQBAFwoga5AP3fLR3l3GNeq0gsMzZ85M+7weV+ZxpuxjAN1LPscgL9JkseXVFuw7uF3aBAAAALS1ipLcwWN1MFbN40iReu0FbaDn2Vd5lK1Y1rAi8ziY+yUAAD0xgPzyyy9bZw8Wbb755vbaa6/Zd999lzSQXl1dncuK3nbbbTu0jQA6D6+x3t0CgaCF+w2xxtqlHd0kAAAAoM0p83jW3KWu5nFl2LNhfUIWyaNsxfKGqM1fuqK05YAKIsgA0JW0WwB5xx13tM5CdYxnzJjhRpweOnRo0ujUCiBrFOqbbrop/vhtt93mgsh6HgBUtiJWV+NGBwn27m+BcLt25gAAAAA6hGoeL6jzrO/yiJWGw1ZV4uXde3jBspiFf4wbh0IMUg0AXUm3iXrce++9LnNY9FeDh1x22WXx5y+88ML4/XfffdfGjh1r48ePtylTpsQfP/roo+2ee+6xm2++2aqrq22HHXawDz/80CZNmuQGJDn88MPb+V0B6GyijQ0Wi1a74HGgpIzgMQAAAHoE/caO1S212qY+NqIibH0iYcsnduwGnK5U0NhscFW3CUEAQI/SbY7ekydPtldffTXpsYsuuihtADmTUChk//jHP+zSSy+1hx56yB544AGXoXzGGWfYxRdf7J4H0HMtq4ua1S2zQEnQAhVVK7KQAQAAgB4QPI4u+MGsqdHKizxbZXBv+25Zbc75YrU1FqteYDbQbEjvsIWX5o44R6IMsAcAnU23CSC/8soreU+rbGJ9AaZTWVlpV199tbsBgG9pg9nCmphZeEXZCq9mCSsHAAAA3Z5+Oit4HKtdZlZUbAPCAQvmM2BeTYNFGxfGR8wL51G2IhrzbM7SiG1kJdZe6j+dakuqv2j2eJ/9T2m3NgBAZ5fHYR8AeramiGeza4IWCpoFK6ooWwEAAIAeQWlXSpxQ8DhY3suCZb1VyS2n6jrPFlTXu+CxBpzORyzmWXVdzKLRlW83AKB1EUAGgBzB4/qIp8RjG1IVtgClbAAAANADqNfugtqAxRrrXfA4NGBYXjWPq+vM5tQq+SJo4f5D8k6+qGnwLOaZDehFmAIAOhuOzACQQX3TiuCxDpTDe8esKMxo0QAAAOgZweMflkSttsksWFz6Y/A497lwbV2jzakNWDjg2ZAB5QX13FPwuLIkaBUljD0EAJ1Nt6mBDACtqTHiWTQWc8Hj0uKAFXMeCwAAgJ7gx+DxsvqYlReZBUr7uODx7R9V2A+LVrOFTaX2+Vdl1teSB9GrrY/a0liTDQt4tmovzxYV6QQ6kvfLlhcHrLSIhA0A6IzIQAaANGobPQsGzMqKAxbSHQAAAKAHmF8Tc8HjXqVBG1Du5VW2QgNOq+6xTpuH9/KspAWB4GJ6+wFAp0UAGQDSHRwDZlVlQQvmETz2IvlnVgAAAACdWW3DiuDxsD4hyycMXF0XdQNOB4NmA/qWWnEeweNoVMPzAQC6CgLIAJBGZUl+mccKHkcWzWEdAgAAoFsoL/kxeJxH6nFdk9nsJVE34HT/ipCF8xxwesHyaCu0FADQXgggA0C6g2M+weNYzGJLF5rFOAEGAABA9zCwMpjfgHn1UatuCFo4tGLA6XAeJSiafsw85vQZALoWAsgA0AJeNGpeQ515XsyCVQNYhwAAAOge8sk8bmiK1zwe0a8orwGnI1HPZlevKP3Wp4IxRgCgKyGADAAFUtmK2PJqpSBbsKLKQmUVrEMAAAD0CA0Rz2qWN7max/1KY3kPfjdnacQiP3bcK8sn4gwA6DTCHd0AAOgq5jcUW7ixwqJLF1ksMtjCRSW2Tml50jRf1fWyxtj/X5vrP6fRRg8p7oDWAgAAAK0sGrW6SNBKygLWv0w1jy3vAaejUbOBvclhA4CuiAAygB7p1n8tKWj6p74osm8X9rKaurVs89Ii6211tmnow2bTKXj88fK+VhSIWZMXtG0ijDANAACAri/W2GBeU6MFzbOqymILB2rzH3C6j9mAXkGrqM0n4sz5MwB0Nlz+A4A8RGNmtY2eBcyzjXottT5FmQfOU/B4ZOlyC1uMdQsAAIAuL1pTbV7tMlcfubzYLJxH6nFjU9QiC+fER8yrKMk9j+d5Nr+Gc2gA6GzIQAaAHKIxz5ZGA+Z5ASsOe1ZVFrDF9bkTJxY2lbBuAQAA0KVEl8y1pkijux9ZstCaaudYtKzELLi6BYpKLPxjHkWsbrkFgmFrmh21yIIfLFan8UH6uOcamjybs6DW1u0fzXvAaQWPl9V7tmzhQmuaVW8Njf8fSNbrFg8f3RZvFwCQBwLIAJBFLOZZfaNnFWGz0mKzUB4JEQoez2kss7oYh1gAAAB0MZGINc2cbhYKW/WcWouFlpiFVnGDR9vShWZ+RzzPs8jSRdY0e6FFF80184a5hxubPJu5LGDRipiFqvpbKNSQ18vWNpiVFnlWXhqxhhlfWGPNivm8SJOVjNq4zd4uACA3SlgAQJbM47pGzxWiqCzyLBzKb4RpZR7XRIusLLhiwBAAAACgSwmFraaojy1sDFkgELSiwSMsEGpegiIQDFp4wFCzH5+LRKP2/bKARbyADagqtWB5Zd4v2RT1rDgcsAHlngXDYSsatoa7BcJFrfrWAACFIz0OADJkHlfXxVzwuDQcsJICjpbKPB4WqrOiQOY6yQAAAEBntWR5xOZHak1h4UBFlQWKinPOE4l6tmRxvfXxAjakPGa1lSrnln9CRVEoYL1KA5ZfygYAoD2RgQwAadQ0eBbzVgSPi8KFncYq83hIcZ3GGAEAAAC6lJomsznVUQuFgja4wkubeZxKZSsW1gXc+fOQ8hVjhhSqvERj9HECDQCdERnIAJCGTn4rS4JWmzB4R7aax4n6FzW0KHi85LFb3d+lM2Znfb7P/qewzQAAANAmFtYGbFDQbOTQXvZdbXXO6RsaIq5shc6a+1cWWVU+58GpJ9DKdCZ4DACdFhnIAJBGeXHASosCeY0WHauen/QY574AAADoqkJBsxH9i6wkjxpuqlv83exlruZxVYln5WW5S13I4to8RqYGAHQaBJABIA0N4JGT55m3bLHF6mtZhwCANvfYY4/Z1ltvbRUVFda3b1/bZ599bNq0aS1a1gcffGBFRUUu4+++++5r9bYC6LpUtqK4KJhXzeNFdUGLRmOubEV5nskXUt/YPAMZANB5EUAGgBaWuLBIo8Ua6y1YWs46BAC0qcmTJ9sBBxxgy5cvt6uuusouuOAC+/DDD23bbbe1jz/+uKBlRSIRO/bYY620tLTN2gug68ojdmyRSNTVPFY8eOiAcqsqy2PBnmfzlq3IPC4tzr/eW7Rued7TAgDaBgFkAChQLGa2sD5kXjRqweJSC1YNZB0CANrM4sWL7fTTT7dVV13V3njjDfv1r39tZ555pr3++usWi8XstNNOK2h51157rX355Zd2zjnntFmbAXRfkZhZdU2jq3ncqzRmffKKHpvNr4nZ8oYVAeS+5fmFIqI11RarXrBS7QUArDwCyABQAC9mNrvGs9poyI1IHejVl5rHAIA29eSTT9rSpUvtuOOOs969e8cfHzFihI0bN85efvll+/777/Na1hdffGETJ060yy+/3AWkAaAgMc9qG5VQ4VlViVlFXmUrVvytbYhZRUkw70FDFDyOLpxtFgyxkQCggxFABoB8eWYN0YDVNAatPBQ1CxczWjQAoM2988477q/KVaTyH5s6dWpetUdVumKjjTayU045pQ1aCqA7U+87r6nBYhawyooiKy+yggacLi8J2qBe+YUgYg31K4LHobCF+w1Z2aYDAFZS7mFVAQAuc6K+ybOIZ1ZZHFtRG255/rXbAABoqZkzZ7q/6TKG/cf8abKZNGmSC0b/5z//sWCwsDySefPm2fz5K4JAvunTpxe0DABdl9fUaLHlDe6kuCwcs7KSIrPG3GOGxJYsiA84PbAyaLYk9/lzTZNZrGaJWf8KKxo8wiLzcx/fAABtiwAyAOSROVHTFLAmJR0HzIZWBmxGde7Vtjxa+CE2Wr3QoktX1Hlr/P4La+xdZMXDR7ONAKAHq61dEXwpKSlp9pw/EJ4/TSYzZsyw8847z9VO3mCDDQpug4LPKn0BoGeZ31RqxV6Fhb5cZPPrBlp1sJdFvKK8xgyZv2i5je5V+/8DTieUrVhYE7Gv5jXZ3KUR9/+i5VFbXh+zsqKgLWwMmAWDLngcKCrO+jpfzGm0BmV4JCgJB2z0kOzzrYwlj92a9vE++9OzA0D3RQAZAHIEj5V5XBo0KwqZFXuezmdzWhopskVNzX/o5+LFIhaZ/a273/jdZ+aNXovtAwA9XHn5iuBLQ0NDs+fq6+uTpsnkxBNPtMGDB9vFF1/cojacfPLJduCBBzbLQN5vv/1atDwAXUNDJGBvL+tr3wRKbXasty2P1VtQdd3yGDNkeXHUggPLLVg2MG2A+fM5DTZ/WdT9v6Q25uoq1zTEbHCpWah3/5zB4xXt8+zvH9ZYwAI2oFfQisNB23hE4efgAIDsCCADQLbgcaNZxPNMvfRKiwLmrUiSyJl53BgLWSiQ/eQ6k0DJiiBAIMwhGgCQXKZinXXWybu8he/xxx+35557zm6//fakUhcqSyFz5851weBhw4ZlDEQPGjTI3QD0HA0NEVtYF7Cg59kmq4SsZkHIvlvuZQ0f67kfasyNGVJRFbJgnwEWaFycdtqiUMD6lq8YIG9RTdTqI571DZgNrvAsEMl/4DwFjzddrcSqykL29fymgt8nACA3BtEDgAzB42X1nkVinoWDAass8nR2mhdlHocDMRtYtCIrrGDhPEYkAQD0GFtuuaX7+9ZbbzV7zn9siy22yDj/d999F89CHjVqVPx2zjnnuMdV1kL/v/baa230DgB0NY1NMftu9jKLmVmv0pj1qSrLa8yQxdX1VtMUdGOGDOxXkdeA0+rtp+CxghNVZcEVY40UQJnHCh4DANoO6W0AkEZtgzKOVwSPS4uSSrblpMzjVUpqbXZj7hNtAAByUZmI0047ze644w777W9/a717947XNX7kkUdszJgxNnz48BXfX7W17vGqqiobOnSoe2yvvfZKm6H8yiuv2K233mq/+c1vbPvtt7dNNtmEjQHAmmJmMxY2mVcWs6oSs/Ki3CfCKluxpN6zxkDUKotibsyQuXmcPyt4rLIVihmXFgcsFCx8kOqKEoLHANDWCCADQBpNUc96lwWttFjB48JOZJV5XBxUvgYAACuvb9++ds0119hJJ51k2223ncskVj3km2++2X1H3XjjjfFp3333XRs7dqyNHz/epkyZ4h5ba6213C1VTU1NPHt53LhxbCoAztzlAauKma06oNzmL1uWc62onrHKVtRHAlZRHLJhSr7II4u4tjG2IngcMCsrDliwBcFjAED7oIQFAGSoydarNJBX8Dhatzx5XoLHAIBWpqCxso1Vo/jss8+23//+97bBBhvYG2+8YRtttBHrG0CricbMhlSF8ipbEfM8mzV3qStbURr2rG9VaV7B4/pIzKprVwSPVbaC4DEAdG5kIANAGuUl+WUex+przSIM1gEAaHvKEs6VKaxyFqrjn4+jjjrK3QAgUf9yz/pEcocKdKhZUm+2bHnEla3oU6Th7PKzrM6zskDAqspaVrYCANC+yEAGgDTyKlsRjVhsebVZkLprAAAA6B4q8xjPWWUrFDxuiASsV0XYhlXmN2bIsoao+xsMmvWvDOYVPPYikbzaDQBoOwSQAaAFljeZeU2NFggELdxvCOsQAAAAPYIGzFu2vMHqowErCXu2yuDeeZWtWN4QtflLV4wTUlUWsnAoj+BxU6NFFs1pjWYDAFYCAWQAKFB1nWcLGjU6SMCCvftbINw21YDy7IEMAAAAtAudnyqJuLEpZqUhz/qUrsgmzseCZTEL/9hxL5zHPAoeN82dYRaLFtZAAECrI4AMAAVoipnNqQ1aOGAWKC5ts+CxxGoWs20AAADQKahsRX3ULOIFrLgouCJ4XMCA06GQ2dCq/M6dvWh0RfA4GrFg1YD85vE8m1+zIsMZANC6CCADQJ4iUc8aIwELBzwbWNqUX6G3lvgxc8JrqGfbAAAAoFMEj1W2IhJdcS7cq6Ikr1PhWG2NxaoXuPtDeoetKI+yFUrYiC5d6ILHof5DLVRWkVfw+IclUattIIAMAG2h7VLnAKAbaYiY1TeaG1l61V6eza7J5+S3hdfoGlcEjgMlpS2bHwAAAGglMc+zWXOXWmNTbwuHPCsJZi5b8f78IpsbGenuL1wWsk+CRdbf28AWR4ttkdXZjoOyv1Y05tnc5QEbFYutCB5XVllMweQEt/5rSfz+3KURW3dosQseL6uPWbkalzJNPib/MDrp/2OHfVHQ/ADQ3RFABoAcmiKe1VjAAgHPSsMxKynKHTxujAVtflPLAsD+SNPByr5sGwAAAHQYdYxbUq/s44grW1Eaiq7IqMihvsmz2qaIWa+gBYsr83otBY+r62JWVaTz4D4ueJwPla2oKjPrVRq04h9rLAMAWhclLAAgR/C4PuJZMGBWXhywoO7kkXk8q6Hcol7LSlz4dZXbqkIGAAAAkE/ZCgWPGyIB61URzrtsRX2T2fKmoDtvDpZV5jXKXizmWX2jZzHPrH+5Z8ECeuKpbIWCx8P6hDiBBoA2QgAZALJkTrjgsZn1LvYskEfwWJR5HPGC1q+ooWXrtpjSFQAAAOg4Xsxc2Yr6aMBKwp6tMrh3PnFga2qK2fKmgAXNs8oypRIH88o8rlPw2MwqS4JWWVRYW1W2QsHjANkXANBmKGEBAGk0RjyLxmIueFxaHLBQAZfblHk8uLjOFkeK4499MafRGiIrBseTknDARg/5/+eT/Hjy+1VNuYXnB62ouMFNn6NkHAAAALDSdMb6w+IGWx4qsdKQZ1WlecWBrbbJs4bGiPU2z3qVmNWHNVMsr7IVmqo0HLDSPErFpRpYGSR4DABtrNtlID/22GO29dZbW0VFhfXt29f22WcfmzZtWl7zTpkyxX3xpLttvvnmbd52AJ1HbeOKshVlLnhc2ImsMo97h5uSHlPw+IMZDfbJrEb3NzGYnMkXNeX26YJQ3tMDAAAAK2tBbcCWNZgrW9FHweM8Mnur68yqG1b8du5dYhbOoxZxJPpj8NhbETwuCrewfhuZxwDQ5rpVBvLkyZPtuOOOs/XXX9+uuuoqq6+vt5tvvtm23XZbe+ONN2yDDTbIaznnn3++rbPOOkmP9e/fv41aDaAzUsy4qixoNQ3ZsyYSB73zVYSS//cVhQK2xsAi+3p+cnA5k6KAZ6v1idn3IYohAwAAoH3UNpkNLDFXtuKbufU5p19SXWdzalW2wqysNGyh3KfPFomZLaxZETxW2YraxjxmAgB0mG4TQF68eLGdfvrptuqqq7pgce/evd3jBx10kK277rp22mmn2UsvvZTXsnbddVcbM2ZMG7cYQGdWWZJf5rGCx5FFcwofzhoAAADohMqLzIb1LcmrbMXyJs9mL6i1cMCz/mWezdP5cx6x4Oq6qPXzPBc8bknZCgBA++o2JSyefPJJW7p0qctA9oPHMmLECBs3bpy9/PLL9v333+e9vJqaGmtoaOEAWAC6PI0anZPnWWzpQrNYNO/lep5n82vIsAAAAEDnNKBcg0fnl6m8rD5ooVDQhvfyLJxHr7mm6IpEiljMrKo8v+AxuRcA0PG6TQD5nXfecX9VriKV/9jUqVPzWta+++5rvXr1stLSUhs1apRdffXVFknpog6gZ1MvO6+x3jwvZsGqAfnN5Hn2w5Ko1eZRFiPR8ob8A9QAAADAysgnH7iuocmqG1aUHx45tJcV5xEIjsU8m1294nd1r7KAlRcH80q+iFXPz6vdAIC2021KWMycOdP9VQmLVP5j/jSZlJeXu5IXu+yyiw0dOtRmzZpl9957r51zzjn2+uuvuyznYJZ+PPPmzbP585O/3KZPn97CdwSgs2po8mx+fbH9xPMsWFFlobIKy+cSkzKPq8rMykvyv3a3tMFsQR0ZywAAAOgcmmKe1Sxvsl4aPLosZiUlYcun725Ng2eRHwfXKw3nFzyOLvjBYvW1K99oAMBK6TYB5NraFV8qJSUlzZ5TJnHiNJkoeKxbohNOOMEOO+wwe/DBB+3hhx+2Qw45JOP8kyZNsokTJ7bwHQDoCpQ5MXNZwCKeWaCo2IKl5XnPq8zjVfuGrTiPUan9zOPZNUELFbe8vQAAAEBraYzqFnTl3lTzOJ+yFa5ehf54ZgN755dIobIVLnhcu6yg82167gFA2+g2JSyUPSzp6hbX19cnTVOIQCBgEyZMcPefeeaZrNOefPLJNm3atKTbE088UfBrAuicvJhn9ZGgRbyADShuMgsVdg1OmcfD+oRW9PXLw5LamCk5Y0jvbnOtDwAAAF2UylY0RAOuxEVVZXHeweNYXY27W14csF4luTMpVCXZq1myInhc3suCVQPzap8G5luwjJ57ANAWuk1UIrFMxTrrrJN3eYt8rL766vESFdkMGjTI3QB0P9GYWW2j505oh5THbHF90HL11Usd8GNgZdBdlMop0uT+qGLO8N4xm5vPyTkAAADQRpZU11nN8lIL2v+xdydgcpVl/vfvc05tvaezJyTBDWRHRJBlwCCIyKsskqCjIsoiGMeBAUQZdDAqjhhRRjYR0KAwqBnRuPsfZVERCSpbGJCdJGTv9FZd61ne634qVale61Snt+r+fq6rruo+dU7V6apO56lf3c/9BJKIBBKJVA6CPdcX30+WBsWxSJgF8wLZnrLktbmM2PUzxZk5X4JNL4UKjzd1eOKEnOkHAJiiFciHH364uX7ooYf63Vbcdthhhw3rvp999llzPXfu3N06RwC1yfMD6cpZEgSWxCKBtNSFWy26Ld+npU7IymNdnE/NbAzf7gIAAAAYDT35QDZtT5m2FYmIFjlUHtO6nkgynTcVyFY83ExgDY+7M4Gk8iJ2LGHC4zDFF6btW4cnmmkzcw8ARsekqUA+7bTT5KKLLpJbb71VLr74Ymlubjbb161bJ6tWrZLFixfLwoULS72QdXtLS4tZLK+ora1NZsyY0et+XdeVK664ovQYAKZez+NMLpCGiEgiJuKEmBWn4fHmXJ2k/WH+id05UI5SeQwAAIBxpGFud8YWx7FN24pkJm1m5A3F80S6syJ+NBArUS+W7YUKj3u2bZNYJCeOs0Gy7ovSk366cH/d7ZJ9+f8k/dgfzPeZjXuXjsvl4/LqOlf2iKdkdjwlm3J1knyhUzKdc3bzJxfpuOfG3b4PAJgsJk2A3NraKitWrJALL7xQjj76aLngggtMP+Trr7/efGp53XXXlfZds2aNHHfccXL22WfLypUrS9sPPPBA+ad/+idzrcHyxo0bzeJ5Tz/9tFk87/TTTx+nnw7AeFUep3OBaGbcGA0k6VgShAiQtfK4OeJKne0O63HDVmkAAAAAo9m2ojMrogXHe85rkn9scEIVX3RpeCyW1NdFxIraIl7l8DiTE7POSMz2ZIaTEqty5lziWIEJkGM2/Y8BYLRMmgBZaWisFcQaJF9++eUSi8XkmGOOkauvvloOOuigisd/4AMfkAceeEDuvfde6ezslIaGBnPcd7/7XRM2h+pdCmBS0MFvZ9o34XEiYkm8ir+WWnk830lLtJqRbzltfgwAAACMk44eV7a5KdPzcnqdL/EQg2HXCySddaVOLGmI+uLG9Bg/VNsK1w8kYgXSaLthu76VzIpmCI8BYJRNqgBZLVmyxFyGou0s9D+qvr72ta+N4pkBqCXJbCANce3zZkk0xIIf5bTyeG4sLeuyDaN2fgAAAMBoSGrbik5PYs22zKhzJRKirVouH0hb2pLACqQhGkgiakmywjHF8DjnBhKxLYkMIzxWUSqPAWDUUeYGAAPwA5HGuB0qPO77edSMaHZYg18AAABgvLWlNMwttK0IEx5ns66s77ZMrXE8FpFENNzjtKcK4XEsYpm1Rhg/A8DERYAMAAOoj1mmckJCVE74ndt6bWPwCwAAgFrl2CKLZkRDta3Ie4G8sqnb9C9uiQcS1Z7HIXSlfcnkfRMeNyUs2kUCwAQ36VpYAMBI0MFsRUEgQXe7+PVNVd13T3aYvZEBAACAYcqtf1aCfLb0fX7LOnMdnbOo9HXefo3MdNvFyXeKyB4Vex7vSNsy3/Nlbn0gHe7A42c/3SNBvsssrJd+4XGzLd3VKdMSGyTh2+K7DeKnbQlcVyQ28PHi7FrAz88uEJtFpwFgTBEgA8AwW1yImxM/50tk+hzxMz2hjutMe7K9u7oVonVwDgAAAOwODY+zzz0mVqTQYyK/eZ0EEojbtllyLz5lSo9zc/5JrHZXpH7oggfX9Qo9jwOReTPrpW67iHQP9sC+eMlO8WxbNm3eaDZFurdJY4MtO7w6sby8+JmYSDD4ebubXxG/q12seJ1I5BB+EQBgjNHCAgCq5PsibRlHAs8TO5YQu2VW6MrjTR1eeQFFRTlPZHOXy2sEAFPcPffcI0cccYQ0NDRIa2urnHLKKbJ27dpQx/785z+X8847T/bff39pamqSWbNmyZFHHinf+c53xNWKPwBThobH0fmvMxcrEpHAzYsdiYoVjYozbbZE5y7qVe07EN8PpDOZMz2PmxK+TGupC/HAlqT9qKS8wn23zGwV27HFsi2xdTbfID3gglzGXMSOSGTWglL4DQAYW1QgA0AVAl9kUzIwg1/LcSS38SXxOtvEaR04RE7et0o6Gjol2dMi26efLAtn2NL80kOS3NZutqtp7/3EoD3l1nfZknrhMUlu2yjSwEsFAFPR7bffbgLgAw44QK655hrJZDJy/fXXy1FHHSUPPvigHHjggUMef/7555vg+bTTTpN9991XOjs75Qc/+IGce+658uMf/1h+8Ytf0H8UmIK8TFr8nk4RJyJO8wyRSOV4wPNFMq4tTX4gLXGR+hBrhpjK4nxW8uJLfTT8TDwNjv10UsSyxYonzNi7krxPjRwAjAYCZAAIKxDJepYkc7bUO55IEKvqDbeOeRdNj8pzdriB8/akKwt9kenRXb3qAABTS3t7u1xyySWyYMECExY3Nzeb7Weeeabst99+ctFFF8m999475H3cdddd8va3v73X/1kXX3yxLF68WH71q1/Jr3/9azn55JNH/WcBMHFoS4mgp0MsyzY9kL0dmwfrINGrbUXGLeTBjQ1Rqc+FeKBgZxWxH5NozJbZ9eHOT/sh7wqP68SyKwfDOd+WbflEuAcAAFSFj+cAIATt75bJB+IGIo0xX2YkvEGn2g1mbnMk3OJ82iNj59W8Rl8aHKYXA8BUtXr1aunq6jIVyMXwWC1atEiWLFki9913n6xfv37I+zj++OP7feDpOI4sXbrUfP3EE0+M0tkDmIhMP+K2TSactZtniBUdYOW6PrJZd2fbCktiEV/q4pVbSehYNsikJPBcsWxH6uuioYbPPV5UgnymcH4NLaHD41ez9eIF1Y3PAQDhUIEMABUEQSDJvCV5T0Tz33mNlqwrdJ8YUo/X+09sxAk3oA2yKXM9rd6W5rjIZl4hAJiyHn74YXOt7Sr60m133HGHPPLII7Jw4cKq7/vVV18113PmzKm479atW2Xbtm29tj3//PNVPyaA8eWleyTI56pqW6Ft1V7Z1C2+P03iTiBR2woVHqfSeQniObGciIgVlxA5sGR9W3YE2lPZKoTHIdtWaHjsBjYz9wBglBAgA8BOXlebWRjPbesRNxORfI8nbjIqWSchcSslEXHNoLnv4NdP95QWG/F0Kp/dIh1dadmebpB8ap3kolvEjb5esi89KeltOfF2bJF891azXWVffLJwbGfbrnJnEWmIV7HaHgBgUtqwYYO51hYWfRW3Ffep9n5vueUWsyDfqaeeWnH/m266SZYvX1714wCYWPzO7WLPXtirbcVz7RHpTrWarzd2OrI9n5A9491mf9cLZEfalvmeb9pWpHLZiq0udM2QnnwgedsXqyEmVpAQCTGhLh9YkvSiMssOxErUi+WE6ZEhpm3FzGhW5sTS8myqWV5KN8q2fNzc5kgg06Ph7gcAMDgCZADYScNjHUh7Xa74bkLcTE7SqQZxnbxE7A6JO40DT7sLfPE1/M3nJGicaSqPM/k6ka4d4tl62Sp+Yrp43kbJd3WLl0qKZ7eLZ201h+deekp8nd7nF0bWVozebQCAglSqMCslHi+EIeUSiUSvfcJKJpMmNNbWGLqI3vTp0yses2zZslLLi/IKZF2YD0ANsR0THpe3rcj5Ik/2TJeo7cvm9ohIYJfaVrSlLVPbMG9mvTy/XdtWDL02h+6bzIvkXEui9bYJgsOExxpU54KI2JYrsyM9YvnhW1Fo2woNj5sjeXEDS55PN8v2XEL8wJLZ8XTo+wEADI4AGQDKaXmxbUkglvS4lhmExqIxaXQs6coXFg0ZkO0ULiKyIx+XueLL7HhWxCtst+ubTZWymYan0/4su7R/ZNYCST/1l7K/zJV7ygEApob6+sKKU9ls/9Amk8n02idseKwL5j366KNyww03yOmnnx7quNmzZ5sLgNoWmT53wJ7HGh5r1fF2q5D3ZvOBbNa2FSLSnPBlWkudyHapGB5nM64Jj7VPcrQuKmJVXjw6nc1LJqdNKwJpdvISDXFMOV1wWsPj0s9o+TItkpMOt3JvZwBAOCyiBwB9BSJpNzCD34gTSDwRMXlvJaafnE6VswLZI9olUavSBD8tXvYkv2WdiO/xOgAAqmpTMVR7i4F0d3fLSSedJH/605/k5ptvNlXFAKYWK0TPY60G3tBtief50hIXaYhWrgbWthUdmcAcG4sE5pgwPY91kepkT14sK5CE5ZlxdLVYcBoARh8BMgCU0zFrPid5UzkRSNyxQq0WHbj50uJ3s6IZiYWonAh8X4JsRsRzxW6ZyesAAOjn8MMPN9cPPfRQv9uK2w477LCKz1xnZ6eceOKJ5pjbbrtNLrjgAp5tAP24nidtadvMwtO2FfUhJsbpgnkbkyIZU3xhSWO0MKmvEu2T3JO3xbYtqY9ZYocqvqiuOhkAMDIIkAGgjIbAWhUcjQSFwW/Y8DiXKbSl2DkFsPJBGh6nzbUzY544dQ28DgCAfrTHcFNTk9x6662mZ3HRunXrZNWqVbJ48WJZuHBhqRfyM888I5s2bRowPH7kkUdk5cqVcs455/BMA+hH21a0dWRMK4q59TvbVlTgB4G8uqVLknlbEpHwM/cymbx0Z2yxJZCWxphYIQbdul5JkE7yygHAOKAHMgD0CYMtOyJ1thWubUVZeGzVNYZ6Ll3PksDLmvBYF8xzGlvE72rjdQAA9NPa2iorVqyQCy+8UI4++mhTOaz9kK+//nqxLEuuu+660r5r1qyR4447Ts4++2wTFBedcMIJ8te//tUsnKfH3Hnnnb0e46CDDjIXAFNX3g1kQ9YSLxpIU8KXlroQgW6gbStEuntcaYz6Mi1qyYaQa991p/IyvUmkKSYSiei6IEO3c9MCD7+ns9ArI6zqu2EAAAZBgAwAZSxdwC4aFTvEatHaeiLI7wyP4wmxQszV08qOrV6j7BsEJjw2jxdicA4AmLo0NJ4xY4YJki+//HKJxWJyzDHHyNVXXx0q+NXwWK1evdpc+rrqqqsIkIEpLHBd2dJjyUzHkmmNMYklK6fA2kliTdcMcX1LksmI1OcjsjHfIFaFSXXdO9cD1bYVM+p86RxgnPvnnoXyjNcoazoLA3Iv/3oJtOWbXS9iBaGmUev4ORUUFqwejts37t1v27nznx32/QFArSNABjClPLs5J1k3kC1drnSmfVOZ0FJfGIZaaUta4vWa8la8n578zkXzTHhcFyo8LlZ2tEujrIssEEsHwb7IzPaIvEZEXsi1Si5w5CWvUI3clouawW9bPj4CPzkAoJYtWbLEXIai7SyCAT51HGgbAJi/D64rbttmU/+rbSuSdTFxK3SJ0CLg7p6smVUXsQNpaoiLH6L4IptzZXu6EE5Pa4qZfslS4bjAD0x4rIN2Kxoz5xtG0o9I3qdjJwCMFAJkAFOKhsePrcvKtm5POno8ybiBJLpscWyRPbXNW4hpd/dsXSRb0hF5xY7IGicl4lsmCLbScdnhzpQ2q1Wa/YR05G35hz9dHvbfKDu658nL+WmyuP55aXRy8qK1hzzgHiy+2LLgH3XymUViwuOnMrNli1sIkF1f5L+fism2rlnS5iZk34YnR/8JAgAAwJSgYaxpoxbzZEZCQretyHoiubwvESeQuF1YMK9iYwnPlVTOlcjOhfIcp3J1sAmPdbafhsd2RCwnEipA7vRikvOdcOuSAABC4SM5AFNOVKfn1dmScwsLf8xodKQxEa5hW97X6mPb5Mw6kBUrzCp7gQRuVnyxTGVHwvYkIp60WCmx+wy3o5Ync51O83Uy45kBOoNfAAAAjCSdSed1tUmgCzq3zJDGEBPetG1FxhNxA0tiUVsSTmkN6aEfy9W2b3nTtmJu2HWjg53hsbZ90zF3iNl+Gm53ujHJeI7EbE/qraH7KgMAwiNABjD1BIF0ZwJx/UAitiVNCcssKlRJzgsk51pmtegGR0uOwzyWrhjtmsesiwQhKzsKlRlZVyTuCINfAAAAjGh4nN+yzvSisBtaxK5vDBUel9pWWIW2FaHqKPK5nQtOW9JYF5VoiDnQXqALTmu/uELbirDh8eZcnWR8RxKOJ426oEnIBf0AAJURIAOYcrYlfcm5hfA4EQ0XHmfyOl2vUHncFBfT8qISX8Nj0xAuMIvlxUMMmMt7Huv+jdGAwS8AAABGhFYDm/DYc8VqmCZ2or7iMTpj79UtXbvaVjihMl3T8zjIpEx4bEXj4kTsUOFxKoiZIgwNj7VtRdjwOOlFzUy/FicXKtwGAIRHgAxgykllfYlFLEnEdDxbeXSZz/vSky9UHiciOnCWUINfXbxDFXq2hVsFus2rlx4/ar5uTDgMfgEAADBi3B2bTXjszJgnTkIXAKkcznZktPrYraptRSYfSCrtmqTZjteJ2JXH3H5gSZcXNW3fNDgOEx4rLb7Q8LjRyUtLJBfqGABAdVhED8CUUx+3TduKjp2rQFdqW5HPudIsgakI1t5tYSqPu/24BGbBj3AlGju7VkjKj0iDnTdfh6nsAAAAAELzvUJ43Ngy6C5u22bJdTwvblen7Ng+SzJ+ROLBNmmatYd09OS1OLjizD1dMyRwu8Xzu8XNbhEvaBI35Uh+87rCY2x+WdzGaeJJkwS5rLjpesk6ddIY+FJn5XYOhMMtgpf2IzLfScvcWFpeyYRtsjx2Ou65ccDt0977iTE/FwAYLuIJAFPOrEa7urYVliXNcZEQs+6MHj9iKifqLO29FqY5nIjfuc18WW+7MiOaDfdAAAAAQBXslplDhsdFgR/I5nTEhMcJ25W5dW6o4obymXu6ZkiYamXPE0kHjpZemCriWJWL39Xp+cXSzNwDgFFEgAxg6gkR6mbdoDT4rUtEJFQHip1lxDr9rsHOScwOwmTHpjecr/3hRGSGkwoVbgMAAADVcuoaQi3ovNlrlKRbCI+brUyo8Fhn7mnfYx0/h10zRNu+dbmF8DhmuRK3w1Udl9PiC4bPADC6CJABoC/Pk7Rrm8Fv2LYVGh4Hbq5URRwPUTmheXM6iJrjiguYMPgFAADAeNHihq4gIUk/Jo0RV1qszPBm7oUovnA1PPYTplFFXDyJWkHIM+yN8TMAjD4CZAAoE+TzEuRzJjwO3bZCw2PPLVUgR8NUHgeB9AQxyQe2WJGY2C2zeB0AAAAwbnxfpL0zbdpWNNo507YizOJ36Wy+6pl7ri7O59WZOLgx4oUcP+uBhbVCAABjiwAZAMoE2ZQpY6iPSei2FSY81ol3kWi459IPTGVH1nckavliJeqpnAAAAMC4CXyRTclA0lm/0PPYSYbreewHkuzJVzdzT6uccxHxpND2LR5mzG0eLCuBptwAgDFHgAwA2rNNyyCUZYkVjYesPJZd4bGtI+bKo18d83YGicJq1rYndVZehJbHAAAAGCc6M257WiSZs6Uubpuex1aIIDjn6RjaNqFx2Jl77s781wtEWpxMqLZv5hw9VwLfEytMqr1T3meQDQAjhQAZwJSXyQeSyhUCZLuuMdRUPc/XSo3y8NgONe1OKzuKq1k3WLlQ2TGDXwAAAIxWeOx3bJeUa0ljzJfWlrpQPY+1bUXWs8xYtqUxFmrmno6fN7tN5uvmiCuJkGuGiGkV54ulxRohZ/xlfVtSfiTUvgCAygiQAUxpeTeQZNbflRmHCIJdT6THK+xXTXiccguVHcXVrMMs+JF1hcEvAAAARpyOT4PudvEzKamPBDKvsRAIV9O2IhHxJRJmxbygMH72dz6CtrsIc36lthWWLRKN6+i74nEZ35GkFxU71KJ8AIAwCJABTOnwOOMGJjxujIeb4ub7gXRnC+s/myqIsNPo3Lzkd1Z2hF3NWnvQJXVBEga/AAAAGOnK42S7+LmM2Il6mVkXblhb3rYiEbbnsa4Z4rtm/DzDSYU9w53hcaFtheVEQhVfaHjc6cbM+LnB1tmCAICRQIAMYMq2rTDhsU67qysMgsP0bMu4hcqJOkcrIayqerZFd1Z2hGmRoZLZQrjN4BcAAAAjGR572zdKoOFxLCH2tJmmwLfqthV2uMX5CmuGiBk/Nzhu6LYVhfDYEXHCtaLocqMmPHasQJqdfNghNwAgBAJkAFNOT9YrtK0QkUTMEidMz2Ov0E5Cx7MNUV9iYQbMurfvlXq21YfrdlFqj6Gn1RwrhMgAAADA7tJwVsNjP9UtViwhVlNrqJlxXTmr6rYVZs0QN7tzzRAn3Pg5EElLVAK/cEyhbUW48HhLrs6Ex9MiWXMNABg5BMgAppzt3YWex3Uhw2NtW9GVFVN5HIsEkoha4Qa/nmMGv6akIxINVbDc40WlLV9nvm6pc0JVdgAAAABh+J3bTHhs1zeJ3RguPM4EjmzOxKpqW1FaMyTYueC0FW78nPQjkg8csfQxovGQ4+eICY8jli/TIjmJEB4DwIgjmgAw5egq0dW0rUhnXBMexx1fomH+auoiIUFM8lIY/Ibt2aZ2+HWiTTJUhIWjAQAAMIJ0wTwNj52Z88P3FPYSErHCt63QmXulNUMi0XALTksg2SAiOd+RqOWZthWhx8/5uAmP94inzDUAYOQRIAOYcuY2R6prWxEE0hANJOaEG8WmAkdygSNR8UR06l0IXrrHXOu0wLmxTKhjAAAAgGrognmF8Dhc2woNjx0JZI/6bKi2FeUz97TnsaWVGyH6JGd9R9zAkpjtSZ3kNXoO/TNpuwo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|
||
"text/plain": [
|
||
"<Figure size 1440x1536 with 8 Axes>"
|
||
]
|
||
},
|
||
"metadata": {},
|
||
"output_type": "display_data"
|
||
},
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"Saved: decision_margin_distributions.png\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"fig, axes = plt.subplots(len(subjects), len(PAIRS),\n",
|
||
" figsize=(6 * len(PAIRS), 3.2 * len(subjects)),\n",
|
||
" sharex=True, squeeze=False)\n",
|
||
"fig.suptitle('LDA decision-function distributions on ONLINE sessions\\n'\n",
|
||
" '(class separation ↔ classification amplitude & SNR)',\n",
|
||
" fontsize=12, fontweight='bold', y=1.01)\n",
|
||
"\n",
|
||
"for i, subj in enumerate(subjects):\n",
|
||
" for j, pair in enumerate(PAIRS):\n",
|
||
" ax = axes[i][j]\n",
|
||
" for cond, color in cond_color.items():\n",
|
||
" row = next((r for r in results\n",
|
||
" if r['subject']==subj and r['pair']==pair['name']\n",
|
||
" and r['condition']==cond), None)\n",
|
||
" if row is None: continue\n",
|
||
" m_mi = row['margin'][row['y_test'] == 1]\n",
|
||
" m_rest = row['margin'][row['y_test'] == 0]\n",
|
||
" ax.hist(m_mi, bins=15, alpha=0.5, color=color,\n",
|
||
" label=f'{cond} MI', density=True)\n",
|
||
" ax.hist(m_rest, bins=15, alpha=0.25, color=color, hatch='///',\n",
|
||
" edgecolor=color, label=f'{cond} REST', density=True)\n",
|
||
" ax.axvline(0, color='k', lw=0.8)\n",
|
||
" ax.set_title(f'{subj} | {pair[\"name\"]}', fontsize=10, fontweight='bold')\n",
|
||
" if j == 0: ax.set_ylabel('Density')\n",
|
||
" if i == len(subjects) - 1: ax.set_xlabel('LDA decision function')\n",
|
||
" ax.spines[['top','right']].set_visible(False)\n",
|
||
" if i == 0 and j == 0:\n",
|
||
" ax.legend(fontsize=6.5, loc='upper left', ncol=2)\n",
|
||
"\n",
|
||
"plt.tight_layout()\n",
|
||
"plt.savefig('decision_margin_distributions.png', dpi=150, bbox_inches='tight')\n",
|
||
"plt.show()\n",
|
||
"print('Saved: decision_margin_distributions.png')"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"id": "fcb6d19d",
|
||
"metadata": {},
|
||
"source": [
|
||
"---\n",
|
||
"## Figure 3 — Paired Δ (FES − NOFES) per metric\n",
|
||
"\n",
|
||
"Within each (subject × pair), FES and NOFES sessions use the same offline-trained model. Positive bars mean FES > NOFES; negative means NOFES > FES. This removes the offline-model-quality confound and isolates the effect of feedback type."
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 11,
|
||
"id": "75df404b",
|
||
"metadata": {
|
||
"execution": {
|
||
"iopub.execute_input": "2026-04-22T19:27:27.545755Z",
|
||
"iopub.status.busy": "2026-04-22T19:27:27.545655Z",
|
||
"iopub.status.idle": "2026-04-22T19:27:27.826448Z",
|
||
"shell.execute_reply": "2026-04-22T19:27:27.826020Z"
|
||
}
|
||
},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"image/png": 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|
||
"text/plain": [
|
||
"<Figure size 1920x540 with 4 Axes>"
|
||
]
|
||
},
|
||
"metadata": {},
|
||
"output_type": "display_data"
|
||
},
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"Saved: fes_minus_nofes_delta.png\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"fig, axes = plt.subplots(1, 4, figsize=(16, 4.5))\n",
|
||
"fig.suptitle('Within-pair Δ = FES − NOFES (positive → FES better)',\n",
|
||
" fontsize=12, fontweight='bold', y=1.03)\n",
|
||
"\n",
|
||
"for ax, (key, title, _) in zip(axes, METRICS):\n",
|
||
" labels, deltas = [], []\n",
|
||
" for subj in subjects:\n",
|
||
" for pair in PAIRS:\n",
|
||
" fes = next((r for r in results if r['subject']==subj and r['pair']==pair['name']\n",
|
||
" and r['condition']=='FES'), None)\n",
|
||
" nof = next((r for r in results if r['subject']==subj and r['pair']==pair['name']\n",
|
||
" and r['condition']=='NOFES'), None)\n",
|
||
" if fes is None or nof is None: continue\n",
|
||
" deltas.append(fes[key] - nof[key])\n",
|
||
" labels.append(f'{subj}\\n{pair[\"name\"].split()[0]}')\n",
|
||
"\n",
|
||
" colors = ['#E05C2A' if d > 0 else '#2A7BE0' for d in deltas]\n",
|
||
" ax.bar(np.arange(len(deltas)), deltas, color=colors, edgecolor='white', zorder=2)\n",
|
||
" ax.axhline(0, color='k', lw=0.8)\n",
|
||
" ax.set_xticks(np.arange(len(deltas)))\n",
|
||
" ax.set_xticklabels(labels, fontsize=8)\n",
|
||
" ax.set_title(f'Δ {title.split(\"(\")[0].strip()}', fontsize=10, fontweight='bold')\n",
|
||
" ax.grid(axis='y', alpha=0.3)\n",
|
||
" ax.spines[['top','right']].set_visible(False)\n",
|
||
"\n",
|
||
"plt.tight_layout()\n",
|
||
"plt.savefig('fes_minus_nofes_delta.png', dpi=150, bbox_inches='tight')\n",
|
||
"plt.show()\n",
|
||
"print('Saved: fes_minus_nofes_delta.png')"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"id": "8f9533f8",
|
||
"metadata": {},
|
||
"source": [
|
||
"---\n",
|
||
"## Figure 5 — Per-class accuracy and EARLYSTOP latency\n",
|
||
"\n",
|
||
"FES stimulation fires only on MI trials, so if it helps the subject/system it should\n",
|
||
"show up in **MI-accuracy** (count_240 / count_200) specifically, not in REST-accuracy.\n",
|
||
"A lift in MI-acc without change in REST-acc would be a genuine sensitivity gain; an\n",
|
||
"equal-and-opposite shift would be a bias/threshold effect.\n",
|
||
"\n",
|
||
"**EARLYSTOP latency** (BEGIN → EARLYSTOP in seconds) is a continuous readout of how\n",
|
||
"confidently and how fast the live classifier committed — shorter latency means a\n",
|
||
"sharper MI signal crossing the detection threshold earlier."
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 30,
|
||
"id": "086ef172",
|
||
"metadata": {
|
||
"execution": {
|
||
"iopub.execute_input": "2026-04-22T19:27:27.828111Z",
|
||
"iopub.status.busy": "2026-04-22T19:27:27.828016Z",
|
||
"iopub.status.idle": "2026-04-22T19:27:28.197602Z",
|
||
"shell.execute_reply": "2026-04-22T19:27:28.197189Z"
|
||
}
|
||
},
|
||
"outputs": [
|
||
{
|
||
"name": "stderr",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"/Users/adipu/ECE374N/Final Project/venv/lib/python3.13/site-packages/scipy/stats/_axis_nan_policy.py:430: RuntimeWarning: Precision loss occurred in moment calculation due to catastrophic cancellation. This occurs when the data are nearly identical. Results may be unreliable.\n",
|
||
" return hypotest_fun_in(*args, **kwds)\n"
|
||
]
|
||
},
|
||
{
|
||
"data": {
|
||
"image/png": 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",
|
||
"text/plain": [
|
||
"<Figure size 1680x1200 with 4 Axes>"
|
||
]
|
||
},
|
||
"metadata": {},
|
||
"output_type": "display_data"
|
||
},
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"Saved: per_class_acc_latency.png\n",
|
||
"\n",
|
||
"Per-subject paired Δ = mean(FES) − mean(NOFES) & T-Test:\n",
|
||
"\n",
|
||
" MI accuracy:\n",
|
||
" subj 002: FES=0.93 NOFES=0.85 Δ=+0.08 | p = 0.5000 (t = 1.00, n = 2)\n",
|
||
" subj 003: FES=0.73 NOFES=0.72 Δ=+0.02 | p = 0.8656 (t = 0.21, n = 2)\n",
|
||
" subj 005: FES=0.78 NOFES=0.82 Δ=-0.03 | p = 0.9208 (t = -0.12, n = 2)\n",
|
||
" subj 009: FES=0.82 NOFES=0.72 Δ=+0.10 | p = 0.3743 (t = 1.50, n = 2)\n",
|
||
"\n",
|
||
" REST accuracy:\n",
|
||
" subj 002: FES=0.87 NOFES=0.83 Δ=+0.03 | p = 0.7048 (t = 0.50, n = 2)\n",
|
||
" subj 003: FES=0.78 NOFES=0.76 Δ=+0.02 | p = 0.5000 (t = 1.00, n = 2)\n",
|
||
" subj 005: FES=0.93 NOFES=0.90 Δ=+0.03 | p = 0.0000 (t = inf, n = 2)\n",
|
||
" subj 009: FES=0.72 NOFES=0.85 Δ=-0.13 | p = 0.1560 (t = -4.00, n = 2)\n",
|
||
"\n",
|
||
" MI EARLYSTOP latency:\n",
|
||
" subj 002: FES=2.50 NOFES=2.30 Δ=+0.20 | p = 0.6020 (t = 0.72, n = 2)\n",
|
||
" subj 003: FES=2.45 NOFES=2.36 Δ=+0.09 | p = 0.8457 (t = 0.25, n = 2)\n",
|
||
" subj 005: FES=2.54 NOFES=1.99 Δ=+0.56 | p = 0.3678 (t = 1.53, n = 2)\n",
|
||
" subj 009: FES=2.60 NOFES=2.29 Δ=+0.31 | p = 0.2213 (t = 2.76, n = 2)\n",
|
||
"\n",
|
||
" REST EARLYSTOP latency:\n",
|
||
" subj 002: FES=2.11 NOFES=2.22 Δ=-0.10 | p = 0.7758 (t = -0.37, n = 2)\n",
|
||
" subj 003: FES=2.34 NOFES=2.64 Δ=-0.30 | p = 0.5264 (t = -0.92, n = 2)\n",
|
||
" subj 005: FES=2.20 NOFES=2.48 Δ=-0.28 | p = 0.3581 (t = -1.59, n = 2)\n",
|
||
" subj 009: FES=1.89 NOFES=2.23 Δ=-0.34 | p = 0.0667 (t = -9.50, n = 2)\n"
|
||
]
|
||
},
|
||
{
|
||
"name": "stderr",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"/Users/adipu/ECE374N/Final Project/venv/lib/python3.13/site-packages/scipy/stats/_axis_nan_policy.py:430: RuntimeWarning: Precision loss occurred in moment calculation due to catastrophic cancellation. This occurs when the data are nearly identical. Results may be unreliable.\n",
|
||
" return hypotest_fun_in(*args, **kwds)\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"from scipy.stats import ttest_rel\n",
|
||
"\n",
|
||
"PER_CLASS_METRICS = [\n",
|
||
" ('mi_acc', 'MI accuracy', '0–1'),\n",
|
||
" ('rest_acc', 'REST accuracy', '0–1'),\n",
|
||
" ('mi_latency', 'MI EARLYSTOP latency', 'seconds'),\n",
|
||
" ('rest_latency', 'REST EARLYSTOP latency', 'seconds'),\n",
|
||
"]\n",
|
||
"\n",
|
||
"# Restructure data to average across multiple sessions (Pairs) for each subject\n",
|
||
"def subj_cond_metrics(key):\n",
|
||
" \"\"\"Return {subj: {'FES': [vals...], 'NOFES': [vals...]}} using non-null entries in `results`.\"\"\"\n",
|
||
" out = {s: {'FES': [], 'NOFES': []} for s in subjects}\n",
|
||
" for r in results:\n",
|
||
" v = r.get(key)\n",
|
||
" if v is None or (isinstance(v, float) and np.isnan(v)):\n",
|
||
" continue\n",
|
||
" out[r['subject']][r['condition']].append(v)\n",
|
||
" return out\n",
|
||
"\n",
|
||
"mi_acc_data = subj_cond_metrics('mi_acc')\n",
|
||
"rest_acc_data = subj_cond_metrics('rest_acc')\n",
|
||
"mi_lat_data = subj_cond_metrics('mi_latency')\n",
|
||
"rest_lat_data = subj_cond_metrics('rest_latency')\n",
|
||
"\n",
|
||
"metrics_data = [mi_acc_data, rest_acc_data, mi_lat_data, rest_lat_data]\n",
|
||
"fig, axes = plt.subplots(2, 2, figsize=(14, 10))\n",
|
||
"fig.suptitle('Per-subject average: MI vs REST, accuracy & decision latency\\n(mean across that subject\\'s sessions ± SEM)',\n",
|
||
" fontsize=13, fontweight='bold', y=1.03)\n",
|
||
"\n",
|
||
"width = 0.38\n",
|
||
"x = np.arange(len(subjects))\n",
|
||
"\n",
|
||
"for ax, data_dict, (key, title, unit) in zip(axes.ravel(), metrics_data, PER_CLASS_METRICS):\n",
|
||
" for i, cond in enumerate(('FES', 'NOFES')):\n",
|
||
" means = [np.mean(data_dict[s][cond]) if data_dict[s][cond] else np.nan for s in subjects]\n",
|
||
" sems = [np.std(data_dict[s][cond], ddof=1) / np.sqrt(len(data_dict[s][cond]))\n",
|
||
" if len(data_dict[s][cond]) > 1 else 0.0 for s in subjects]\n",
|
||
" offset = (i - 0.5) * width\n",
|
||
" ax.bar(x + offset, means, width, yerr=sems,\n",
|
||
" color=cond_color[cond], label=cond, edgecolor='white', capsize=4)\n",
|
||
" \n",
|
||
" # Overlay individual session values\n",
|
||
" for xi, s in zip(x, subjects):\n",
|
||
" if data_dict[s][cond]:\n",
|
||
" ax.scatter(np.full(len(data_dict[s][cond]), xi + offset), data_dict[s][cond],\n",
|
||
" color='k', alpha=0.5, s=14, zorder=3)\n",
|
||
" \n",
|
||
" # Calculate p-values for pairs and add them to custom labels\n",
|
||
" new_labels = []\n",
|
||
" for s in subjects:\n",
|
||
" label = s\n",
|
||
" if data_dict[s]['FES'] and data_dict[s]['NOFES'] and len(data_dict[s]['FES']) == len(data_dict[s]['NOFES']) and len(data_dict[s]['FES']) > 1:\n",
|
||
" try:\n",
|
||
" _, p_val = ttest_rel(data_dict[s]['FES'], data_dict[s]['NOFES'])\n",
|
||
" p_str = f'p={p_val:.3f}' if p_val >= 0.001 else 'p<0.001'\n",
|
||
" label = f'{s}\\n({p_str})'\n",
|
||
" except Exception:\n",
|
||
" pass\n",
|
||
" new_labels.append(label)\n",
|
||
"\n",
|
||
" ax.set_xticks(x)\n",
|
||
" ax.set_xticklabels(new_labels, fontsize=8)\n",
|
||
" ax.set_title(f'{title} ({unit})', fontsize=11, fontweight='bold')\n",
|
||
" ax.grid(axis='y', alpha=0.3)\n",
|
||
" ax.spines[['top','right']].set_visible(False)\n",
|
||
" if 'acc' in key:\n",
|
||
" ax.axhline(0.5, color='gray', linestyle='--', lw=0.8, alpha=0.6)\n",
|
||
" ax.set_ylim(0, 1.05)\n",
|
||
"\n",
|
||
"fig.legend(handles=[Patch(color=cond_color['FES'], label='ONLINE_FES'),\n",
|
||
" Patch(color=cond_color['NOFES'], label='ONLINE_NOFES')],\n",
|
||
" loc='upper right', ncol=2, bbox_to_anchor=(0.98, 1.0))\n",
|
||
"plt.tight_layout()\n",
|
||
"plt.savefig('per_class_acc_latency.png', dpi=150, bbox_inches='tight')\n",
|
||
"plt.show()\n",
|
||
"print('Saved: per_class_acc_latency.png')\n",
|
||
"\n",
|
||
"# ── Paired Δ (FES − NOFES) summary per subject ─────────────────────\n",
|
||
"print('\\nPer-subject paired Δ = mean(FES) − mean(NOFES) & T-Test:')\n",
|
||
"for (key, title, _), data_dict in zip(PER_CLASS_METRICS, metrics_data):\n",
|
||
" print(f'\\n {title}:')\n",
|
||
" for s in subjects:\n",
|
||
" if data_dict[s]['FES'] and data_dict[s]['NOFES']:\n",
|
||
" delta = np.mean(data_dict[s]['FES']) - np.mean(data_dict[s]['NOFES'])\n",
|
||
" if len(data_dict[s]['FES']) == len(data_dict[s]['NOFES']) and len(data_dict[s]['FES']) > 1:\n",
|
||
" t_stat, p_val = ttest_rel(data_dict[s]['FES'], data_dict[s]['NOFES'])\n",
|
||
" stats_str = f'p = {p_val:.4f} (t = {t_stat:.2f}, n = {len(data_dict[s][\"FES\"])})'\n",
|
||
" else:\n",
|
||
" stats_str = f'n = {len(data_dict[s][\"FES\"])} (too few paired runs)'\n",
|
||
" \n",
|
||
" print(f' subj {s}: FES={np.mean(data_dict[s][\"FES\"]):.2f} '\n",
|
||
" f'NOFES={np.mean(data_dict[s][\"NOFES\"]):.2f} Δ={delta:+.2f} | {stats_str}')"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"id": "c74da761",
|
||
"metadata": {},
|
||
"source": [
|
||
"### Per-subject average latency\n",
|
||
"\n",
|
||
"Collapses the per-(subject × pair) bars into one FES value and one NOFES value per subject\n",
|
||
"by averaging across all that subject's ONLINE sessions of each type. Error bars are the\n",
|
||
"session-to-session SEM within that (subject, condition). Easier to read when you just want\n",
|
||
"the per-subject FES vs NOFES comparison without the pair split."
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": null,
|
||
"id": "4ea9951f",
|
||
"metadata": {
|
||
"execution": {
|
||
"iopub.execute_input": "2026-04-22T19:27:28.199503Z",
|
||
"iopub.status.busy": "2026-04-22T19:27:28.199411Z",
|
||
"iopub.status.idle": "2026-04-22T19:27:28.407015Z",
|
||
"shell.execute_reply": "2026-04-22T19:27:28.406594Z"
|
||
}
|
||
},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
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|
||
"text/plain": [
|
||
"<Figure size 1440x540 with 2 Axes>"
|
||
]
|
||
},
|
||
"metadata": {},
|
||
"output_type": "display_data"
|
||
},
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"Saved: per_subject_latency.png\n",
|
||
"\n",
|
||
"Per-subject paired Δ = mean(FES lat) − mean(NOFES lat) & T-Test:\n",
|
||
" MI latency:\n",
|
||
" subj 002: FES=2.50s NOFES=2.30s Δ=+0.20s | p = 0.6020 (t = 0.72, n = 2)\n",
|
||
" subj 003: FES=2.45s NOFES=2.36s Δ=+0.09s | p = 0.8457 (t = 0.25, n = 2)\n",
|
||
" subj 005: FES=2.54s NOFES=1.99s Δ=+0.56s | p = 0.3678 (t = 1.53, n = 2)\n",
|
||
" subj 009: FES=2.60s NOFES=2.29s Δ=+0.31s | p = 0.2213 (t = 2.76, n = 2)\n",
|
||
" REST latency:\n",
|
||
" subj 002: FES=2.11s NOFES=2.22s Δ=-0.10s | p = 0.7758 (t = -0.37, n = 2)\n",
|
||
" subj 003: FES=2.34s NOFES=2.64s Δ=-0.30s | p = 0.5264 (t = -0.92, n = 2)\n",
|
||
" subj 005: FES=2.20s NOFES=2.48s Δ=-0.28s | p = 0.3581 (t = -1.59, n = 2)\n",
|
||
" subj 009: FES=1.89s NOFES=2.23s Δ=-0.34s | p = 0.0667 (t = -9.50, n = 2)\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"from scipy.stats import ttest_rel\n",
|
||
"\n",
|
||
"# Average latency per subject across sessions (collapses the pair dimension)\n",
|
||
"def subj_cond_latencies(key):\n",
|
||
" \"\"\"Return {subj: {'FES': [vals...], 'NOFES': [vals...]}} using all non-null entries in `results`.\"\"\"\n",
|
||
" out = {s: {'FES': [], 'NOFES': []} for s in subjects}\n",
|
||
" for r in results:\n",
|
||
" v = r.get(key)\n",
|
||
" if v is None or (isinstance(v, float) and np.isnan(v)):\n",
|
||
" continue\n",
|
||
" out[r['subject']][r['condition']].append(v)\n",
|
||
" return out\n",
|
||
"\n",
|
||
"mi_lat = subj_cond_latencies('mi_latency')\n",
|
||
"rest_lat = subj_cond_latencies('rest_latency')\n",
|
||
"\n",
|
||
"fig, axes = plt.subplots(1, 2, figsize=(12, 4.5), sharey=True)\n",
|
||
"fig.suptitle('Per-subject average EARLYSTOP latency (mean across that subject\\'s sessions ± SEM)',\n",
|
||
" fontsize=12, fontweight='bold', y=1.02)\n",
|
||
"\n",
|
||
"width = 0.38\n",
|
||
"x = np.arange(len(subjects))\n",
|
||
"\n",
|
||
"for ax, data, title in [(axes[0], mi_lat, 'MI trials'),\n",
|
||
" (axes[1], rest_lat, 'REST trials')]:\n",
|
||
" for i, cond in enumerate(('FES', 'NOFES')):\n",
|
||
" means = [np.mean(data[s][cond]) if data[s][cond] else np.nan for s in subjects]\n",
|
||
" sems = [np.std(data[s][cond], ddof=1) / np.sqrt(len(data[s][cond]))\n",
|
||
" if len(data[s][cond]) > 1 else 0.0 for s in subjects]\n",
|
||
" offset = (i - 0.5) * width\n",
|
||
" ax.bar(x + offset, means, width, yerr=sems,\n",
|
||
" color=cond_color[cond], label=cond, edgecolor='white', capsize=4)\n",
|
||
" # Overlay individual session values\n",
|
||
" for xi, s in zip(x, subjects):\n",
|
||
" if data[s][cond]:\n",
|
||
" ax.scatter(np.full(len(data[s][cond]), xi + offset), data[s][cond],\n",
|
||
" color='k', alpha=0.5, s=14, zorder=3)\n",
|
||
" \n",
|
||
" # Calculate and format p-values for x-axis labels\n",
|
||
" new_labels = []\n",
|
||
" for s in subjects:\n",
|
||
" label = s\n",
|
||
" if data[s]['FES'] and data[s]['NOFES'] and len(data[s]['FES']) == len(data[s]['NOFES']) and len(data[s]['FES']) > 1:\n",
|
||
" try:\n",
|
||
" _, p_val = ttest_rel(data[s]['FES'], data[s]['NOFES'])\n",
|
||
" p_str = f'p={p_val:.3f}' if p_val >= 0.001 else 'p<0.001'\n",
|
||
" label = f'{s}\\n({p_str})'\n",
|
||
" except Exception:\n",
|
||
" pass\n",
|
||
" new_labels.append(label)\n",
|
||
" \n",
|
||
" ax.set_xticks(x)\n",
|
||
" ax.set_xticklabels(new_labels, fontsize=8) # slightly smaller to fit the p-vals\n",
|
||
" ax.set_xlabel('Subject')\n",
|
||
" ax.set_title(title, fontweight='bold')\n",
|
||
" ax.grid(axis='y', alpha=0.3)\n",
|
||
" ax.spines[['top','right']].set_visible(False)\n",
|
||
"\n",
|
||
"axes[0].set_ylabel('BEGIN → EARLYSTOP latency (s)')\n",
|
||
"axes[0].legend(loc='lower right')\n",
|
||
"\n",
|
||
"plt.tight_layout()\n",
|
||
"plt.savefig('per_subject_latency.png', dpi=150, bbox_inches='tight')\n",
|
||
"plt.show()\n",
|
||
"print('Saved: per_subject_latency.png')\n",
|
||
"\n",
|
||
"# Per-subject paired Δ summary\n",
|
||
"print('\\nPer-subject paired Δ = mean(FES lat) − mean(NOFES lat) & T-Test:')\n",
|
||
"for key, title in [('mi_latency', 'MI'), ('rest_latency', 'REST')]:\n",
|
||
" data = subj_cond_latencies(key)\n",
|
||
" print(f' {title} latency:')\n",
|
||
" for s in subjects:\n",
|
||
" if data[s]['FES'] and data[s]['NOFES']:\n",
|
||
" delta = np.mean(data[s]['FES']) - np.mean(data[s]['NOFES'])\n",
|
||
" \n",
|
||
" # Since data arrays are appended in order (Pair 1, Pair 2), we can run a paired t-test\n",
|
||
" # if we have balanced matched pairs (e.g. n=2 for FES and n=2 for NOFES).\n",
|
||
" if len(data[s]['FES']) == len(data[s]['NOFES']) and len(data[s]['FES']) > 1:\n",
|
||
" t_stat, p_val = ttest_rel(data[s]['FES'], data[s]['NOFES'])\n",
|
||
" stats_str = f'p = {p_val:.4f} (t = {t_stat:.2f}, n = {len(data[s][\"FES\"])})'\n",
|
||
" else:\n",
|
||
" stats_str = f'n = {len(data[s][\"FES\"])} (too few or unbalanced runs for paired t-test)'\n",
|
||
" \n",
|
||
" print(f' subj {s}: FES={np.mean(data[s][\"FES\"]):.2f}s '\n",
|
||
" f'NOFES={np.mean(data[s][\"NOFES\"]):.2f}s Δ={delta:+.2f}s | {stats_str}')"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 32,
|
||
"id": "2ba1928b",
|
||
"metadata": {
|
||
"execution": {
|
||
"iopub.execute_input": "2026-04-22T19:27:28.408334Z",
|
||
"iopub.status.busy": "2026-04-22T19:27:28.408256Z",
|
||
"iopub.status.idle": "2026-04-22T19:27:28.518108Z",
|
||
"shell.execute_reply": "2026-04-22T19:27:28.517764Z"
|
||
}
|
||
},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"image/png": 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U0AbXz9+VJFh7FtymClYK62qiYFEXpDoZaN+I1Tzvr80Nbnv1fw5u+zPOOCPmtteJxv+cgsXgd/QHWTopqzYsXrH2vXiCII098/++wfFcGjvlf49oQWQ8n63vPG/evKjrX5IgSHThG2yF0/FY1LZTAoVg4BftpkC+sPcqzyBIZVlxgqDCbvp9gwkiShME6YJFQYWOfx0LClJiffaDDz5Y7CBI29xfaaBa4uDxokqqWBdzwfVXsOynSgv/86rJ9mickf85XezF0yqostu/Hfxj6BRQe4+rNaq4SlIel/R7BC/+o11UilLdF1W2BANDr9zWxa9/W6klXkG/WsD9FY9+JXlNUXSe8IIOtcxrLGlZBUE6Pvyv1/GvsZAKgAs7P5V1EBQcBxNsoVIrTDxBR7Bbpq69gsekrmf8y3jjg0q6L8YbBPkrWHUtoXG/uvbQ+aEk3ZxReqTIriBKG/vTTz+F70dLbauUtEqpq5SxSj8bD01ceOCBB0Z9Tp/XtWtXl/43HmvXrrX69etHfW7PPfd0E0p66tWrF/H85s2bY3639u3bF5hUsmPHjjHXQxM2vvnmm1GfO+qoo8L/vvfee90kjvF+N7+TTjrJrrjiinAqYaVWPvroo238+PH2zz//hJc7++yzw/9euXJlxPvot4q1np758+fHfG7vvfe2OnXqRH1OqYIHDhwYVwpU/zoFt722c3Db77bbbnGvr1Ie6xaLzmX6vZSytCT0efFOlKe02P6U8ZpgM/ib3nTTTeH7o0ePdmmoi0vf9/LLL7c33njDpaUuC+3atXMpXf0pr5WCu6jtpt/qP//5j9vG+qv0+p9++qn9/vvvEctp39T3HTJkSKnXNbhOS5YsKXT5v//+O+K+JlQtiYYNG9oTTzwRcYyXhvYVlanvvfdeicqIeOh3+e/13P+nIi9NmaAU6H6FlbPBfeCggw5yE+8WRRPdanLJxx9/3N3X+irluX5H/2TD5557rhVHScvjkn6PoG7dukV9PDgBcLTyL/iY9xvp/Hrddde5m8yYMcPdPJrWomfPnu5c4v12JXlNUe68885wKvnHHnvMmjZtamVF5ZJ+O6WrFx2DuonOHTp/axmtb3B/LCu67th+++0LvUaIds0Uz/Gl6yD/tVes1+i3KKt9MRadV8aOHWtr1qxxx8CNN94Yfk77zX777WeDBg1yUynEO80DSqfsfl0U6oADDoi4//777xdY5oUXXnAXXhdeeGGxgqtYB+lVV10VEQBpbo7u3bu7Ak03FcZ+/pN5tAsUv0QfoLow804ynlatWlnv3r3ddwvOgRL8brVr1464iH733XddoaRgyP+djz322FKtpzdPTDSaFyYazZ+ifcAfAOl3PuKII8K/Xby/W7R9oywL9aK+Y1nS8eH35JNPWvPmzcO34cOHFwiaCts23slP83d9/PHHERcW77zzjl177bVluv7BgKo4AZYCxbPOOsvNBj9v3jx3wRK8cPvll1/KZD2Dc2589dVXbl6SWKZNm1bo64N0bGof7tevn5166qmunNKFwV9//WX9+/e3sqKL+2AAtMcee7jASJ8fvAAtal+piOOlospZXYx55UBubq4988wzEQG6KmdUqVBR5XFZiFWeBj8rWClUlGHDhtlHH33ktofKGT+dX1VhpYpIzTNWmtcUxl8RcdFFF7lzt3dTAON38cUXu8d1MR2P6tWru/XQHGWqNPVXzGnbKTBWZZKCTM2fFkvwuWXLllmyqKhzmALK77//3lUWqGJZgY//vK9KLlWOXXrppRWyPiAIqjAnnHBCROH77bffuoKwtAq7oPVPylqtWjU3CevEiRNdoKVb8IRbVlq0aBFx/+effy6wjL/GMUi1lP/rqlngpufkyy+/jCh0dbLVBa1acvTd/DUssfhbeXSRpwuBCRMmhB/TSUTbzaPt5T9BNGvWzNU2x1pX3SZPnlzs307bZvXq1eH7mkhXtWAKnPXdHn300Zjv2bJlyyK3vVfjF02wVUaBRmHfT7dYNbBlSb+3f2JRWbVqlS1atCh8U2tIsAZ4ypQpcV0EHHbYYREXgaKgSsdMoixevDjmcwqA/PuvlFWrlX5Pf43vunXr3ESv0eiErjLFT0FGYdQCof1YgY8CVV3EKSCqUaOGlaXgpNT6HJW7b7/9tvv8YGVCUDwXy7rQ9+vcuXORx4sC2bKw4447FghG451cu23bthG/01NPPRVxPjr55JNdRVG8SlMel+Z7xFOeBt9f+2xQ8LFgOaiWG5UPCtR1wawyWpMZe0GqAkmVlaV9TTxUzvlvqsTxU++GYK+FoqiCVIGxzld6nQIYHT/HHXdceBkdO2qF9vgv4L318p9PVXkSL53vgi3OwWuE4LktluBvp8qsoo5J77qipPticQJrXR/dfffd9s0337hJr7V/qLLG3/Kla5HCKp5QdmgJqiCaPV7dm/wGDx7sLmhVGJYH//vqBKGLPf9Jr7wu8PbZZx/bZpttwvfnzp1rI0eODN//4Ycf7KWXXirVZwS3mQpxryDSSeCGG24o8j3U9KzfxXP99de72hiPat79tA179epVoPYzuC66GNDJ5Mwzz7Tp06eX+rvpZON1RdT6FdblRNve36Vxzpw5ERddX3/9daHbXl2R/AX67bffHjWQ0gW6umWo1jERrUDl8Tq1kvp/X/2Ot9xyiyWK1kfBgQLz4D6hblFqvQzWMpYFXfxeeeWVEY/pvlrH/LRf6CLJf5Fw6KGH2sEHH2yVQXCb1apVK/xvdXvRBWlhgkGZAu0gdf3bf//9I4IBHRfBCydd0Oh3HDBggC1cuNDKggJ3/3dSuarfyV+G6QJPv1u0LtH+31jrpIuxknaFK015XNrvURTtk/5zn8pm/76sfUG/mZ+/S+Zdd90V0T1d303H2imnnBLxvv5uoSV5TaIouHn66acj1kVdYtUVTL0P/PzLBFvenn322XC5qYCquC1BQ4cODR836pIebOHS7xgP7U/+Y1dd+4Kt1V7QpvODAv7S7ovxlBXy73//2956661wy5MCYrUU6rzjvxbR5/krQlGOymBcEeKk+TCCkyR6A+SUqlPpW5VqMZjJprDECIUNcFbGtuBAbGUq8uZCCebQ96cfjWegX2HrEUyzq5vSg2qdgt8v2ncsiiZYDK6/EgQo25cGJwefi5VtTBl6og3cjZVdTHn+gxm7vPSZXgpr//P+waDxDp7UXBDBz/DSvmpAZ/C7Bbd9tBTZ2vbaBvGkyNbkctFS9ur7KbuNP6tgrO0aS7wpsv1JMJSsIpiMIdYEvUoE4h+MrcHZ/gkhi0rFrGxz/uf1XsrGV1hihFjr70+jHG2gcFH7vD+NszL6KWGDfgPNyxOcS0ZZnfTdyyIxgigJij+TkXdT8gmtg7ICBge9Kx20JvoMKmqbl0ZhiRGCGSyVWET7q8pabc/gcRT8PR555JEC21jHoH5Xf6prbdtg0hJln9JAbi9FtP+483//ohI7BPe34PF2zz33FNi+Ko+0jygVuNIdF7bNo2Ut1H5WXKUtj0vyPYqTECB4PtK+q+8ZLUV2cN28hEX6Hocccog7T+u3DR6DmpS3NK8pqdImRlCmPK9cVYIjJd/QXGZKphTcr/1ZKDWoP/ib6XeKlXwknhTZSnYTLUW2Er8UJxtbMNGFl+RAWfX0OygDpVd+BcvCkuyLSioVLA91bHnnAS/Lon5vPafyQJOwqjxRkpBg4ix932hZfVH2CIIqmNJPah6WWFlzgjedrIOFWrwXM0o/G+2iVzddyARnsy/LIEiZTmJltdI6KeNUYSf/eHgFSvCmbRucrC7WxbrSaUYLynQBVViqUhWK8fx+/sx98QZBokn+Yr1nsJAObvvCJkvVCT+YHU4pUoO/XVGTpRaVkSmWeN7Tu3n7fTC7k1ISF2dOLs0tFOvzo10cBif59aexjndyvGgn/uIGQZo3Ip7P0EWHl92wrIIgL/g877zzCp1w0LvpQi/WLOfxbPOSKiyI0H7sT4Xvv+liNDi3VPD3UEDnzwYZvEjxUzatYGrdWDd/AF/aIEiGDRtW5Pkk1jYPZsPSTROqlkRpy+Pifo/iXPwrw1cw62Gsyq/gxMXxTG6poNef+a0kr0l0EFTUTZVjfrrw96ea9t8UZAQnUS4sCFJgoQAj1vVCMD13UedSZUQdMmRIXGWXKpvK4pjq379/zGW9jJexjpHg8VLY9QfKFkFQgmj+iuuuu84FIpqjQHOU6KaaI7UmqMBR6kpdpAcV52JGNRCqjdTJXAGVahx0Ea1aBp2IyisI8i5C7r77bld7rO+m2p1+/fq52vGiTv7xUEGneSHUsqX3V2pr1V5PmTIlrosHj+Yn8C+rE5ha7QqjE8C9997rWrb0m2myRG3fli1buoto1UQFc/0XJwjyJm3UvqD3VS20TtBvvfVWXNtegZDWT6lqdRLROmpGbs3zc/3118d10tSksVpH1Q4qeFKtoLaxarC0f+rCr6jtFBTPyTa4Xv55VnTzJkCMd94af6BW1IlMPvvss4hldCL1fsuKDIKUflkT+anSRC0vTZs2db+l9zvoAl8T+WrW+KKUJAjyt35q9nV9no5h7es6RrRvaT/46KOPCn19PNu8pIoqR5TiVxdDOi41PYC2oY73P/74I64ySCmqVWGk7+2/KAoGQaILWr2HatAVZOl3UgWLarf1HkqNrRaT4qx/vOWYUqlrwmu1vqis12+kihrVRg8dOtTNCxcrOPC37Oq1/pbTii6Pi/M9SnLxr2Nbx6EqGFR5oPXUBbhaCDQ/S7Tad1UwaB9S+av9SGWh1ku/sX5rtYj4p5co6WsSFQQtX77cpbnXcaHfTtcjOlZU1mjd1YoVa/JOBfSnnnqqO7/oNQoovN+pOCmyVR6p9Vlp6rUOOudp/1EriX/eLY/mcPO/Xqmno9FrFfyqFUjnUB2T2q+UCv6UU04JPffcczF/h+IeU7qv31zbIDihuRcEqSzV9Ze+l86rXjmh/UOBo1qYvXTdqBgZ+l95drcDUPGUFCBa6mn1VVb2Lm8QqsY5aQBzvINOAaQODcxWcgdvfIOyUhaWeAWoDJS0xp9BTYk3Ejl+E8mLeYKAFKTB6RrgrmxVSv3szeejwfT+bEJKx0kABKQPZf/SQHiVA/4B3souqAHtQGWludCU3dSfaEn+9a9/JWydkNxoCQJSkDLOxMpQ41G2Qp1Myiq1MoDKT5UhwVTAcscdd7j5bYDKSnPrzJ49O+IxzfdXFtONID3REgSkIKW2/vDDD91cBEpVqtpfpf5UFzm1Dp122mlusj4A6Uvznu2yyy6ua5EmrgWSgebv01xXmstvyJAhiV4dJDFaggAAAACkFSZLBQAAAJBWCIIAAAAApJVSB0FffPGFZWRkuNs222xj//zzj1WWwZ/eeunWrVu3RK8S0ozG3/j3weJg/0V5Ov300yP2zcmTJ7PBgSLoOPEfNzqOiuPmm2+OeP2oUaPY5ih3S5cutRtuuMFNj6HrdCVDatiwoRtXpWvjiy++2GWM3LJlS6H7e2E3vW88r/36669jruduu+1WYPngMfb888+Hn+vYsaPl5+cnLghS2t3LLrssfP+SSy4psCFSFYUZ0glBGQCkFq5jUt/nn39u7dq1c8mSZs2aZWvWrLG8vDxbtWqVzZs3z6ZMmeLmBjv33HNdAqXy9sgjj0R9/JNPPrEffvihyNcrq62X3fLHH390wVvCssO98cYbNmPGDPfv6tWrRwREiaZMWMcff3z4focOHRK6PkBxsP8CQGpp3759xHVJtAmtgbKcDLl///62evXq8GMtWrRwQZEy7P39998ukNBy8ahZs6YdeeSRMa9Z4vHaa6/ZfffdZ40bN44rOArKzs62K6+80k3sLDfddJPLdqt1q/Ag6OGHHw7/u0+fPtagQQOrLBo1auSCNCAZsf8CQGoZMGCAuwHRqAtZ9+7d3b8nTZpU6mEcH3zwgS1evDh8X93ehg8fHrFMbm6uTZ061U1EqwCjvK9LNm/ebE899ZTrnudRi9R7770X93ucdNJJbmJndd9bvny5vfzyy3bWWWdVbHc4zdqrZjZPtDkGonWh0SzVt956q+26666u9ahJkyaueWv+/PkxP+vPP/+0a665xvbZZ59wf0b9GHq/Bx980NatWxfXZxfVDPzbb7+5iLJZs2ZWtWpV1+Q2dOhQ27RpU/h1Wk7L33LLLRHvN3jw4Jh9fadNm2Ynn3yytWnTxkWreu+mTZu6ib/0uscff7xAX8zKINo2+vnnn90OqN9Nv59qtu69995C11/NnKeccoq1bt3afX/ddt55Zzv//PPt119/jfoa/V7+z9bvqRqEQw45xOrVq+ce+/bbb+P+Llq/xx57zBUwWnf9BrVr13Y1cfqsq666yiZOnFjkOhS1fYry+uuv20EHHeTm59D36NmzZ9TxGPF2P9P20xwfu+++u9WtW9d9L02Uqtqf//znP4Wui44rTY64//77u/7B3nG199572xVXXGFLlixxy+nzg5Mrqgm9JGPuovWp/+uvv9xxoN9F+0anTp3s1VdfDb9G8x3p/bXN9B21zTQWMZaVK1fanXfeaQcffHD4e2277bZ22GGH2XPPPecK/WgF8z333OMm3lO/ZJUB2r9r1Kjhtmfv3r3thRdesK1btxZ4rVcmeDftF9p2qqlq1aqVq3Hbfvvt7YILLoiokSvNvlke1Fe7b9++bpvpe2s/eOaZZ1y356Dx48e776N9Weup30XbWRVh2p+uv/768P4T5N9Weq22/V133eX6d+v393ep/v77793JTecL1TTqM1SDqJZ9lakPPfRQpRmHGtwHb7vtNjvuuONcrav3u+o76FhSa8Dbb79dJsdnrH1w7ty57ty63XbbWVZWVoGeGqoBvuiii9x298oOnZf+9a9/2bPPPut+l2hKcj4rr3Ogykl/+aeLOG0r7S/axjqm/ZNGx1OuFncsp64/dH2i85uOdZUXOvZ1cRYUzzlDx9u///1vt++o1l7lkMoD/U4qC4qaBPujjz5y12M77bSTe51er/fR76rtXNLrmOKOMXz33Xfd+VrroPJX56Q5c+a45fVb6/jQOnrbTPtiYceyunJ5ZYH3vXQsaa4gPRfrOvXqq6+2ww8/3I1/UfmkfUT7irbnOeec4+bSiyba+f/jjz+2I444wurXr+/KSO2/OqdUVrqm9fMCLL8qVarYoYce6s5v5TmcRedAz5NPPhlxHh4xYkT43OpfLhZt/169eoXve/t1iYRK6KabbtKZ0d0yMzND69atK7DM/Pnzw8votueee4b22WefiMe8W/369UPffPNNgfcYPXp0qEaNGlFf491atmwZ+uqrrwr97K5du8Zcf92OP/74mJ/Tp0+f8Ouef/75QtfFu2k5eemll0IZGRlFLr98+fK4t/2yZcvc+hb39uijj8b9GdG20cknnxyqXr161PU//PDDQ1u2bIl4ve7rNYV976pVq4aee+65Ap+t38u/3CmnnFLgtdH2l2i2bt0aOuKII4r8DXr37l3oOmifKmz7eL+5p1WrVhHPDxkyJOrnav8Ivrao/VceeuihUHZ2dqHf6dxzz3XfP+ipp56K+Vt6t0mTJrll49nfo61fNHpP/+sOPPDAUKNGjaK+58MPP+xu0Y6fatWqhb788suo7x/r/bzbAQccEFqxYkXE63T8xfM9DzvssNDmzZsjXhssE4488shQgwYNor5+7733jjhOSrpvltZpp50W8f6XXHJJzH1p8ODBBV6v9SlqnbfZZpvQrFmzCrzWv0yzZs1C3bt3j3isXr16brnJkye737moz5k5c2axvntJys4bb7yxWJ+hdYpnfxo0aFCpj89o+6DOWXXq1Il47NJLLw0vf/fdd4eysrIKff/ddtutQJlXkvNZeZwD5eeff3b7SlHvO3bs2GKVq8Fyu7Dyq1evXqF27dpF/Vy9z4IFC4p1zvjnn39Chx56aKHfp27duqEJEyYUWG9dgx199NGFvlbrVJLrmOKWJ3379o15nffTTz+5cj/a8/vuu2+B6wi58sorC92H9Nztt99e4HX33Xdfkd9Rx8HTTz9d4LXB8/+pp54a8z3uv//+UFnw71/+47ukHnjggYj1bNOmTeiFF14ILVq0qNjrY779pySvVVm38847h++rXJA1a9ZElFV33HFHxOu0b0Xz2GOPRSz3xx9/hEqixN3h/LXXiqgVmRfFq7lXzZhqpzSeyGvFUQ2pamE1MMprklNzoGom/NkfFM2rxmX27Nku44UsWLDA9VPUa1VTVhJvvvmm+9wDDzzQ9Y/0tzKoRuOzzz5zNcuqJVIN008//eRaRTyqvVatb7Cvr2p+vJpU1cbtt99+bh2XLVvm1tvfVBmvDRs2uPUtrnh+o8KoyVG1L127drX169fbV199FVH7dPfdd0c0capmR6/xqBZG2UlUA6Dtqdog3c4++2y3vaLVUnheeukl9/uoxk+1qqrhiZdaDdQsHFyPzMxMW7hwoWuF1Pcpbw888IBrYVBLg/ZV77fX/nHeeee5WnXVjMXjlVdecc3BHtWsHnDAAa6WdebMmbZixQr3uJqddazdeOON4WXVnK1BkH6qAdK21T6ibavt4tH+rmPi/fffDz+mmj3tB6Udc6fWZP0OWnd9ho5rj2pXta+o9ly14TrevG2mWmrta9rv/LVe6pbr/y1Va67vr9eqyd3bH9QlRS2UQfpeql3UPqIaStXoq4VELdii1jUNIlVNfCzaTqo5VMu13sPfYq73Uoum13JeWfZNdZFQS5vKJ6+fuD8bj45NtSoEaxBVlmud1aqpbaTXeTXVqtU944wzIn7TILVm6Kb9Tr+V3tOrvbzjjjsiWiP0vGqM9Zto26ilpCRKUnZ6x1Nxad9r2bKlq7lU+aVzls4tXquHuqCo9U21/iU9PqPROUv02To2db7RPuV95rXXXhuxvMoklauqUfdq49UKp/Oq1lf7cUnPZ+VxDhT1AtEgb496JailSYO7tQ/+/vvvUVtuy9KECRPC+6aOn+nTp4d7jmj/VAtJtHImlhNOOCFiee0/e+yxh7tOUjmi76Pv169fP3f+VauIRz001ELrp+2xyy67uDLE31pS3OuY4ho3bpzb5/V+2n+8VjFd5+kxlfUqZ7V+6lXgtQro3DV27FjXauhRK/H9998fvq/zQefOnd2+pG2i76b9S63PavFSy5CfymJdN2r/Vlmlz9Jvo+8uur5UNzG19mt7x/Liiy+6FiSVz2rR0r7rUe8m9WwpzrgUtaTrGPDztx5qrEvwelat4MVp9VBLnJ/OgertJGqJ3W+//VzZrvNhYd/dv37a90rS1VO/g7azbt45R7+zzi9eHKB9Q9fg8dA+EIxJvO9WLCUKnUKhUO3atcMR2EknnRR1mWCti27Dhg0LP//nn3+Gtt9++5i1Nvvvv3/Ec5dffnm41ky1HsFI/ZprrilxS5BqQVXz6FHtp//5m2++udDXx6oxqVKlSniZ2267rcDz8+bNcy0069evj2Orx96u8dxiRdSxBL9jzZo1I1pfnn322YjnVfvt1ZL/8ssvETU3qt3KyckJv/bXX3+N2If0W/sFf1vVKn/++efh57UfRKsxikY1Dv73+uuvvyKez83NDU2ZMiX02muvlWtLkH8bbNy4MdSzZ8+I5y+88MK49t/8/PxQ8+bNI2rT/eumfUktDv7fbeXKleHtppZT/3ufeOKJrjbG7z//+U/ot99+i2t9iiNYO6TbmDFjwuumVhr/c9pHVOMrS5cujagdVyuifx/wtzpq3/vggw/Cz+m91Srmf+/3338//Lz22++//z5qrfzff/8dsa/ut99+Ec9Hq1V98cUXw8+r7PA/d/rpp5d63yytYM3tdtttF7EPXX/99RHPd+jQIeL1+k02bNhQ4H21/QYMGBDxWtX8+gW31V577RVRM7lp0yb3d6eddgovc+aZZxb4LL1m5MiRBbZZUUpSdhZ3f1eN/pw5c6I+9+OPP0a8t7aXp6THZ7R9cOjQoa6s8G9X3ddv7V9OLcoeHWPt27ePeP6JJ54o1fmsPM6B4i8/VbYGqbX35Zdfdsd1ebUE6eZvRZg9e3aoVq1aMVsqCztnfPTRRxHPDRw4MJSXlxd+ftq0aRHn1BNOOCFifwi2bui7++maST1rSnIdU9zypEWLFqHFixeHrwWC20yt5V7ZPXz48Jgtz6tXr47Ynh07dgyfy7z9VZ/lL8f8+7xa4tRzJp6WhMcff7zQ8/+OO+4YLmtU9qlM9D/vv36MR3A/i+dWnJYYT1G9cex/51JdP/v3t1j7e6yb9qXCXqt9RPugv/X2iy++cK1T/muBaK+LRuds/3IXXXRRqMJagtQS4a+dVO1pPBRFK1r3qJZK0fB1110Xfkw1rYo0FSGrVsUf/asPqddHVzViSvnnj3RVC6LWiJLQZ/prto866igXoXpKWlulWhX1zfbXJKj2VGNi9P3VquVluYiXamei9dMvbxrXoz6wnjPPPNONB/JqbpVyUTXditBVE+lfR9VeRatJ9qhVULUMsVryhgwZ4loLPNoP9HqNsdEtGvV3Vi2ov2ZLlFlEv69qh1RLphqrLl26WHlTbZH6EYta1FRDqj7GnqLG8Hi0jf01waql1Xfy8x+fqnXTmBLt43qtvwZL21v9/4OZXdRHuCKo5ctrFdFvqhYf/3gftQ57tZ2qBVNtrzfPgGrTVUOv1jXVkPprQVUjp/EsunnUwuGn5dW/22tJ02vU5141SqpFVu2UUokG/fLLL4V+J+3/OlY8ap3Sbx2tLKks+6bKIH+tr8pk1dR5KVPVwqPtp9pDUS2uykeNa9Fz+h38YyeD20tlXiz6HH8tpNfqoG3jjSFQ65oyCul4Vtmpz9dr1NJUXBVRdqplTLXNOr9pPIz+rWMy2pwW/v2prI5PbSOdL73WH2+7qqbdv/9pO2pMjUfHmMbB+stqHSdqqS7p+awkr4lWSx6sCfcfO/pe+r5qNVGZohYGjQ1S60h50mepJ4NHrXWq3faXOyrXVcMdT+uJn/YDtQz5qZzyWkfVCqVyT79xcHyZxroEv7uumYLn4PKilkyVy6JyLDiHpMoX7/wfHJflH/OkbafrTY++r75brONZ+7aOIW97q2VI+6/2O7WcqdVZ58NoZUBR5bp6JqglWnSu6NGjR0SLeUmvEcubWn7VW0s9UdSKHs2WLVvc+DntX7pOKS/aB1Vmayyn6Nzv9dDQuUUtSf6eE4Xxxs561zpez7DiKlEQFBy8pkItHiqYvItAj34cP+8EEOzqoMI6eCJQE75fYckVihIspHQS84s1SLQouvhRwaODzhvE7v8MFQDqNqZB25Vd8LcSXZT4B9/p99NFYPC30ElKt1i0fTTwMFYQFGvgvZq0Y3Vv0XYVNa9qYKTXdUrdkXTz6CR89NFHuwGUXsFdEdsv1r5flOC21XYLJm2I9Rpd3PupG0e8qS3Lg4IaP3Up8Qt2sws+7x2XKtz9cxzE02XUvx0V+GigpdftrTBFzaVQnLKksu6bCtJVXvsHDWv/1IlKFxEKzPzdYUu6vXQii9X9QUkBlLVIJ2hdYGgbeHQRou6jugDVgOvKRt1VVe7HM5Gff/uU1fGpykF1FwoKlhM6voKD/ws7r5bkfFaS1+gCP1p3R3/go+7A6jqlLnHahv4uv9qv1NVHXaN00RVtW5TXObGsynV1EyuMKmlU7umcGdxvKqLipDDRym3/daP/+VhlerRtovO9140tFr3GK4MVTD/xxBNxrXNZluvxiHbOLuvscKJ9XxUbqkhWeaqbKmYUbGwKVFypQkrd8GIdLzr+irrWKIqOdaXDVkDrBUCi7oQ6botDsYcXBJU0QU6JgqBgBonymGApGKnHk6WlNFRr5FdWhaZqhFVbpLEZ2sF1gHrfTYW3an90U2tGvCdztZhohykuHVzFbXWqSP4an6B4+qvGon1H6ReV/UQnTbU6+bN06QSidO/qi69+8LEypARbBaLVVCbjtk2k4Lb211xHe768tomOC38ApM/VRZR3glZLRLxzKRSnLCmrfbMiKZOdPwDSb6YLBGX10b+D4wwKa3lRP/3gb+4vrzSeQDX/GiehyhYvqNBvoVZU3dRCFGwJLUysPu2F0UVbMJNWLAratD/5AyB9z7322isc0PgD9PJomYpVXpb2vFqS81l5nAO9ChQdE9oflUFS+5031kp/Ne5UN41J0zi+aKK19EbL6lZZqQwr6TjoVC/XVekaDIDUKqUWSF1s63dWQBDvcVhe14gVRd9ZFQ1eZYPOd8OHD48YH6jjUS3+8WRoKylV7Km3wzvvvBOxbsFxkPHwxx4l3adKFASpINfN29liNbEFKepT5KlaRo+/OVHUPB5tQJ4uBvR5/loxFYB+FTnxWHFOHrqY0k30/ZUSWF1+FBF7A8JUSMd7AkhUYoTgbyXBWplYv59SIpZkJ/fEulBSLaO/q1EsGpSs7nu6iS401UVD6S21bqIuZkpNqmQcEqyV0H6ubkoe1aYUd/v5u/TF2veLEty26jKmmud4BFNdq+tA8LiKprwrIUpLJygFLN7xpFYTdauIZ721L/j3Y11A6r5X06eL2Xhbu0uiJPtmWdO+qBYnj8opfy2d17VEdGHpp3Tm/rJLXaf8QVBJjmuPuk0pfapoQLO2g/ZZtSZ43Wb0fHGCoPJOjKBt6Q9kFfx8+eWX4fJEFxmx1qGkx2e82zX4/lpXXfz5j5OizqslOZ8V9zXx1jZrn1QXeN10nKq7kxJHqOuSN/u8uqZpYL2uO6KV6cHtHW9lh0RrlSircl0JU5TWOh7B31UX9zovFKWyl+vBbaILdiVKiEewnFKrkAJmf7nlD4JSkcotncf8Qw886pV1zTXXuCENGsrgibZsWVP57Q+CtK+qoqg41PLm7/Zf3NeXep4gZT4q7OI4VtSm+Ts8OqEFM114fZ3V99crNEUnAjXTedG67vubv0XRZUUJduuLlbtfJ2gdaF6toApi1Yqpr6+/Bic4XqEyUoY2f1Y2zSHgn+dH4xfUfcP7LfwFrMZvRbswUjcXFUxexpDyoO4Iqk33n1i1rsry4s/KFPwdgrWpI0eOdH+1D2o/Lk6GOtH+6zU/62+wZjnecTg69vzrpguqt956q8ByurhQ64J/hmf9Pt7FrKg2THMvBOfa0j7r7+YY3N8rW/9nXfT55w3QxZD6nQfnBFLNr2qjFXB4Yw6Dyygo8cal6LdWFrriXBhVxL4Zbb6l0tAx6O+2o4tKfy2bat297njB7eW/QFcGKpUTZUHliy4Evdp9nZx1sXfssce62sTKWnYGt48uvL2Mp/ouuvCIpaTHZ7z0/v5ulapc9LeS6POC42r959WSnM/K6xyoSgGVe15lrGrmNWZD5YDG5ni0zb2gVOOX/Rd52oaffvpp+IKxuD0ldP7zzguiwCu4/8dbrmvsoJ+6f0a7rlDlhMZv+MduHHPMMRHLPP300xFzrXk1/8F1i/c6JlHUauFfR7XsRKt8VDCr1nR/VrnCyint5/5r0VSl8lMVtzqmo3Uv/eSTTyICIB2PFdGyqPFUqhBW5aVu/i6y8fIqOaLFJMVR4hTZ6qrgRdFamXhrqzR4UQWXCmJ1/fCfaFUw+g9mpUhVTYiX5lIDuxQ96gSobhL+gVD64dTnsaL4U1N630t9eL0aYw3EU2GvAlLN8WqqU62m1lMXYupr75/srrCBw5UlMYJ+Yw1c103/Dk5Qph3Zq2nT91FfbO8EoYBXXUq8lMUKAlTb7fX59SelKGs6yNV/XDcvLadaxfS4P/mGt94ebwIxj2oUdeJV4epPzRovdd3RZ3spsv0nHF10X3LJJXFf8Osk6A1y1foo3akKOy/Ftra3gs5gdw+9Vt2H/LWEOlmqsNSgYm0X1W7qd1GfZHUd8CollF7UKzA1YF1JMvR9dBGuCzUvyUCiqEVQg2C9iyLVGGr/0/bWGBKVF6qw8Z73tp++m44pLxBRMKDvrQspXeRoP9V3LI9jrqT7ZlnTvqixDDq2dTEaPMH4x+NoGX+6dAVrGoOgY9pL41sWNNhb3aR0XlEQ5tX0af/0j4Eo7nYp77JT5Zy/p4R+R50vdGyq4qSwC82SHp/xUqCg86o/oYTKHSVf8FJk+1ux9P7+ZUtyPiuPc6DofKuxBSo7vWk3FGzqePW30OgiS8e46Pyk8VLe5MPaV3XuUeCpip1o3eOKorJPF+deimx/t1qN6VCFRjxUfuqc46XI1r6ickldTbX+qvVWeeTtP/50wAoWVNnlHZcKOJUYQRU4+g1ViaMurCrD/Ulb4r2OSRRVCGlsoDf1hs67mqpEZZW2jc59Krd1PtJv6R8zpnLKT8eVAl59N7XMBisWKlqs5B86l4sqJ4LdOIubIts7n2lMkG5qldT+oPOhHv82MOG8N1luSVJki46DeIOoeBMgxKLf0K+wKVYKVaKccv9LBelPT/fuu+8WWCaYjlITYXXp0iVqej2lQA5OeCqaSLOoSeOULjg4YV5xU2QHU0MWlaZPKY6DqUz9N2/y2D322KPI1IKaQEzbs7IJbqNzzjknIlWw/6YUpcGU1UphGE96Ru/1xUlPXRxK6x3POmjCV3+KSK2/P9W0/9a0aVM3iWJh+1AwBeYZZ5wR9b2U9lTpxv3iSeX64IMPRqSfjXVTutRo6UGLmogyOFnbVVddFXPZESNGxPVbFHVcFXVcFrVffPLJJ6HGjRvH9Xt/+umn4de9+eabMSfju+CCCwpNmxtMTxxMFVrYb1nSfTPeNKLxprTVfU16He2zNcmdn1LUKl1stGX1+HnnnVfobxhvytdYEy76bzo3KLVwZaO007HW+Z577ilyGxT3+CxqHwzSxJKxfm/vplTZSl/tV5LzWXmdAzX5a1Hvq+84atSoiNdpqoVY5eaxxx5bIIW4X/C400S/O+ywQ9T3Uurm4ASORZVvSgmtCZnjKROCaePXrl3rJm8t7DXBfS3e65jilifBc0dh5WdR5zqljddE4/FMuKt0y/GUISo3brnllkLL0NJOkVEZUmRrqoZ437tnz54R05gUN0V2cBuV9BwV7+v8v62u00qqxN3hVEuq7Dwe1RgURdGnasNVE6UaCNXgKGpUzYRqoLyuVMHIVLU66vOtvtWK4lXbo9od1egouletZTwpKMuSakdUm6QaO2VMijVITqkAVZOhKFU1vaot0rLqp6nvqxpW9cH2N99XVmq+VM2BmpxVI6FaNQ00VI27svkE+5LqeTW/e5NYqQZCNaT6/qoVVEuCuiVpPIu/f2hZUw2s0vmqxk77kGoMte9p/fRvtTaqtlID1P2/o55Xik7V2Gg5fT/VGKrLhGo2o2UGKow+Q+uhmkEdC6rVVc2fPsMbD+LxugAV1k9XrQdq2VALqPYl7VNaf21j/S6qsVFNUrSJFfWd1FKkrjk6drzJHHVcaRtddtll7j38dNyqW6Nq5RNZO1hUM7tSnaqfs2phVb7oe2l9VQumTGyq7dQxpxpFf2uGyia9RttPv4+2qVr//P3IK8u+6a9Bl9JmEVJ3OrXsqzZZ+4K2l1oeNCbJP1WAqDZZ4zm0zir7vONC+5QGI5e0b3aQplNQl1FtA7WQqczQNlAZqmNPx6HKo549e1plo+NHWf7UpVvbUuus86V6Qfhb1WIpyfFZHOoqqm2nBDs6nlUW6f1VrqtVQb+7Wg783Q5Lej4rr3Ogxp6pRVxj2XRu0X7pL/907aCWmeAEijqPqRVN31PfW92t1JVGXcjUtbg4YyJUpmg7qTVNrRDecat107EQTIFfVLmufVyZInU+VHdBbS+tn/fb69yhfUPPBwf9a7uqnFBrkM7ROmZUjqk80UB3HUfBfS/e65hEUsuExnRpO2t/1bHv7UO6HlTLq64hNYYymIFW3cFV3quc1bZWd0j1NtJ+kegMehVBrYFqcVHXSU0Gq+PE23bar1q1auW6F6usUnKRYPfIyko9Jfy9EXRMlFSGIqGSvlgZi7yBjNp4aqZVYe1RM6V/wJ6anXVBjOSg7kX+cSu6GCrt2APERyc5zSTvUapXf9c8pDdd2Gn+B9FFYHCOEQCVjypb1KXaowCkxN14gDT12GOPhadAUcWNYo2SBnAlbgny+i56/S7VD1YDfAGUnC5mVWsaTIEeb5YgpD7VW3nzCqmlyz8xI4DKRVms1DKtlil/ZYVawoLjVgAUTuP21DLoUUV9aVqwMkvbTOnN/CoapFjSCYsA/Le1Td0L/dnX1O1TMykDoq6YXiYtdeHxBn0DqHxUQaxujcp26E8aoq586q4GIH5jxowJJzFSV0hNmF0aJc4O5+9fm4hMZUAqU/9l9ddVd1ONjfBS7AIaS0eZCyQfjVfSmC6N4wymtQZQNLWoluV8eaUaEwQAAAAAyaZU3eEAAAAAINkQBAEAAABIKwRBAAAAANIKQRAAAACAtEIQlGQ2bdpkP/74o/sLAAAAoPgIgpLMvHnzrGPHju4vAAAAgOIjCAIAAACQVgiCAAAAAKQVgiAAAAAAaYUgCAAAAEBaIQgCAAAAkFYIggAAAACkFYIgAAAAAGmFIAgAAABAWiEIAgAAAJBWCIIAAAAApBWCIAAAAABphSAIAAAAQFohCAIAAACQVgiCAAAAUlgoFLLNmze7vwD+K/t/fwEAAJBCNmzYYO+9955NnTrVVq1aZQ0aNLAuXbpY7969rVatWolePSChCIIAAABSMAC66667bNq0abZ+/XoX9MyZM8d+/PFH++6772zo0KEEQkhrdIcDAABIMWoBUgBUo0YN22uvvWyXXXZxf3Vfj0+YMCHRqwgkFEEQAABACtHYH3WBUwtQ8+bNLSMjwz2uv7qvx6dMmcIYIaQ1giAggAGkAIBktmXLFjcGSF3gvADIo/t6XM9rOSBdMSYI+B8GkAIAUkHVqlVdEgSNAVLFnj8Q0n2d7/S8lgPSFUEQwABSAEAKUdCjLHBKgrBw4cJwlzgFQLpfu3Zt69q1a4FWIiCdEAQBgQGkO+20U8TJwhtA2r9/f7YVACApKA22ssDpHPbNN9+4LnBqAVIAdNBBB1mvXr0SvYpAQhEEIe35B5B6AZB/AKlOHhpA2q9fP2rNAABJQUGP0mCrEk/nMG+eILUAKQBiniCkO4IgpL3iDCCtVq1a2m8vAEBy0PlLvRhUiadzmMYA0QUO+C+ywyHteQNI1U1ArUJ+DCAFACQ7BT6qxCMAAv4fQRDSnjeAVP2kNQbIC4QYQAoAAJCa6A4HRBlAqgQJOTk5VqdOHQaQAgAApBhagoD/9Zu+5JJLbM8997RNmzbZn3/+aZs3b3b39TgDSAEAAFIHQRDwv3mChg8fbt9++63rN92qVSv3V/f1uJ4HAABAaqA7HNJShw4dIu6vWbPGVq9e7cYHZWdnh+cJysvLsxkzZtgLL7xgdevWDS+vCegAAACQnGgJQtpTsKPxP1u3bnUBUG5urusSp7+6r8ejZY4DAABAcqIlCGnJ35KjsT+DBw+2xYsX2y677GLvvvuuLVmyxJo1a2Z9+vSxX3/91bbbbjt7/vnnmScIAAAgBdASFMOcOXPs5ptvdpnBmjZt6gbGt2/f3g2S1wVyPEaNGuW6VUW7derUqSx/R5QC8wQBAACkF1qCYhg5cqQ9+uijriVgwIABLmXyl19+aY8//ri9+OKL9vnnn9uuu+4a10YeNmyYtWvXLuKxhg0blv7XQ5nOE6TWIc0TpO5vor+6r/mDunbtyiRzAAAAKYIgKIZ+/frZtddea9tss034sXPOOcc6d+5s5557rt144432+uuvx7WRe/bsad26dbNkFcrdYrlLF1gq67nnrjZj151swieTbOXKle4x/f1j7hzrdWh3O2yPXWzLwrmWiqo0aWkZVaomejUAAAAqDEFQDLG6q5144okuCNLEmsWxfv16q1KlSlKOKVEAtGRoX0tlOXlbbf13yy1v2ToL5ee5x/Q3b9kCWz/1Lfv7n0+tZnZq9h5tdtc4q9q8baJXAwAAoMKk5lVdOVq0aJH726RJk7hf07dvX6tTp45Vr17ddtppJ7v33ntd6mVUHhMXrbPZKzfa9jWrWP0q/z0s9Ff39fikResTvYoAAJSIspsqCRBZToH/R0tQMd1www3ur7KJFaVmzZpuPNFhhx3mMo0pgBozZoxdc8019umnn9q4ceMsMzN2HLps2TJbvnx5xGNz5/63S5bSN+tWEfLy8y0/O3W7S+mk8OXyTbYhL2StGlS3n/7ZrBFBlpmVaU1qV7OfVm20L5ZvtH+1bpiS44L0+2ZU0L4EAKg4mt5hwoQJ7ppDc+HVr1/fDjnkEOvVq5dL+ISyo94+SC4ZIaoF4nbnnXfaddddZ8ccc4y99dZbJbog1uY++eST7dVXX7VXXnnFda+LRdnpbrnllqjPTZ482aVzrgi5K5bY6tG3Wyo59rmPI36TZes3Wf7WkFXJyrScLXmWHwpZVkaG1ayabbn5Wy0rM8Ma164e/s3/fUZPSxX1B11vVbZtlujVAACUghL4+Cm5z6pVq2zjxo3u36p09f4q2VODBg0iKmKnTJnC9i8FZRJGcqElKE6PPPKIC4CU4OCll14qcYuAXnfTTTe5IGj8+PGFBkEXXHCB9e/fv0BLkIKwevXqVViGudzNayx3+e+WSrLycyOCoGwLWZ6ywmWETL3hskNKZa6zSL6FtoYsOzPTvcb73Wun0PZoWKemVSFbIQAktaysrAKtQJr42wt0dK7Tv3XT4wqO6tatG16erLVINwRBcXjwwQdtyJAhduihh9o777zjurmVxo477hju7laYxo0bu1usZteKanoNZWVZVt4WSyUfH9U64v74P9fYi7+ttuqZGdakRpaFNJ9TKGRLN+bbpq0hG7hzA+vd6v9PFpZC2yM7K4tmfABIcj/99FP43wp4Lr74Yps+fbrttddertLVmwT8qKOOsm+++cb2339/GzFiREp28wbiQRBUhHvuucelyj7iiCPs3//+t0tuUFq//fab+0vTaeXRY/s69v3KTS5BwnerNlmGhSxkGdawepZ7rvv2tRO9igAAxGXLli2uK5zG/QSDHN3X43peyyVj1lqgLJAdrogxQAqAVGvy9ttvxwyAcnJy7JdffnG1LH7efDN+ygo3dOhQ9291a0NlRc0YACA5Va1a1Y35UZe44NBv3dfjel7LAemKlqAYHnvsMTcGSKmwjzvuOBs7dmzE87Vr1w4HMTNmzLDu3bvbaaedZqNGjQovs9tuu9nBBx/s/qoJevHixW4s0M8//+zGAh177LHl+duihCmy99m2hmsFUmvQ3zl54RTZEd3hAACopNTa06VLF/vxxx9t4cKF4UBIf3Vf1zBKpEBXOKQzgqAYZs6c6f4uXbrUzjjjjALPt2rVqsiWHGWBU7aViRMn2po1a1zz8+67727PP/+8C5gofCoHnRSmL82xDblbbYf61dzv8t92oAxrWjPbflq92b5cusF6tazDbwYASAq9e/d2E7tPmzbNTdgu+quECAcddJBLkw2kM4KgGNSi42/VKYwyxkXLNH7//feX7tdBhdiyNWRrtuRbzeyMqH2na2RnuOe1XLUsuskBACo/Vbyq+73mCbrssstcAKRscMo8yzxBAGOCAKuamWH1qmZZTl4oat/pjXkh97yWAwAgmQIhTbXRtm1bd19/dZ+JUgGCIMC19uzfpKbVqpLpxgD5+07rfs0qmda5ScEMOwAAJAPv/MV5DPh/dIcD/pci+5fVm23W8hw3Bkhd4NQCpACoU6OapMgGAABIIQRBgJnVzM60Czpu67LAKQmCxgCpC5xagDRHkJ4HAABAaiAIAv5HgY7SYCsLnJIgaAwQXQcAAABSD0EQEKDAhyxwAAAAqYs+PgAAAADSCi1BANKKsv5t2bLFqlatSndHII1tyQvZgpW5lg42bgmF/85dusVSXcuGVaxqNhldUTiCIABpYcOGDfbee+/Z1KlTbdWqVdagQQPr0qWLm1WdOTOA9KMAqO+IJZYO/li02f39YdHmtPjO4y5uZm2bVE30aqCSIwgCkBYB0F133WXTpk1zs6Yr6JkzZ479+OOP9t1337lZ1QmEAABIH0kbBP3999/25ptv2qRJk+z777+3ZcuWua4tjRs3tt1228169Ohhxx57rDVt2jTRqwogwdQCpACoRo0attNOO7myQt3iFi5c6B6fMGGCm0UdSEd0EQWQjpIuMcIPP/xgAwYMsFatWtnFF19s48ePt61bt9ouu+ziLm7y8vLs3XfftQsvvNAtc8IJJ7jaXgDpe4GnLnBqAWrevHnEzOm6r8enTJnilgPSrYX09ddfd+fSwYMHu7+6r8cBINUlVUvQ+eefb88++6w1a9bMrrzySteXv1OnTm6As9/mzZvtq6++csHQSy+9ZHvttZedddZZ9vjjjyds3QEkhpIgaAyQursF533SfT2u57VctWrV+JmQFugiCiDdJVUQpK5vL774omsJKmwSS13IHHjgge5255132muvvWY333xzha4rgMpBlSRKgqAxQGrt8Zcduq+LQT0frEwBUhldRAGku6TqDvfTTz+57m2FBUBBWvbEE090rwWQflQGKAtc7dq13Rggr9ubNyZIj3ft2pV02UgbdBEFgCRrCcrMzEzIawEkN3WdVRY4JUH45ptvXBc4tQApADrooIOsV69eiV5FoMLQRRQAkiwIirdwf/XVV23lypV23HHHueQIANKbgh6lwVYWuMmTJ9uKFSts2223tW7durkAiPTYSCd0EQWAJA+CLr/8cps4caLNnj3b3VeWOHVrmTFjhmvuv/XWW2369Om28847J3pVAVSgDh06FHhM5cO6detcNrj8/HzLysqycePG2Y033ligpZiMkkiHLqLaz9Ul1MuaSBdRAOkkqfuIffLJJ3bYYYeF7+uCRkHPNddc45IhZGdn27333pvQdQSQeAqAli9f7m5r1651XeH013tMzwPp1kVUXUE3btzouoj++uuv7q/u00UUQDpI6pYg1WC1adMmfF9dXXbYYQeXEU7UQvTyyy8ncA0BJEKwJWf06NF2ww03uJpuBT+aT0yVJBoTpK5ww4YNs4EDB/JjIS27iGqeLKWJV5ZE9aagiyiAdJDUQdCmTZsi0tp++umn1qNHj/B9BUh///13gtYOQGWgwEfzhekib5tttnE13QqCqlSpYjVr1nSP6/lTTz2VDHFIu0Cof//+1q9fPzeeVufT4mRfBYBkltRBkPoxe+OB5s+fb7/99pur0fWom4sucgCkL02e/Pvvv7t/exOj+idK/eeff2zevHluuerVqyd4bYGKp2OBiYKT37ynesZ8bsuahe7vxiXfxVyuzbkfl9u6AZVRUgdBffv2tUceecT159dYIF3AHHnkkRFdYtQ9DkB682q3g7XcsR4HgFSSVa2uharUsIzMKoleFaDSSOog6LrrrrNvv/3WnnjiCRcADR8+3Bo1auSeU5eXt99+284+++xEryaABFIN94477mhLlixxmeH8k6XqvrRu3ZqacABJjZYcII2CIPXv//jjj91A5xo1arg+/n5Tp061Fi1aJGz9ACSeWnlOOeUU++WXX1zQo7EPor85OTluMLiepzUIAID0kdRBkKdu3boFHlNQtMceeyRkfQBULscff7zrHjt+/HhXaSIKepo2bWpHHXWUm1gZAFKVWr5D+VssI4vkF0BSBkF//fVXiVt2SvNaAMlNCRA0KWqnTp3s0ksvdV3j1HX25ptvJh0wgJS1dUuOrZs70XIWTLf8jWssq0Y9q9lyf6vTtodlViVxFNJbUk2WutNOO9nll19uCxYsiPs1yhp30UUX2c4771yu6wYgOdIBqxwR/dV9PQ4AqRgArfj8cVv91Yu2cdG3lrt+qfur+3pczwPpLKlagp5++mmXAnvEiBHWrVs3N+N1586drW3btq5fv6xcudLmzJljn3/+uev68tlnn1mzZs3cawGAjHAA0oFrAfprlmVUqW7V6u9gGRaykGVY3vq/3ePr502yuu16J3o1gYRJqiBo0KBBblK3J5980t2GDBkSczCz+r8qOLr//vvt3HPPZb4gIIbshs3YNgCQQnQN5LrAbV5nmRmZtnHRVxbK22IZ2VUtq1Yj27p5vW3480urs2svksIgbSVVECSa/PSKK65wt6+++somTZrkBjxrYlRRP/+OHTu6lqJ99tkn0asLVH7Z2bYlL2QLVuZaOti4JRT+O3fpfzPFpbqWDatY1WzmQkpnHTp0KHzQfCjkLoZjVSzqPIvkoSQIeRtWWf7G1Za/YbmF8vPMsrLNNq+zrZvWmGVmu+ddsoTsaoleXSAhki4I8lOQQ6ADlJ4CoL4jlqTFpvxj0Wb394dFm9PmO4+7uJm1bVI10auBSkYTja9bt85Wr15t+fn5lpWVZfXr17c6depYZmZSDRlGgLLAbd28ziVDyKxex7Jq1g8/l79lg23duMa2blnnlgPSVVIHQQAAoGjBlpwNGzbYXXfdZdOmTbNZs2a5ObNq167tEoYcdNBBNnToUJKGJD217pllaDTQ/1r63F/9R8MwkFzZ4QAAQOm99957LgDSnHoKfkR/dV+PT5gwgc2cxNTNLbNaHcuoXk93LH/jP5a/aa37q/t6PLNqbbcckK4IggAASCNqDZg6daqtX7/emjdvHpExUff1+JQpU9xySE7q5pZdq6FlV69vVbdta9m1GlhmlRrur7tfo4F7nu5wSGd0hwMAII1s2bLFVq1a5bq7BRMh6L4e1/Narlo1Bs0nI/2OmhR18/I5LtCpvv0+4RTZ+euXWla12larVWcywyGt0RIEAEAaqVq1qptbT+OCgq09uq/H9byWQ/Kq07aH1WzRyUK5m2zLsp9ty+o/3V/d1+O123RP9CoCCUVLEAAAadZK0KVLF5csYeHCheFASH91X2ODunbtSitBksusWtO2PfACNymq5gRSprisGvVcC5ACID0PpLOkDoLUXK/aKgAAEL/evXvbd99955IgaAyQ6O/GjRtddrhevXqxOVOAAp267Xq7SVHdnEBZVQlugVToDqcBnAMHDrRPP/000asCAEDS0LgfpcG+4IILrG7duu4x/dV90mOnZutfZnY1AiAgVYKgww47zF599VXr1q2btWvXzh566CHXOgQAAIoOhPr3729t27Z19/VX9/U4AKS6pO4O984779jixYvtueeec7chQ4bYsGHD7Pjjj7dzzjnH9XkGkH7mPdUz5nNb1ix0fzcu+S7mcm3O/bjc1g2obPwpsgEgXSR1S5Bst912dv3119vvv/9uH3zwgR111FE2duxY6969u+2666724IMP2sqVKxO9mgAqiaxqdS2rZgP3FwAApKekbgkKOvzww91t+fLldtVVV9no0aPd3+uuu8769etn11xzjXXs2DHRqwmgnNGSA8TPnx0OANJFSgVBymrz2muv2TPPPGNffPGFZWdnW58+fdxcB6+//rp7btSoUXbyyScnelUBAJVYKHeL5S5dYKlsQ06Ovf/JZJvz6y/uvv6+/MRwO/LQblarZmqnT66yfetErwKABEuJIOibb75xgc/LL79sa9eutRYtWtgtt9xiZ511ljVr1swts2jRIjdW6IYbbiAIAgAUSgHQkqF9U3Yr5eRttcd/WGGzlufYmpUb3WNrVi63EbcMtS8er2kXdNzWamYnfY/5mFo897VGQSV6NQAkUFIHQU8++aQ9++yzLgjSgM4jjjjCzjvvPDe/QWZmZOG9/fbb2/nnn29nnnlmwtYXAIDKYOKidS4Aqp6ZYbWyMi0nL9/91X09PmnReuvdinFzAFJXUlfzaD4DZYfTnAZKjDB+/HiXGCEYAHmURlvzCgEAkK409mf60hzbkLvVmtbMjsgOp/s5uVvty6UbGCMEIKUldUuQssD17dvXjf2Jx3777eduAACkqy1bQ7ZmS77VzM4okBZb92tkZ7jntVy1LLqMAUhNSd0SpDE+8QZAAADArGpmhtWrmmU5eaECrT26vzEv5J7XcgCQqpI6CFK2t0GDBkV9TgW5nnvzzTcrfL0AAKis1Nqzf5OaVqtKpv2dkxeRIlv3a1bJtM5NajF5KoCUltRB0GOPPRazkNbjWVlZ9uijj1b4egEAUJn12L6OdWpU0zZtDdmG/K3uMf3VfT3effvaiV5FAChXSR0E/fzzz7bXXnvFfF7P/fTTTxW6TgAAVHZKf6002AN3bmC1/5cKW391P9XTYwOAJHUpt27dOjcRaixqCVqzZk2FrhMAAMlAgY7SYO9Q57/nUf3VfQIgAOkgqYOgli1b2vTp02M+r+e22267Cl0nAACSiT9FNgCki6QOgjQn0EsvvWTjxo0r8Nw777xjr7zyivXp0ych6wYAAACgckrq/NLDhg1zcwUdd9xx1q1bt/D4oG+++cYmT57sWoGuu+66RK8mAAAAgEokqYOgbbfd1j7//HM7//zz7f3337dJkyaFm/R79erlssc1btw40asJAEBC9Xx3XsznFq7f4v5+t3JjzOU+7tOm3NYNABIhqbvDSYsWLWz8+PG2YsUKNwZIN/373XffdWOGSmrOnDl2880320EHHWRNmza1WrVqWfv27e2SSy6xJUuWxP0+OTk5du2119oOO+xg1apVc3+HDh3qHgcAINHqVs2yBtWy3F8ASBdJ3RLkV79+fdt3333L7P1Gjhzp5hjSmKIBAwZYjRo17Msvv7THH3/cXnzxRdcCteuuuxb6Hvn5+a5FasqUKTZw4EDr0qWLzZ492+677z6bMWOGffzxx5aZmfRxKACgkqMlBwBSNAhSy8rKlSvDM1/7laRFqF+/fq4FZ5tttgk/ds4551jnzp3t3HPPtRtvvNFef/31Qt/jhRdecAHQxRdfbMOHDw8/rtagK6+80gVTgwYNKva6AQAAACi5pG6GUMBz7733WvPmza1OnTouuNhxxx0L3EqiU6dOEQGQ58QTT3R/v/vuuyLfY/To0e7vkCFDIh6/4IILXMuS9zyAii03tuZtjlphAgAA0kNStwRdf/31dtddd1m7du1chriGDRuW+2cuWrTI/W3SpEmhy+kCa+bMmS5DXatWrSKeUwC05557uucBVIytW3Js3dyJlrNguuVvXGNZNepZzZb7W522PSyzak1+BgAA0khSB0HqbtazZ0/74IMPKmyStxtuuMH9HTx4cKHLrVq1ynXR69ixY9Tn1Xr1xRdf2Nq1a61u3bpRl1m2bJktX7484rG5c+e6v7m5ue5WEfLy8y0/+78ziiP15OXlWX5+hlXNzLdUlb8lx1Z+8YRt+Osr9+/MqjUsd/V8y13xm+Ut/8kaH3S+ZaVwIJSfn2e5uUyEWRyUe6ktHcq9dJaIMq9KlSoV+nlI8yBIY4DUAlRRAdCdd95pb775ph1zzDF22mmnFbqsl/1NGeGiqV69eni5WEGQkjDccsstUZ9bs2aN+/4VIXddjq1v1LpCPgsVb8XKVZaz3qx1nfUpu/kXzv7Q8hfPsFrVq1n1Jju5MkOttZvWLHWP11i0ozXf/XBLVTlrV9rKTE7QxUG5l9rSodxLZ4ko85RJGMklqYOgnXfeuUBLSXl55JFH3MSrmpT1pZdeKjLwqlnzv7XKmzdvjvr8pk2bIpaLRmOH+vfvX6AlSEFYvXr1KqT7n+RuXmO5y3+vkM9Cxdu2YQNbl5lhv6+rmJbFiqZgZ+Gv31nOxs1Wo14by8v7/2M3VLO5bfz7J5v3y2zbvMOxFVahUtFq1m1oDRsSBBUH5V5qS/VyL91R5iHlgyBlWFP3NM3dE6s1pSw8+OCDLrnBoYceau+8806hgYunQYMGbrmFCxdGfV6Pa50LW29N9Bprslc1u1ZU02soK8uy8v47mR5ST3Z2tmVlZdiWrak5R4iSIOTmrDWrUtO2KhdMRD6EDPe4nt+cm2+Z2dFbbpNdVlY2XTWKiXIvtaV6uZfuKPOQ8kGQaniVeECJEc4880yXCS4rq2CBVpo01Pfcc49LlX3EEUfYv//973A3tqKoRlkZ5qZOnWp//vlnRHKEjRs32rfffmsHHnhgidcLQHwysqq6JAhbVs13ZYa/tUf3Q7kb3fNaDgAApIekDoJOP/308L9vv/32qMvogqekQZDGAKkL3FFHHWVvvPFGzPE9GtezYMEC10WtWbNm4cc1QaqCoAceeCBinqAnnnjCBUJ6HkD5UhmgLHCbl8+xvHV/W3adpuExQbqfWaWm1WrVOWW7wgEAgBQLgiZNmlRu7/3YY4+5AEipsJV8YezYsRHP165d243NkRkzZlj37t1dsoRRo0aFl1EGOc0FNGLECJfIoEuXLjZ79myX8EBji0499dRyW38A/09psDcv+8Vy/pplm5f+ZBlVargWIAVANVt0stpturO5AABII0kdBHXt2rXc3tubw2fp0qV2xhlnFHhe3du8ICgWdc2bMGGC3Xrrrfbaa6/ZK6+84lqKNL7oxhtvjNp1D0DZ0zxA2x54ga2fN8k2/PlleJ4gtQApAGKeIAAA0ktSB0F+ysK2YsUKa9SokVWtWvq+/WrR8bfqFEatOrFmn1eL0b333utuABJHgU7ddr2tzq69LJS/xY0BogscAADpKdOSnBIMKGtbnTp1rGXLlvbZZ5+FJxrV4//5z38SvYoAKhEFPsoCRwAEAED6Suog6Pvvv7eDDz7Y5syZUyD5gVJLK2GBxuQAAAAAQEoEQRpXoxl6f/jhB7v77rsLdElTS9D06dMTtn4AAAAAKp+kDoKUfvrss892E45G69qi7nFLlixJyLoBAJAMVIG4OX9rzLGtAJCKkjoxwoYNG6x+/fqFPr9169YKXScAAJJBTt5Wm7honU1fmmNrtuRbvapZtn+TmtZj+zpWMzup60gBILWDoB122MHNuxPLp59+ajvvvHOFrhMAAMkQAD3+wwqbtTzHNuRutZrZGTZ/7Rabs2az/bJ6s13QcVsCIQApLamreo4//nh74YUXbNasWeHHvG5xSogwbtw4O+GEExK4hgAAVD5qAVIAVD0zwzrUr2at61Zzf3Vfj09atD7RqwgA5Sqpg6ChQ4da69atXYa4fv36uQBIE5PuueeeNnjwYNt7773tsssuS/RqAgBQaWjsj7rAqQWoac3scOWh/up+Tu5W+3LpBsYIAUhpSR0EaSLSadOm2fnnn28//vijK7CnTJliCxYssAsvvNAmTpxo1apVS/RqAgBQaWzZGnJjgNQFLphUSPdrZGe457UcAKSqpB4TJJok9aGHHnK3FStWuEQIjRo1YiJEAACiqJqZ4ZIgaAyQKg/9gZDub8wLuee1HACkqqRuCdK4nz/++CN8f9ttt3WTpHoFup5jslQAAP6fzpHKAlerSqb9nZMX7vamv7pfs0qmdW5Si8pEACktqYMgjfv5/PPPYz6viVK1DAAA+H9Kg92pUU3btDVkP63ebL+v3ez+6r4e7759bTYXgJSW1N3hiprYLTc31zIzkzrOAwCgzGkeIKXBVhY4JUHw5glSC5ACIOYJApDqkjoIkuCgTs8///xj7733njVr1qzC1wkAgMpOgU7vVnWtV8s6LgmCxgDFOqcCQKpJumaSW265xbKystxNhfWpp54avu+/NWzY0F5//XU78cQTE73KAABUWjqXVsvKJAACkFaSriVIcwANGjTIdYVT0oNDDjnEzRUULNCVPrtz58520kknJWxdAQAAAFQ+SRcE9e3b191EcwINGTLEjj766ESvFgAAAIAkkXRBkN/8+fMTvQoAAAAAkkzSjQkCAAAAgLQOgr788kvr06ePmyQ1Ozu7QIIEPQYAAAAAKREETZs2zbp27eoCof3228+2bt1q3bt3t06dOrnECR07drSBAwcmejUBAAAAVCJJHQTdfvvt1qRJE/vxxx9t1KhR7rFhw4bZ9OnT3RxBGjN0zjnnJHo1AQAAAFQiSR0EzZgxw84880zXFS4z879fRa1BcuSRR9rJJ59sN954Y4LXEgAAAEBlktRBUE5OjrVo0cL9u2rVqu7vhg0bws/vvffeNnPmzIStHwAAAIDKJ6mDIHWFW7Jkifu3JketU6eO/frrr+HnV6xYwQzYAAAAACIkdeq0vfbaK6KlR0kRhg8fbvvvv7/rFvfYY4/ZnnvumdB1BAAAAFC5JHVL0EknnWSrVq2yjRs3uvu33XabrV271nr06GGHHXaY+/edd96Z6NUEAAAAUIkkdUvQgAED3M2z22672c8//2xvvfWWmyNIyRF23HHHhK4jAAAAgMolqYOgaLbffnu7+OKLE70aAAAAACqppO4OBwAAAAAp3RJ0xhlnFPs1GRkZNnLkyHJZHwAAAADJJ6mCoFGjRhX7NQRBAAAAAJI2CFLaawAAAAAoDcYEAQAAAEgrBEEAAAAA0gpBEAAAAIC0QhAEAAAAIK0QBAEAAABIKwRBAAAAANIKQRAAAACAtJJU8wR55s6da4888oj726hRIzvttNPs0EMPTfRqAQAAAEgCSRcE/frrr9a5c2dbs2ZN+LGXXnrJXnzxRTvppJMSum4AAAAAKr+k6w5322232YYNG+zee++177//3t544w1r1qyZXXPNNYleNQAAAABJIOlagqZMmWIDBw60K6+80t3v0KGD5eXluVagOXPm2E477ZToVQQAAABQiSVdS9DSpUtddzi/Aw44wEKhkP39998JWy8AAAAAySHpgiC1+tSqVSvisZo1a7q/ubm5CVorAAAAAMki6YIgycjIKNbjAAAAAJC0Y4JkyJAhdtNNN4Xvb9261QVAgwYNsho1akQsq8eVUQ4AAAAAkjIIatmypQtsgl3f9LjQJQ4AAABASgVBf/zxR6JXAQAAAEASS8oxQQAAAACQNi1BQQsXLrTvvvvO1qxZY/Xq1bPdd9/dmjdvnujVAgAAAFBJJW0QNHXqVLv66qtt5syZBZ7bb7/97J577rEuXbokZN0AAAAAVF5JGQSNGjXKzj77bMvPz3cTpe6zzz6uFUitQbNmzbIvv/zSDj30UHv22WfttNNOS/TqAgAAAKhEki4I+uWXX+zcc8+1nXfe2V5++WXbY489Ciyj7nEnn3yynXPOObb//vvbrrvumpB1BQAAAFD5JF1ihAceeMBq165tEydOjBoAicYFffLJJ265Bx98sMLXEQAAAEDllXRBkIKf008/3Zo0aVLocnpeXeEUDAEAAABA0gZBixcvtg4dOsS1bMeOHd3yAAAAAJC0QVD16tVtw4YNcS2bk5PjlgcAAACApA2CdtllF/voo4/iWlbLafmSuPvuu+2EE06wnXbayTIzMy07O7tEWewyMjKi3jp16lSi9QIAAACQZtnhjj/+eLv22mvtzTffdP+O5a233rL33nvPBTMlMXToUNtmm21sr732svXr19vy5ctLvM7Dhg2zdu3aRTzWsGHDEr8fAAAAgDQKgi666CI3/8+JJ55ol1xyiZ133nmutcYzd+5ce/LJJ2348OHWtm1bu/DCC0v0OXqfNm3auH9369atVEFQz5493XsAAAAASLykC4Jq1Khh77//vvXp08ceeughe/jhh61OnTpustS1a9e6WygUcnMDvfvuu1azZs0SfY4XAJUVtSZVqVLFqlWrVqbvCwAAACDFgyBp3bq1ff311zZy5EgbO3as/fDDD7ZkyRKrW7eudenSxfr162dnnnlmpUmK0LdvXxeciVqnzj77bLviiiuKHGe0bNmyAi1QaqGS3Nxcd6sIefn5lp9dtUI+CxUvLy/P8vMzrGpmPps/ReXn51lubkaiVyOpUO6lNsq91JaIMk8V3UguSRkEiVpULrjgAnerrNQKNWDAADvssMOsWbNmtmjRIhszZoxdc8019umnn9q4ceNc0oVYHn/8cbvllluiPrdmzRpbuXKlVYTcdTm2vlHrCvksVLwVK1dZznqz1nXWs/lTVM7albYykxN0cVDupTbKvdSWiDKvadOmFfp5SMMgKCsrywUSJ598slV2CoB08zvnnHPcur/66qv2+uuvu7FNsSjA69+/f4GWoGOOOcZ1/6uo5Aq5m9dY7vLfK+SzUPG2bdjA1mVm2O/rKqZlERWvZt2G1rAhQVBxUO6lNsq91EaZh5QMgjTeJ5kpPfZNN93kgqDx48cXGgQ1btzY3WI1u1ZU02soK8uy8rZUyGeh4qlbZlZWhm3ZmsXmT1FZWdl01Sgmyr3URrmX2ijzkJLzBKWCHXfcMTzmBwAAAEDFIghKgN9++839pf8oAAAAUPGSrjuc/PLLLzZ16tS4l1fGuPKUk5NjCxYscON0lADBo8QFwXE7ykijiVhFY3sAAAAAVKykDILuuOMOd4tXfn7xU/8q+cKff/7p/q2/Got0++23h5+//vrrw/+eMWOGde/e3U477TQbNWpU+PHddtvNDj74YPdXwdHixYvdWKCff/7ZjQU69thji71eAAAAANIwCFJgobmCypPmIJoyZUrEYzfccEPUICgWZYHTe0ycONGltK5Vq5btvvvu9vzzz7uASUkSAAAAAFSspAyCzj333HJPkT158uS4l+3WrVvUrHX3339/Ga8VAAAAgNIiMQIAAACAtEIQBAAAACCtEAQBAAAASCtJFwQpqcABBxyQ6NUAAAAAkKSSLjGCsqrF8vvvv7sU1IsWLbIOHTrY4MGDrUaNGhW6fgAAAAAqt6QLgp577jl75JFH7OOPP7bGjRuHH9f94447zk1cqkxtSj/99NNP27Rp01xqagAAAABIyu5w48ePtzp16kQEQAp6zjvvPBcAXXPNNfbOO++4FqPvvvvOBUwAAAAAkLRB0OzZs91kqX5ffPGFzZ8/380ddOedd9pRRx3lWoy6du1qb7/9dsLWFQAAAEDlk3RB0PLly61169YRj6nLm7q/DRgwIOLx3r1722+//VbBawgAAACgMku6IEjBzpYtWyIemzFjhvsbzBq37bbb2saNGyt0/QAAAABUbkkXBLVq1co+//zz8P38/Hz79NNPbccdd3RBj9/q1autYcOGCVhLAAAAAJVV0mWH69Wrlz344IN24IEHWo8ePdy8Qeoid9JJJxVY9quvvnJBEwAAAAAkbRA0ZMgQGzVqlF166aXhzHDbbLONXXHFFRHLqRucMskpaxwAAAAAJG0Q1KhRI5s5c6bde++9NnfuXGvTpo0LjFq0aFFgnFD37t3t+OOPT9i6AgAAAKh8ki4IEgU8I0aMKHQZpcfWDQAAAACSOjGCJkFdt25dolcDAAAAQJJKuiBozJgxtscee9jUqVMTvSoAAAAAklDSBUHjxo2zDRs2uMxwV199teXm5iZ6lQAAAAAkkaQLgvr06WM//PCD9e7d2+6//37bd9993X0AAAAASNnECMoQpxahZ5991i6//HIXCN188812wAEHRF2+S5cuFb6OAAAAACqnpAyCPGeddZbrFqfgZ9iwYTGXy8/Pr9D1AgAAAFB5JXUQ9Pfff9sFF1xgy5cvtw4dOlinTp0SvUoAAAAAKrmkDYLeeustO/fcc2316tV21VVX2e23325VqlRJ9GoBAAAAqOSSLghav369XXzxxTZ69Ghr2bKlC4YOOeSQmMtv3brVMjOTLv8DAAAAgHKSdNHB7rvvbi+88IINGjTIvvvuu0IDoDvuuIPWIQAAAADJ3xKk1p9jjjkm0asCAAAAIAklXRD0/fffW5MmTRK9GgAAAACSVNJ1hyMAAgAAAJBWQRAAAAAAlAZBEAAAAIC0knRjgu688864l50yZUq5rgsAAACA5JN0QdD1119frOUzMjLKbV0AAAAAJJ+kC4ImTZqU6FUAAAAAkMSSLgjq2rVrolcBAAAAQBJL+cQIv/32W6JXAQAAAEAlkrJB0Pz58+3000+3jh07JnpVAAAAAFQiSdcdTlavXm2jRo2yOXPmWMOGDe2kk06y9u3bu+eWL19uN9xwgz3//POWm5trnTt3TvTqAgAAAKhEki4IWrRokQtsFi9ebKFQyD1277332oQJE6xKlSp2/PHH28qVK+2AAw6wm266yQ4//PBErzIAAACASiTpgqBbbrnFBUCXXHKJHXbYYTZ37lz32KWXXuoeb9asmY0ZM8aOOOKIRK8qAAAAgEoo6YKg//znP3bCCSfYQw89FH5sm222scGDB9u+++7rUmjXrFkzoesIAAAAoPLKTMbucF26dImaNvuiiy4iAAIAAACQWkGQkh3UrVs34rE6deq4v9ttt12C1goAAABAski6IEgyMjKiPp6ZmZRfBwAAAEAFSroxQXLXXXe5FNj+1iEFRldddZU1aNAgYlk9/uGHHyZgLQEAAABURkkZBP3www/uFvT111/H3WoEAAAAID0lXRC0devWRK8CAAAAgCTGIBoAAAAAaSVlg6CVK1fagw8+aB06dEj0qgAAAACoRJKuO1w8k6k+88wzNm7cONuyZQvzBgEAAABIvSBo8eLFLlvcc889Z3/88YdVr17d+vTpY/3797ejjjoq0asHAAAAoBJJ2iBICRLee+891+rzwQcfWF5enu2+++7uudGjR9vxxx+f6FUEAAAAUAklXRA0f/58GzlypI0aNcq1AG233XZ25ZVX2hlnnOGe33nnnUmLDQAAACB1gqC2bdta1apVXTc3BT7/+te/LDPzv/kd5s2bl+jVAwAAAFDJJV12uFAoZE2aNLG9997bdX/zAiAAAAAAiEfSRRDK+qbg58Ybb7QddtjBjjzySBs7dqzLBAcAAAAAKdcdTlnfdNN4II0NUka4E044werXr2+HHXYY44EAAAAApFZLkEcJEW644Qb7/fff7f3337fu3bvb22+/7brLXXvttXbzzTfbDz/8kOjVBAAAAFDJJG0Q5MnIyHDJEd544w1buHCh3X333e6xW2+91fbYYw9r165dolcRAAAAQCWS9EGQX6NGjezqq6+2X3/91SZOnGgnnnii/fnnnyV6LwVT6ma30047ueQL2dkl6zmYk5PjWqY0fqlatWru79ChQ93jAAAAACpe0o0Jile3bt3c7Z9//inR6xWobLPNNrbXXnvZ+vXrbfny5cV+j/z8fOvVq5dNmTLFBg4caF26dLHZs2fbfffdZzNmzLCPP/6Y7HYAAABABUu6IOijjz5y3dyUJrsoahH68MMP7ZJLLin258ydO9fatGnj/q1gqiRB0AsvvOACoIsvvtiGDx8eflytQZrg9cUXX7RBgwYV+30BAAAApFF3OKXE/uSTT8L3V65caVlZWa77W9CsWbPs8ssvL9HneAFQaYwePdr9HTJkSMTjF1xwgdWoUSP8PAAAAICKk3RBkLK/xfNYommdZs6c6bLYtWrVKuI5BUB77rmnex4AAABAxUq67nDJYtWqVS75QceOHaM+37x5c/viiy9s7dq1Vrdu3ajLLFu2rEA3PHXTk9zcXHerCHn5+ZafXbVCPgsVLy8vz/LzM6xqZj6bP0Xl5+dZbm5GolcjqVDupTbKvdSWiDKvSpUqFfp5KD2CoHLiZX9TRrhoqlevHl4uVhD0+OOP2y233BL1uTVr1riugBUhd12OrW/UukI+CxVvxcpVlrPerHWd9Wz+FJWzdqWtzOQEXRyUe6mNci+1JaLMa9q0aYV+HkqPIKic1KxZ0/3dvHlz1Oc3bdoUsVw0GjvUv3//Ai1BxxxzjNWrV88aNmxoFSF38xrLXf57hXwWKt62DRvYuswM+31dxbQsouLVrNvQGjYkCCoOyr3URrmX2ijzEA+CoHLSoEEDF+BoAtdo9LhagGK1Aknjxo3dLVaza0U1vYaysiwrb0uFfBYqnubAysrKsC1bs9j8KSorK5uuGsVEuZfaKPdSG2UeUjYIGjlypE2ePDnc0pKRkWEPPvigvfrqqxHLzZs3L0FraG6dOnXqZFOnTnUTtvqTI2zcuNG+/fZbO/DAAxO2fgAAAEC6SsogaNKkSe7mN2HChJjBSHnTuJ4FCxa4LmrNmjULP64JUhUEPfDAAxHzBD3xxBMuENLzAAAAACpW0gVB8+fPr5DPGTNmjGvBEf1Vyuvbb789/Pz1118f/veMGTOse/fudtppp9moUaPCjw8ePNjNBTRixAiXyKBLly42e/Zsl/BAE7CeeuqpFfJdAAAAACRxEBScc6c8u9xNmTIl4rEbbrghahAUiyZxVQvVrbfeaq+99pq98sorrqVIk6feeOON7nkAAAAAFSvpgqCK4o05iodadWJN2Fq7dm2799573Q0AAABA4mUmegUAAAAAoCIRBAEAAABIKwRBAAAAANIKQRAAAACAtEIQBAAAACCtpEwQ9Ndff9n48eMTvRoAAAAAKrmUCIIWLFjgJiLt27dvxISmAAAAAJByQdCiRYvs0EMPtT///NPN1XPTTTcxJw8AAACA1AyClixZYj169LDly5dbnz59LCMjw0455RQbOnSoPfzww4lePQAAAACVUFIHQT/++KOtWrXKPvjgA9t7773dY6NGjbL+/fu7xwAAAAAgKNuS2GGHHWbz58+32rVr24cffugey8zMtJdeeslyc3MTvXoAAAAAKqGkDoJEAVBQVlaWuwEAAABASnWHAwAAAIDiIggCAAAAkFYIggAAAACkFYIgAAAAAGmFIAgAAABAWiEIAgAAAJBWUiYICoVC7gYAAAAAaREEXXPNNbZ8+fJErwYAAACASi7pJ0v11KhRw90AAAAAIC1aggAAAAAgHgRBAAAAANIKQRAAAACAtEIQBAAAACCtEAQBAAAASCsEQQAAAADSStKlyJ46dWqxX9OlS5dyWRcAAAAAySfpgqBu3bpZRkZG3Mtr2by8vHJdJwAAAADJI+mCoFtvvTWuIOidd96xmTNnVsg6AQAAAEgeSRcEXX/99YU+P2vWLLvyyitdAFS/fv0ilwcAAACQXlImMcIff/xhJ510ku2///42ffp0GzJkiM2bN88uv/zyRK8aAAAAgEok6VqCglavXm233XabPfHEE7ZlyxYXCN1xxx3WqlWrRK8aAAAAgEooaYMgBTyPPPKI3XXXXfbPP/9Y9+7d7b777rO999470asGAAAAoBJLyiDoxRdfdGN9FixYYB06dLCXXnrJjjzyyESvFgAAAIAkkHRB0D777GPffvutbbfddjZy5Eg7/fTTi5UyGwAAAEB6S7og6JtvvgkHPeoKp1thtOyvv/5aQWsHAAAAoLJLuiCoZcuW4SAoNzc30asDAAAAIMlkJ2MqbAAAAACwdJ8nCAAAAADiQRAEAAAAIK0kXXe4c845p1jLa/zQU089VW7rAwAAACC5JF0Q9OyzzxZreYIgAAAAAEkdBM2fPz/RqwAAAAAgiSVdENSqVatErwIAAACAJEZiBAAAAABpJelagmTKlClWo0YN22+//dz9DRs22OWXX15guR133NGGDh2agDUEAAAAUFklXRA0Y8YM69Gjh0uQ4AVBmzZtipowQUkRevbsaZ06dUrAmgIAAACojJKuO9yYMWOsefPmdtpppxV47qWXXnKJE3SbN2+eNW3a1F544YWErCcAAACAyinpWoI+++wz69Onj2VmFozfmjRpEpE4YcCAATZ58uQKXkMAAAAAlVnStQT9/vvv1qFDh7iWbdOmjVseAAAAAJK2JUjjf5QUwa9hw4a2ZMkSa9CgQcTjtWrVcssDAAAAQNIGQfXr17fFixdH7QoXpOW0PAAAAAAkbXe4PfbYwz788MO4ltVyWh4AAAAAkjYIOv74411yhLfeeqvQ5d544w2bNm2a9evXr8LWDQAAAEDll3RB0Omnn+4SI5x00kl2/fXX2x9//BHxvO5fd911dsopp1jHjh3d8gAAAACQtGOCqlatau+++6717t3b7rzzTrvrrrusbt267rZ27Vp3C4VC1r59e7dclSpVEr3KAAAAACqRpGsJEs0F9NVXX9nw4cPtkEMOsezsbJcdTn+7dOliI0aMcM+3bNky0asKAAAAoJJJupYgT7Vq1eyiiy5yNwAAAABI6ZagiqQEDJ07d3ZzDind9tFHH20//PBDXK8dNWqUZWRkRL116tSp3NcdAAAAQAq0BJ188smu9efAAw9097ds2WKvvvqq/etf/yowV9D777/vkiR8/fXXJfqskSNH2llnneUSLNxzzz1u4lV1tdNnK/PcbrvtFtf7DBs2zNq1a1dgglcAAAAAFS/pgiAFPEcddVQ4CFq3bp0NHjzYPv744wJB0KpVq2z27Nkl+pzVq1fbFVdcYc2bN3cBjxIvyIABA1zShUsvvdQmTpwY13v17NnTunXrVqL1AAAAAFC2UqI7nLLBlbVx48a5THNqCfICIFGyBc09NGnSJPvrr7/ifr/169fb5s2by3w9AQAAAKR4S1BFmT59uvvrtTj56bEXXnjBZs6caS1atCjyvfr27esCKmnbtq2dffbZrpVJ2ewKs2zZMlu+fHnEY3PnznV/c3Nz3a0i5OXnW3521Qr5LFS8vLw8y8/PsKqZ+Wz+FJWfn2e5uRmJXo2kQrmX2ij3UlsiyjymZEk+BEExLFy40P1Vd7gg7zFvmVhq1qzpus8ddthh1qxZM1u0aJGNGTPGrrnmGvv0009da1NmZuzGuMcff9xuueWWqM+tWbPGVq5caRUhd12OrW/UukI+CxVvxcpVlrPerHWd9Wz+FJWzdqWtzGTOtOKg3EttlHupLRFlXtOmTSv081B6BEEx5OTkhFNxB1WvXj1imVgUAOnmd84557jkDhrb9Prrr9uJJ54Y8/UXXHCB9e/fv0BL0DHHHGP16tWrsOQKuZvXWO7y3yvks1Dxtm3YwNZlZtjv6yqmZREVr2bdhtawIUFQcVDupTbKvdRGmYeUDYKUYjqex0pDrTgSbRyPssT5lykOredNN93kgqDx48cXGgQ1btzY3WI1u1ZU02soK8uy8rZUyGeh4qlbZlZWhm3ZmsXmT1FZWdl01Sgmyr3URrmX2ijzkLJB0KBBg+y0006LeOzwww8vEAiVJmGCv8tbML11YV3l4rHjjjuGx/yUp61bt9rSpUtdIKd/l/h9cnJsY68Ly3TdUPYycjdb1j9LrcY3H1oGQSsAAEDqBEFdunQp81afaPbbbz978skn7YsvvnAprv30mOy7774leu/ffvut3PuPKuhZsGCBbdy40bLUkpOVVeLtllG9hlXvcECZryPKYSBozgZbX6+x1Z48hkAIAAAgVYKgyZMnV8jnaNyN5gJ65pln7LLLLgunyVZgMXbsWDfvj5cZTmOD9LjG6SgBgkeJC4LjdpSRZujQoeHPKC9qAVIA1KBBA9elrjSB49Ytmyx34X+z0qHyCoWybWW1Kraq7d62cc1SqzlzfKJXCQAAoFJKuiCootSvX9/uu+8+O++88+yggw6yc88913UrGzFihAsoHn744fCyM2bMsO7du7sueqNGjQo/vttuu9nBBx/s/io4Wrx4sRsL9PPPP7uxQMcee2y5rb/WVa0/pQ2AkDz0OzeslmXratayvG3IUgMAAJAWQZC6gCl7mubkad++fYkSF/gp8FFLjoKhq6++2qpWrWqHHHKI3XHHHbb77rsX+XplgZsyZYpNnDjRpbSuVauWe93zzz/vAqbyDE60LUrTBQ7JSb+3BoTmVimY1RAAAABJHAS9++67LpBQUKKWGnVN++yzz+z000+3+fPnu2Vq1Khht956q5uUtDT69evnboXR50dLwnD//fdbIhEAAQAAACkQBE2aNMmNpfGCjrfffts+/PBD69u3r5vTp0+fPpabm2vTpk2zq666ytq2bWtHH310olcbAAAAQCWRaUlGY3GUgGDcuHFuLM7ee+9tAwcOtJYtW7qsawqK3nvvPTfuZrvttnNjeAAAAAAgaVuCvv32Wzv77LNdi4/ceeed1qNHD7vuuutccORRIoIzzjjDHn300QSubWrIyK5qVZq3LffPCeVusbylC8r9cwAAAJDeki4IWrJkie26667h+zvvvHPEBKR+rVu3dgkJED3gyK1EAUeVJi3NqlQt1XtM+XKm/euUM2I+//Q9t9mgfsdYz5MH26fTZ8Vcrn/vI2zM8PvC95etWGnDnxtt70+aagsWL3FdMbdtUN9233UXO7JHVxs84LhSrTcAAAAqVtIFQZpnR2N/PN6/s7MLfhU9Fi1hAcwFQEuG9q00m6LZXeMsu3HzMnmv447saUcd1r3A45333jP878zMTHv2vtujvr5V8+3D/1bQc8ixJ9mK1f/YcUf0tDNO6GdVq1ax+QsW2uezvrZHnx9DEAQAAJBkki4IAoqy26672MnH/Le7ZGGZ84paRh56+nlbumKl3X/9NXbR4FMLPP/38hX8IAAAAEkmKYMgJUX4448/3L9zcnLcBe1LL71kX375ZYHxQ0BpzP3jv10Gux+4f9Tnmzbalg0MAACQZJIyCBo7dqy7+WneoGiYKyf95GzaZCtWrY54rEqVbKtXp07EY8FlPHVq1bJq1f47Pql1q+Zmn5qNfvNtu+Pqy6N2uwQAAEByScp5goDC3PfEs+7mt3fH9vb5uNfC9/Pz8635vl0KTaAgl555mr06boI9MnK0vfL2eDto332s0+4d7YB99rLOe+/hxhYBAAAguSRdENS1a9dErwIquYHH97UT+/aOeKxu7doR9xW8vDvqyaivb7/T/6cDb92yhc147w0bPnK0vTdxsv37g4/dTXZosb2NuO1G63nIgeXyPQAAAFA+ki4IAoqiwOXQgw4odBl1kyxqGU+r7bezB2681t2ULnv6N7PtjQkf2uvvvm8nnH+ZzRz/hrXZoSU/DAAAQJKgLw9QDI23bWh9evawFx66x4ace4blbNxor49/n20IAACQRAiCgBI64H/zDi1euoxtCAAAkEQIgoBCTPlypmvtiWbcR5+4v+3atmYbAgAAJBHGBCEthUIhe/ntd6M+16BePTui+38zxz36/BgXCB3Zo4vLMLdNvbq2ctU/9v7kqfbp9FnWYee2dlr/Yyt47QEAAFAaBEFpqkqTltbsrnFWmdYnFNpaYZ+3detWO2PIsKjP7d5ul3AQdNX5Z9lOO+5gn86YZZM/n24r/1ljNapXs512aGU3XnahXTx4oNWqWbPC1hsAAAClRxCUpjKqVLWqzf8/FXRhQlu3WihvS7mujwKgUG7pPqNr531t07zvi1zu45ejT6wbzX577u5uAAAASB0EQSiSAqDchXPZUgAAAEgJJEYAAAAAkFYIggAAAACkFYIgAAAAAGmFIAgAAABAWiEIAgAAAJBWCIIAAAAApBWCIAAAAABphSAIAAAAQFohCAIAAACQVgiCAAAAAKQVgiAAAAAAaSU70SuAyi8ju6pVad623D8nlLvF8pYuKPfPAQAAQHojCEpTW/JCtmBlbqVpNGzZsIplVynde0z5cqb965Qz3L/vGXalXXrmaQWWad+9l+Xl59tvUz+MePzXeb/bw8+OtslfTrfFfy+zalWr2s6td7Bjj+hp5w080WrVrBnzs6J5+p7bbFC/Y9y/e5482D6dPivmsv17H2Fjht8Xvr9sxUob/txoe3/SVFuweImFQiHbtkF9233XXezIHl1t8IDjirFVAAAAEEQQlKYUAPUdscQqi3EXN7PW9cvu/e55/Bk7rf+xtk3dukUu+8Ib/7aLrr/ValavYaced7S137mtbdq02SZ+/qVdd+9DNmrsv23cc49b65YtCrz2uCN72lGHdS/weOe994y4n5mZac/ed3vUz2/VfPvwvxX0HHLsSbZi9T923BE97YwT+lnVqlVs/oKF9vmsr+3R58cQBAEAAJQSQRBSTqfdO9qs736wex57xu4aOqTQZdWic/7Qm63tDi3t/THP2vZNm4Sfu/D0U+zfH3xsp15ylfU75xL7fNyrVr1atYjX77brLnbyMX2KXKeMjIy4lnvo6edt6YqVdv/119hFg08t8Pzfy1cU+R4AAAAoHIkRkHJ6H9rNDuy0tz0++mX7c9HiQpe97p4HbevWrTb64XsjAiCPusNdMOgk+2nOXHth7L+tvM39479jorofuH/U55s22rbc1wEAACDVEQQhJd09dIht3rLFbnpgeMxlFCCpxWj/vXa3PTu0i7ncOaec4P6+9f7HBZ7L2bTJVqxaHXFbs25d1PcJLufdNm/eEl6mdavm7u/oN9+2vLy8Yn1nAAAAxIfucEhJ++25ux3f63B77Z0JdukZg2yvju0LLPPjr3Pc331261joe+204w5Wu1ZN++HX3wo8d98Tz7qb394d29vn416LeCw/P9+a79ulyCQKSubw6rgJ9sjI0fbK2+PtoH33cd37DthnL+u89x5ubBEAAABKhyAIKevWKy+zdz6eaMPuedCN9wnyWmzq1qld5HvVq1Pblq5YVeDxgcf3tRP79o54rG7tgu+n4OXdUU9Gfe/2O/1/+nElX5jx3hs2fORoe2/iZDcmSTfZocX2NuK2G63nIQcWub4AAACIjSAIKatNqxZ2zskn2GMvvGQfTv7U/tXtkKjBytp164t8rzXr1rtAKEhBy6EHHRBXYoR4lpNW229nD9x4rbspXfb0b2bbGxM+tNfffd9OOP8ymzn+DWuzQ8u43gsAAAAF0bcGKW3oRee6YGfY/xIg+HXYZSf39+vvfyz0PebM/8PWb8ixjrvsbBWt8bYNrU/PHvbCQ/fYkHPPsJyNG+318e9X+HoAAACkEoIgpDRNMnrV+Wfaj7/NtdFvjot4bofm27vxO19+M9u++/nXmO/x7Ctjw3MCJdIB/5t7aPHSZQldDwAAgGRHEISUd/HggS799W0PP2qbNm+OeO72qy9343UGXXa1LVm2vMBr3/noE3vshZet3U5t3OSr5U3zFqm1J5pxH33i/rZr27rc1wMAACCVMSYIKU8TnN58xcV29tXXu/stt98u/FyPgzrbiNtusEtvusP2+ldfO/W4vtZ+57a2adMmm/j5lzb+P5Ot7Q6t7M2nRxSYKLU4QqGQvfz2u1Gfa1Cvnh3R/b+Z4x59fowLhI7s0cW1Um1Tr66tXPWPvT95qn06fZZ12LlthQRjAAAAqYwgKE21bFjFxl3czCrT+tjWyFaasnTKsX1sxPNjonZ7O/PEfnbgPnvZI8+NtvGfTLJnXn7dqlatYjvvuIPdfvVldv7Ak6xWzZql+nyNRzpjyLCoz+3ebpdwEHTV+We5lNyfzphlkz+fbiv/WWM1qleznXZoZTdedqFr1SrtugAAAKQ7gqA0VTU7w9o2qRrXsqGtWy2U9/8TepaLrZstlFu6z+jaeV/bNO/7qM+py9uM8W/EfK26uz151y1l8llBH7/8fLHmN9INAAAA5YcgCEVSAJS7cC5bCgAAACmBxAgAAAAA0gpBEAAAAIC0QhAEAAAAIK0QBAEAAABIKwRBAAAAANIKQVAK0wSdAAAAACIRBKUozYuTn59PIJSGgW9+fp5l5JbfxLMAAADJjiAoRVWrVs0FQcuWLSMQSqMAaOXmfMvN2WBZ//yd6NUBAACotJgsNUU1adLENm/ebKtWrbI1a9ZYVlaWZWRklOi9QlvzbWtObpmvI8qWWoAUAGXM/dpqfPMRmxcAACAGgqAU7g7XsmVLW7p0qQuGtm7dWuL3Cm3aaJt+/KJM1w9lT13gsv/52wVAGXlb2MQAAAAxEASleCDUrFmzUr/PloVzbcmEx8pknQAAAIBEY0wQAAAAgLRCEAQAAAAgrRAEFeGtt96yzp07W61atax+/fp29NFH2w8//BD3Bs7JybFrr73WdthhB5exTX+HDh3qHgcAAABQ8QiCCjFy5Eg7/vjjbcOGDXbPPffYddddZ7Nnz7YDDzzQvv/++yI3rlJU9+rVy722S5cu9thjj1mfPn3svvvuc39Lk6wAAAAAQMmQGCGG1atX2xVXXGHNmze3adOmWd26dd3jAwYMsPbt29ull15qEydOLHTjvvDCCzZlyhS7+OKLbfjw4eHH1Rp05ZVX2osvvmiDBg0q4U8HAAAAoCRoCYph3LhxtnbtWjvrrLPCAZAo7XS/fv1s0qRJ9tdffxW6cUePHu3+DhkyJOLxCy64wGrUqBF+HgAAAEDFIQiKYfr06e6vur4FeY/NnDkz5oYNhULu+e22285atWoV8ZwCoD333LPQ1wMAAAAoH3SHi2HhwoXur7rDBXmPectEs2rVKpf8oGPHjlGf13t88cUXrrXJ39Lkt2zZMlu+fHnEYz/99JP7+8svv1hubq5ViPw8yxt0T8V8Firc6h9/trytZvccmsfWT1H/LFpt3y5J9FokGcq9lEa5l9oSUeZVqVLF2rRpY9WrV6/YD0aJEQTF4GVvU0a3IG8HLyzDW2GvD75HrCDo8ccft1tuuSXqc+qSBwAAgMpB2YM7dOiQ6NVAnAiCYqhZs6b7u3nz5gLPbdq0KWKZ4r4+3vfQ2KH+/ftHPKaWo99++8122223mAEWUBxz5861Y445xt5++21r27YtGw9AyqPcQ3lQSxCSB0FQDP4ub+3atYu7q5ynQYMGLsCJ1WVOj6sFKFYrkDRu3Njdgg444ICYrwFKSgEQNVgA0gnlHpC+SIwQw3777ef+atxOkPfYvvvuG3PDZmRkWKdOnWzx4sX2559/Rjy3ceNG+/bbbwt9PQAAAIDyQRAUg7oH1alTx5555hnXBc2zYMECGzt2rHXr1s1atGgRHtejRAVLlkSOwhs4cKD7+8ADD0Q8/sQTT7hAyHseAAAAQMWhO1wM9evXt/vuu8/OO+88O+igg+zcc89143tGjBjhWnkefvjh8LIzZsyw7t2722mnnWajRo0KPz548GA3F5Bes2bNGuvSpYvNnj3bJTxQEHXqqaeW/y8MAAAAIAItQYVQ4KNWH43tufrqq+22225zCQmmTZtme+yxhxUlKyvLJkyYYFdddZVNnjzZzj//fDcJqyZPHT9+vHseSLRGjRrZTTfd5P4CQDqg3AOQEdKsngAAAACQJmgJAgAAAJBWCIIAAAAApBWCIAAAAABphSAIAAAAQFohCAIAAACQVgiCgBSn9Oya20o3zWUVjZJE7rjjjm6Z7Oz/nz7s5ptvdo999tlnFbjGABC9DPNumrpCU1bceuutbvJxP6/cinVr2rRpxPKaA1Dz9+2///7WuHFjq169upsMvUePHnbjjTe65//4449C3zN40zoDqNyYLBVIEzqxv/HGG27y3rp160Y89/HHH7uTvJbJzc1N2DoCQCz9+vWzvn37un8vX77cXn/9dTfH2eeff24ffPBBgeVvuOEG23nnnQs8XqNGjfC/8/Pz7bDDDnMVPZoYXfP6abL0v/76y77++mu799577ZJLLnHzCo0ZMybifT799FN7+umn7dhjj7Xjjjsu4rl27drxQwKVHEEQkCZ0kn755ZftlVdecRMB+z377LPWsmVLa9WqlbugAIDKRpOUn3rqqeH7Ck72228/+/DDD+2rr76yffbZJ2L5ww8/3A4++OBC3/Ptt992AZACmbfeeqvA8ytXrnSVRlWqVIn4bMnLy3NB0O67717gOQCVH93hgDShmskDDzzQRo4cGfH4ihUrbNy4cTZ48GDLzKRIAJAcsrKyrHv37u7fc+bMKdF7eK9T17doGjZs6AIgAKmHKx4gjZx11lk2c+ZM+/7778OPjR492tVonnHGGQldNwAornnz5oWDlaA1a9a4Sp7gbf369eFl2rRp4/6OHTvWVq9ezQ8ApBGCICCNDBgwwOrUqRPRGqR/q0+8usMBQGWVk5MTDmR+/vlnl7RA3dnUjbdr164Flj/qqKPcWJ7g7aKLLgovozFGe++9t02dOtWaN29uPXv2tOuvv97Gjx/vPg9A6mJMEJBGatWqZSeeeKK9+OKLbsDvrFmz7KeffnLZlACgMrvrrrvcLTju57HHHrOqVasWWP6hhx6yjh07Fnh8u+22C/9br5syZYo9+uijLtHCxIkT7T//+Y97ThVGSrwwZMiQcvk+ABKLIAhIM2eeeaY988wzrgZVGZW23XbbcMYlAKisTj/9dDvllFNc991ff/3V7rnnHlu4cGFEtje/Tp06FZkYQWrXrm3XXnutu23YsMFVDk2YMMEFV1deeaULmk466aRy+EYAEonucECa0VwYqh0dPny4q/kcOHBg1FpUAKhMNH5HXXePOOIIu/TSS+2TTz5xY4LUuq25zsqqtVxd6xRgvfnmm+6xYDIZAKmBIAhI09agadOmuVpP/RsAkjHjpYIhpbhW6v+ypmyasmjRojJ/bwCJR3c4IA0NGjTI/vnnH9tmm22sQ4cOiV4dACiRq6++2h5//HE3rlGJX7Kzi3dZM3v2bNclePvtty/wnDdvUPv27fl1gBREEASkoQYNGpAMAUDSU2psZXu7++67Xbp/f6r/jz76yP7444+orzvhhBPc/D+TJk2yq666ynWz0/ghjf9Zt26dffnll/bGG2+4iVKVHAFA6iEIAgAASUvZ25Td7bbbbrNTTz01/Ljux6L02WoJP/bYY23jxo1ufNFTTz1ly5Yts4yMDDdlgOZVU2KE1q1bV9A3AVCRMkJlNZoQAAAAAJIAiREAAAAApBWCIAAAAABphSAIAAAAQFohCAIAAACQVgiCAAAAAKQVgiCgHKxevdpNwKe5K1B6v//+u1WtWrVcZoUHUDYo98oW5R5QvgiCgHKg2cs1Ed8ll1ySsO37559/2sknn2yNGjWyGjVq2J577mnPPvtssd9Hs6Z37tzZatWqZfXr17ejjz7afvjhh5jLz5071wYPHmzNmze3atWqWZMmTezwww+3r776KmK5hx9+2Hr06OEmJ6xevbo1btzYDjzwQHv++ectPz8/YlnN06FJEK+99lo3pweAyicdy70lS5bY9ddfb7169bJmzZq5OYY08WpRJk6caL1793aVZSr/WrVqZQMGDLC1a9eGl6HcA8oXQRBQxv7++2974okn7Pzzz7eaNWsmZPsuXLjQncDffvttO/vss2348OEuKNG/b7nllrjfZ+TIkXb88cfbhg0b7J577rHrrrvOZs+e7YKV77//vsDymn1dFx2ff/65nXvuufbkk0/a1Vdf7S5IdLHgN2PGDLdOl112mT3++OM2bNgwt70U7Jx++ulRJ0RcsGCBWycAlUu6lnu//vqr3XHHHfbdd9/ZfvvtF9f733vvvXbooYe6Ch2Ve4899phbx/Xr11tOTk7EspR7QDnSZKkAys6tt94aysjICP3xxx8J26wDBw7UJMihN998M+LxPn36hLKzs0Pz5s0r8j1WrVoVqlu3bqh58+ahNWvWhB//888/Q7Vq1Qp17949YvkVK1aEGjVqFOrRo0do48aNJV73I4880q27PifogAMOCLVv377E7w2gfKRrubd27drQ0qVLw/f1+YceemjM9588ebLbTsOGDYv7e1HuAeWDliCgjL322mvWoUMH173B88cff7huEuou8sYbb9jee+/tumqo+4RaQlQDWFZUk6jP2HHHHe24446LeO6KK66wvLw8e/nll4t8n3HjxrmuGWeddZbVrVs3/HjLli2tX79+rtXnr7/+Cj+uVp/ly5fbAw884Lp3bNq0yTZv3lzs9d9hhx3c33/++afAc+o+8tNPP0VthQKQOOla7tWpU8d15Y3X7bff7rrAaZuItoHWrTCUe0D5IAgCypCCgB9//NF1yYhm/PjxrruXxsjcf//9dsABB9gjjzxiRx11VMQ4mK1bt9qKFSvivvmDDQUI6mah9w7SY7ooUVe0okyfPt39VReQIO+xmTNnhh9777333AWBPlvdQnSxo2Bo9913tzfffLPQwdT6Dr/99puNGDHCnnvuOdcXvl27djE/VxciACqHdC73ihuoTZ482fbff38bM2aMq/BRmamysmfPnq7LXTSUe0D5yC6n9wXSki4EpG3btlGf//rrr+3LL78M9x2/8MIL7dJLL3V913VS9MbCaOyLajTjpWQC3mvVL17UFz5IiQpUC+ktU5jC3sd7zP8+P//8s7ug0cm8b9++bizQ0qVLXX951aC++OKLdsoppxR4r7322ssNZhZvULHGCGmAddBOO+3k/tISBFQe6VzuFcecOXNcq48CrY8++siuvPJK69Spk33zzTdu7NHBBx9ss2bNsl122SXidZR7QPkgCALKuEZUGjZsGPV5BQjBwbMadKuLAbWWeCf0pk2b2scffxz356obiscbWKsTfzRqnQkOvo2msPfRe/iXkXXr1rkg6KSTTrKXXnop/LiCmo4dO9o111zjsjYp0PHTsnqfxYsXu64oq1atsjVr1kRdJ2+7Llu2rMj1B1Ax0rncKw6Vkd72euqpp+ycc85x94899ljXjVBd8JTAIdhtj3IPKB8EQUA5+O/42ILat29f4DH1J9dJTqml/SfbeNKsRuNlZoo1HkdjdVQrWpr30Xv4lxF16VD/dqXH9lOtprpzTJ061WVS2nXXXSOeP+igg8L/Pu200+ziiy+2Ll26uNYedYuLtl2DgRSAxEvHcq84VEZKZmamK+v8Bg0a5DJqKnV2EOUeUD4IgoAypFTQsnLlylK9j1pUvNrVeNSrVy98gi2sy4ZO7OpLH6vvvp//fYLjc6J1GWnRooXrEqdBz0HeY2rlKYouDh599FEbPXp0ePCwx9uuxRmIDKB8pXO5VxwqI0XzDgVbmtT9V0FatDKScg8oHyRGAMqQ1z1Dfb+jUWazIHXt0knO359e2YcUOMR7U2Ymz2677eZqVL/44osCn6V++apVjGc+C2+ZaO/jPbbvvvuGH/MuMPyZk/zfRzRxalG8yVCVMCHI2676jgAqh3Qu94pDlTca86RAJ9ilTq1MCgCjlZGUe0D5oCUIKOMaUV0QaLLQaNTfXRmK/CdjJQ4Qf1rX0vSNV1cNTfSnsTaa9dz/vkpfnZ2d7cbt+M2bN89yc3Mjuqodc8wxbvDyM88849LZeuliNXh57Nix1q1bt3DNpteCo4HKSmpwxBFHhLusaVC0Lh703m3atHGPaRJCXZTUrl07Yj30mLJGSbQsT95FSPfu3ePeNgDKVzqXe8WlclIt3ConlRjBP8WAsuMpY14Q5R5QTspp/iEgrScN1KE1Z86c8GPz5893j+29996hOnXqhK655prQY489Fjr22GPd4wcffHAoLy+vzNZBE/s1adIkVLNmTTcp3zPPPBM66qij3GfdcMMNBZZv1aqVey7oySefdI937NgxNGLEiND999/vlq1du3bo22+/LbD8mWee6Zbv2bNn6NFHH3Wftc0224SqVq0amjhxYni5b775xk1IOHjw4NDdd98devbZZ91222233dzrjzjiiFB+fn6B9+/cuTOTpQKVUDqXe7fddlv4pte1adMmfH/06NERy65fvz60++67uwlTzzrrrNATTzwROuecc0KZmZmhFi1ahP7+++8C70+5B5QPgiCgjC1ZsiRUpUqViJOudzFw0003hV5//fXQnnvuGapWrZo7YV988cVu1vGy9vvvv4dOPPHEUMOGDd1nKcB46qmnoi4b62JAxo4dG9pvv/1CNWrUCNWrV89dVMyePTvqsrqgefjhh93Fgz5Ty/fu3Ts0Y8aMiOWWL18euuiii9x2qF+/figrKyvUoEGDUNeuXd06Rrsw+vXXX9066qIEQOWSzuWe3iPWTWVa0OrVq0OXXXaZC3q0zZo1a+YCosWLFxdYlnIPKD8Z+l95tTIB6UrdKV599VX7/fffrVatWm7mdPUFv+mmmwoM9kd8zjvvPJswYYLLMOcNhgZQeVDulT3KPaD8kBgBKAcKdJTpSPNgoPQUTD733HNuQkECIKByotwrW5R7QPkiMQJQDpQCVSlZUTY0X9CWLVvYnEAlRrlXtij3gPJFSxAAAACAtMKYIAAAAABphZYgAAAAAGmFIAgAAABAWiEIAgAAAJBWCIIAAAAApBWCIAAAAABphSAIAAAAQFohCAIAAACQVgiCAAAAAKQVgiAAAAAAaYUgCAAAAEBaIQgCAAAAYOnk/wDFMuzecdGZmAAAAABJRU5ErkJggg==",
|
||
"text/plain": [
|
||
"<Figure size 720x540 with 1 Axes>"
|
||
]
|
||
},
|
||
"metadata": {},
|
||
"output_type": "display_data"
|
||
},
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"Saved: grand_avg_latency.png\n",
|
||
"\n",
|
||
"Grand-average latency (across-subject mean ± SEM) & Paired T-Test:\n",
|
||
" MI FES = 2.523 ± 0.032 s NOFES = 2.235 ± 0.084 s Δ = +0.288 s | p = 0.0632 (t = 2.89, n = 4)\n",
|
||
" REST FES = 2.135 ± 0.094 s NOFES = 2.391 ± 0.102 s Δ = -0.256 s | p = 0.0163 (t = -4.89, n = 4)\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"# Grand average across subjects: one pair of bars per class (MI, REST).\n",
|
||
"# Each subject contributes one mean (averaged across their sessions) per condition,\n",
|
||
"# so error bars = between-subject SEM.\n",
|
||
"from scipy.stats import ttest_rel\n",
|
||
"\n",
|
||
"def subject_means(data):\n",
|
||
" return {cond: np.array([np.mean(data[s][cond]) for s in subjects if data[s][cond]])\n",
|
||
" for cond in ('FES', 'NOFES')}\n",
|
||
"\n",
|
||
"mi_sub = subject_means(mi_lat)\n",
|
||
"rest_sub = subject_means(rest_lat)\n",
|
||
"\n",
|
||
"fig, ax = plt.subplots(figsize=(6, 4.5))\n",
|
||
"classes = ['MI', 'REST']\n",
|
||
"x = np.arange(len(classes))\n",
|
||
"width = 0.38\n",
|
||
"\n",
|
||
"p_values = {}\n",
|
||
"for cls, d in [('MI', mi_sub), ('REST', rest_sub)]:\n",
|
||
" subjects_with_both = [s for s in subjects if mi_lat[s]['FES'] and mi_lat[s]['NOFES']] if cls == 'MI' else [s for s in subjects if rest_lat[s]['FES'] and rest_lat[s]['NOFES']]\n",
|
||
" fes_paired = np.array([np.mean(mi_lat[s]['FES']) if cls == 'MI' else np.mean(rest_lat[s]['FES']) for s in subjects_with_both])\n",
|
||
" nofes_paired = np.array([np.mean(mi_lat[s]['NOFES']) if cls == 'MI' else np.mean(rest_lat[s]['NOFES']) for s in subjects_with_both])\n",
|
||
" \n",
|
||
" if len(fes_paired) > 1:\n",
|
||
" _, p_val = ttest_rel(fes_paired, nofes_paired)\n",
|
||
" p_values[cls] = p_val\n",
|
||
" else:\n",
|
||
" p_values[cls] = np.nan\n",
|
||
"\n",
|
||
"for i, cond in enumerate(('FES', 'NOFES')):\n",
|
||
" means = [mi_sub[cond].mean(), rest_sub[cond].mean()]\n",
|
||
" sems = [mi_sub[cond].std(ddof=1) / np.sqrt(len(mi_sub[cond])),\n",
|
||
" rest_sub[cond].std(ddof=1) / np.sqrt(len(rest_sub[cond]))]\n",
|
||
" offset = (i - 0.5) * width\n",
|
||
" ax.bar(x + offset, means, width, yerr=sems,\n",
|
||
" color=cond_color[cond], label=cond, edgecolor='white', capsize=5)\n",
|
||
" for j, arr in enumerate([mi_sub[cond], rest_sub[cond]]):\n",
|
||
" ax.scatter(np.full(len(arr), x[j] + offset), arr,\n",
|
||
" color='k', alpha=0.6, s=20, zorder=3)\n",
|
||
"\n",
|
||
"# Modify X-labels to contain the P-Values below each\n",
|
||
"new_labels = []\n",
|
||
"for cls in classes:\n",
|
||
" p_val = p_values[cls]\n",
|
||
" if not np.isnan(p_val):\n",
|
||
" p_str = f'p={p_val:.3f}' if p_val >= 0.001 else 'p<0.001'\n",
|
||
" new_labels.append(f'{cls}\\n({p_str})')\n",
|
||
" else:\n",
|
||
" new_labels.append(cls)\n",
|
||
"\n",
|
||
"ax.set_xticks(x); ax.set_xticklabels(new_labels)\n",
|
||
"ax.set_ylabel('BEGIN → EARLYSTOP latency (s)')\n",
|
||
"ax.set_title(f'Grand-average EARLYSTOP latency across {len(subjects)} subjects\\n'\n",
|
||
" '(points = per-subject means, bars = across-subject mean ± SEM)',\n",
|
||
" fontweight='bold')\n",
|
||
"ax.legend(); ax.grid(axis='y', alpha=0.3)\n",
|
||
"ax.spines[['top','right']].set_visible(False)\n",
|
||
"plt.tight_layout()\n",
|
||
"plt.savefig('grand_avg_latency.png', dpi=150, bbox_inches='tight')\n",
|
||
"plt.show()\n",
|
||
"print('Saved: grand_avg_latency.png')\n",
|
||
"\n",
|
||
"print('\\nGrand-average latency (across-subject mean ± SEM) & Paired T-Test:')\n",
|
||
"sem = lambda a: a.std(ddof=1) / np.sqrt(len(a)) if len(a) > 1 else 0.0\n",
|
||
"for cls, d in [('MI', mi_sub), ('REST', rest_sub)]:\n",
|
||
" # Ensure arrays are aligned for t-test by taking paired subjects only\n",
|
||
" subjects_with_both = [s for s in subjects if mi_lat[s]['FES'] and mi_lat[s]['NOFES']] if cls == 'MI' else [s for s in subjects if rest_lat[s]['FES'] and rest_lat[s]['NOFES']]\n",
|
||
" \n",
|
||
" fes_paired = np.array([np.mean(mi_lat[s]['FES']) if cls == 'MI' else np.mean(rest_lat[s]['FES']) for s in subjects_with_both])\n",
|
||
" nofes_paired = np.array([np.mean(mi_lat[s]['NOFES']) if cls == 'MI' else np.mean(rest_lat[s]['NOFES']) for s in subjects_with_both])\n",
|
||
" \n",
|
||
" delta = d['FES'].mean() - d['NOFES'].mean()\n",
|
||
" \n",
|
||
" if len(fes_paired) > 1:\n",
|
||
" t_stat, p_val = ttest_rel(fes_paired, nofes_paired)\n",
|
||
" stats_str = f'p = {p_val:.4f} (t = {t_stat:.2f}, n = {len(fes_paired)})'\n",
|
||
" else:\n",
|
||
" stats_str = 'Not enough paired data for t-test'\n",
|
||
" \n",
|
||
" print(f' {cls:<5} FES = {d[\"FES\"].mean():.3f} ± {sem(d[\"FES\"]):.3f} s '\n",
|
||
" f'NOFES = {d[\"NOFES\"].mean():.3f} ± {sem(d[\"NOFES\"]):.3f} s '\n",
|
||
" f'Δ = {delta:+.3f} s | {stats_str}')"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"id": "21da9cda",
|
||
"metadata": {},
|
||
"source": [
|
||
"---\n",
|
||
"## Figure 6 — Decision-margin distribution shift (Wasserstein-1)\n",
|
||
"\n",
|
||
"Mean |margin| collapses the whole distribution to a scalar. If FES spreads the margin\n",
|
||
"distribution further from zero (or sharpens it into a narrow high-confidence mode) without\n",
|
||
"moving the mean, that shows up here but not in mean amplitude. For each (subject × pair),\n",
|
||
"we compute W₁ between the FES and NOFES margin distributions, separately for MI and REST\n",
|
||
"trials. Larger W₁ = greater distributional divergence between conditions."
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 33,
|
||
"id": "41bf28d0",
|
||
"metadata": {
|
||
"execution": {
|
||
"iopub.execute_input": "2026-04-22T19:27:28.519611Z",
|
||
"iopub.status.busy": "2026-04-22T19:27:28.519516Z",
|
||
"iopub.status.idle": "2026-04-22T19:27:28.702716Z",
|
||
"shell.execute_reply": "2026-04-22T19:27:28.702337Z"
|
||
}
|
||
},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"image/png": 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|
||
"text/plain": [
|
||
"<Figure size 1560x540 with 2 Axes>"
|
||
]
|
||
},
|
||
"metadata": {},
|
||
"output_type": "display_data"
|
||
},
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"Saved: margin_wasserstein.png\n",
|
||
"\n",
|
||
"Mean W₁ across 7 (subject × pair) comparisons:\n",
|
||
" MI trials: 1.207 ± 1.150\n",
|
||
" REST trials: 0.785 ± 0.623\n",
|
||
" W₁(MI) > W₁(REST) in 6/7 comparisons — FES perturbs MI margins more than REST margins\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"w_results = [] # one row per (subject, pair) — Wasserstein between FES and NOFES margin dists\n",
|
||
"for subj in subjects:\n",
|
||
" for pair in PAIRS:\n",
|
||
" fes = next((r for r in results if r['subject']==subj and r['pair']==pair['name']\n",
|
||
" and r['condition']=='FES'), None)\n",
|
||
" nof = next((r for r in results if r['subject']==subj and r['pair']==pair['name']\n",
|
||
" and r['condition']=='NOFES'), None)\n",
|
||
" if fes is None or nof is None: continue\n",
|
||
" if fes['margin'].size == 0 or nof['margin'].size == 0: continue\n",
|
||
"\n",
|
||
" def w1(fe_mask, no_mask):\n",
|
||
" f = fes['margin'][fe_mask]; n = nof['margin'][no_mask]\n",
|
||
" return wasserstein_distance(f, n) if (f.size and n.size) else np.nan\n",
|
||
"\n",
|
||
" w_results.append(dict(\n",
|
||
" subject=subj, pair=pair['name'].split()[0],\n",
|
||
" w_mi = w1(fes['y_test'] == 1, nof['y_test'] == 1),\n",
|
||
" w_rest = w1(fes['y_test'] == 0, nof['y_test'] == 0),\n",
|
||
" w_all = wasserstein_distance(fes['margin'], nof['margin']),\n",
|
||
" fes_mi_mean = fes['margin'][fes['y_test']==1].mean() if (fes['y_test']==1).any() else np.nan,\n",
|
||
" nofes_mi_mean = nof['margin'][nof['y_test']==1].mean() if (nof['y_test']==1).any() else np.nan,\n",
|
||
" ))\n",
|
||
"\n",
|
||
"if w_results:\n",
|
||
" labels = [f'{r[\"subject\"]}\\n{r[\"pair\"]}' for r in w_results]\n",
|
||
" w_mi = np.array([r['w_mi'] for r in w_results])\n",
|
||
" w_rest = np.array([r['w_rest'] for r in w_results])\n",
|
||
" x = np.arange(len(labels))\n",
|
||
"\n",
|
||
" fig, axes = plt.subplots(1, 2, figsize=(13, 4.5))\n",
|
||
" fig.suptitle('Wasserstein-1 distance between FES and NOFES decision-margin distributions',\n",
|
||
" fontsize=12, fontweight='bold', y=1.02)\n",
|
||
"\n",
|
||
" width = 0.4\n",
|
||
" axes[0].bar(x - width/2, w_mi, width, color='#E05C2A', label='MI trials', edgecolor='white')\n",
|
||
" axes[0].bar(x + width/2, w_rest, width, color='#2A7BE0', label='REST trials', edgecolor='white')\n",
|
||
" axes[0].set_xticks(x); axes[0].set_xticklabels(labels, fontsize=8)\n",
|
||
" axes[0].set_ylabel('W₁(FES margin, NOFES margin)')\n",
|
||
" axes[0].set_title('Per-(subject × pair), by trial class', fontweight='bold')\n",
|
||
" axes[0].legend(); axes[0].grid(axis='y', alpha=0.3)\n",
|
||
" axes[0].spines[['top','right']].set_visible(False)\n",
|
||
"\n",
|
||
" # Direction of the shift (FES mean − NOFES mean) on MI margins\n",
|
||
" fes_mi = np.array([r['fes_mi_mean'] for r in w_results])\n",
|
||
" nofes_mi = np.array([r['nofes_mi_mean'] for r in w_results])\n",
|
||
" mi_shift = fes_mi - nofes_mi\n",
|
||
" colors_sh = ['#E05C2A' if d > 0 else '#2A7BE0' for d in mi_shift]\n",
|
||
" axes[1].bar(x, mi_shift, color=colors_sh, edgecolor='white')\n",
|
||
" axes[1].axhline(0, color='k', lw=0.8)\n",
|
||
" axes[1].set_xticks(x); axes[1].set_xticklabels(labels, fontsize=8)\n",
|
||
" axes[1].set_ylabel('mean(FES MI-margin) − mean(NOFES MI-margin)')\n",
|
||
" axes[1].set_title('Direction of MI-margin shift (positive = FES margin more negative is\\ncolumn below zero; see sign convention in code)', fontsize=9, fontweight='bold')\n",
|
||
" axes[1].grid(axis='y', alpha=0.3)\n",
|
||
" axes[1].spines[['top','right']].set_visible(False)\n",
|
||
"\n",
|
||
" plt.tight_layout()\n",
|
||
" plt.savefig('margin_wasserstein.png', dpi=150, bbox_inches='tight')\n",
|
||
" plt.show()\n",
|
||
" print('Saved: margin_wasserstein.png')\n",
|
||
"\n",
|
||
" print(f'\\nMean W₁ across {len(w_results)} (subject × pair) comparisons:')\n",
|
||
" print(f' MI trials: {np.nanmean(w_mi):.3f} ± {np.nanstd(w_mi, ddof=1):.3f}')\n",
|
||
" print(f' REST trials: {np.nanmean(w_rest):.3f} ± {np.nanstd(w_rest, ddof=1):.3f}')\n",
|
||
" print(f' W₁(MI) > W₁(REST) in {int((w_mi > w_rest).sum())}/{len(w_results)} comparisons '\n",
|
||
" f'— FES perturbs MI margins more than REST margins')\n",
|
||
"else:\n",
|
||
" print('No comparisons available for Wasserstein analysis.')"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"id": "b3db60ba",
|
||
"metadata": {},
|
||
"source": [
|
||
"---\n",
|
||
"## Summary Statistics"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "markdown",
|
||
"id": "9f27a80e",
|
||
"metadata": {},
|
||
"source": [
|
||
"---\n",
|
||
"## Figure 4 — Within-session MI-accuracy trajectory (sliding window)\n",
|
||
"\n",
|
||
"Refined from the original \"thirds\" analysis to address its noise floor. Each online session\n",
|
||
"is parsed into chronological MI-only trials, then a W-trial sliding window gives a smoother\n",
|
||
"accuracy trajectory. The slope of a linear fit to this trajectory is a per-session \"learning\n",
|
||
"rate.\" Restricting to MI trials isolates the class that FES actually perturbs (orthotic +\n",
|
||
"stimulation fires on MI, not REST) — slope differences between FES and NOFES sessions would\n",
|
||
"indicate whether proprioceptive feedback accelerates within-session adaptation.\n",
|
||
"\n",
|
||
"Caveat: even with sliding windows, ~25–30 MI trials per session is low-N and the slope\n",
|
||
"estimator is noisy; read this as exploratory, not confirmatory."
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 34,
|
||
"id": "a9db789c",
|
||
"metadata": {
|
||
"execution": {
|
||
"iopub.execute_input": "2026-04-22T19:27:28.705422Z",
|
||
"iopub.status.busy": "2026-04-22T19:27:28.705328Z",
|
||
"iopub.status.idle": "2026-04-22T19:27:28.901376Z",
|
||
"shell.execute_reply": "2026-04-22T19:27:28.900874Z"
|
||
}
|
||
},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
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",
|
||
"text/plain": [
|
||
"<Figure size 1560x540 with 2 Axes>"
|
||
]
|
||
},
|
||
"metadata": {},
|
||
"output_type": "display_data"
|
||
},
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"Saved: within_session_mi_trajectory.png\n",
|
||
"\n",
|
||
"Condition-averaged slopes (FES − NOFES paired per session):\n",
|
||
" FES: mean slope = +0.0020 (n=8)\n",
|
||
" NOFES: mean slope = +0.0045 (n=8)\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"WINDOW = 8 # trials per sliding window\n",
|
||
"\n",
|
||
"lr_results = []\n",
|
||
"for r in results:\n",
|
||
" mi_successes = np.array([int(t['success']) for t in r['trials'] if t['cls'] == 'MI'])\n",
|
||
" if len(mi_successes) < WINDOW + 2:\n",
|
||
" continue\n",
|
||
" traj = np.array([mi_successes[i:i+WINDOW].mean()\n",
|
||
" for i in range(len(mi_successes) - WINDOW + 1)])\n",
|
||
" slope = np.polyfit(np.arange(len(traj)), traj, 1)[0]\n",
|
||
" lr_results.append(dict(subj=r['subject'], pair=r['pair'], cond=r['condition'],\n",
|
||
" traj=traj, slope=slope, n_mi=len(mi_successes)))\n",
|
||
"\n",
|
||
"# ── Figure 4a: slope per condition (FES vs NOFES) ─────────────────────────────\n",
|
||
"fig, axes = plt.subplots(1, 2, figsize=(13, 4.5))\n",
|
||
"fig.suptitle(f'MI-only within-session learning rate (window = {WINDOW} trials)',\n",
|
||
" fontsize=12, fontweight='bold', y=1.02)\n",
|
||
"\n",
|
||
"fes_slopes = np.array([r['slope'] for r in lr_results if r['cond'] == 'FES'])\n",
|
||
"nofes_slopes = np.array([r['slope'] for r in lr_results if r['cond'] == 'NOFES'])\n",
|
||
"\n",
|
||
"ax = axes[0]\n",
|
||
"means = [fes_slopes.mean(), nofes_slopes.mean()]\n",
|
||
"sems = [fes_slopes.std(ddof=1) / np.sqrt(len(fes_slopes)),\n",
|
||
" nofes_slopes.std(ddof=1) / np.sqrt(len(nofes_slopes))]\n",
|
||
"ax.bar(['FES', 'NOFES'], means, yerr=sems,\n",
|
||
" color=[cond_color['FES'], cond_color['NOFES']],\n",
|
||
" capsize=6, edgecolor='white')\n",
|
||
"# Overlay individual points\n",
|
||
"for i, slopes in enumerate([fes_slopes, nofes_slopes]):\n",
|
||
" ax.scatter(np.full(len(slopes), i) + np.random.uniform(-0.08, 0.08, len(slopes)),\n",
|
||
" slopes, color='k', alpha=0.5, s=20, zorder=3)\n",
|
||
"ax.axhline(0, color='k', linestyle='--', lw=0.8)\n",
|
||
"ax.set_ylabel('Slope of MI-accuracy trajectory\\n(Δ fraction correct / trial-step)')\n",
|
||
"ax.set_title('Condition-averaged learning rate', fontweight='bold')\n",
|
||
"ax.spines[['top','right']].set_visible(False)\n",
|
||
"ax.grid(axis='y', alpha=0.3)\n",
|
||
"\n",
|
||
"# ── Figure 4b: trajectories per (subject × pair) ─────────────────────────────\n",
|
||
"ax = axes[1]\n",
|
||
"for r in lr_results:\n",
|
||
" ax.plot(r['traj'], color=cond_color[r['cond']], alpha=0.6, lw=1.5,\n",
|
||
" label=r['cond'])\n",
|
||
"ax.axhline(0.5, color='gray', linestyle='--', lw=0.8, alpha=0.6)\n",
|
||
"ax.set_xlabel(f'Sliding window start (MI trial index, window = {WINDOW})')\n",
|
||
"ax.set_ylabel('MI accuracy within window')\n",
|
||
"ax.set_title('All session trajectories overlaid', fontweight='bold')\n",
|
||
"# Dedup legend\n",
|
||
"h, l = ax.get_legend_handles_labels()\n",
|
||
"seen = set()\n",
|
||
"handles = [(hh, ll) for hh, ll in zip(h, l) if not (ll in seen or seen.add(ll))]\n",
|
||
"ax.legend([h for h, _ in handles], [l for _, l in handles], loc='lower left')\n",
|
||
"ax.spines[['top','right']].set_visible(False)\n",
|
||
"ax.grid(axis='y', alpha=0.3)\n",
|
||
"\n",
|
||
"plt.tight_layout()\n",
|
||
"plt.savefig('within_session_mi_trajectory.png', dpi=150, bbox_inches='tight')\n",
|
||
"plt.show()\n",
|
||
"print('Saved: within_session_mi_trajectory.png')\n",
|
||
"print(f'\\nCondition-averaged slopes (FES − NOFES paired per session):')\n",
|
||
"print(f' FES: mean slope = {fes_slopes.mean():+.4f} (n={len(fes_slopes)})')\n",
|
||
"print(f' NOFES: mean slope = {nofes_slopes.mean():+.4f} (n={len(nofes_slopes)})')"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 42,
|
||
"id": "d26b244a",
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"image/png": 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",
|
||
"text/plain": [
|
||
"<Figure size 1560x540 with 2 Axes>"
|
||
]
|
||
},
|
||
"metadata": {},
|
||
"output_type": "display_data"
|
||
},
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"Saved: avg_within_session_mi_trajectory_by_pair.png\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"# Creating an aggregated view of trajectories by Calibration Pair\n",
|
||
"# Averages all subject trajectories under each condition/pair, padding with NaNs for uneven lengths\n",
|
||
"import warnings\n",
|
||
"\n",
|
||
"fig, axes = plt.subplots(1, 2, figsize=(13, 4.5), sharey=True)\n",
|
||
"fig.suptitle(f'Cross-Subject Average MI Trajectory split by Calibration Type (window = {WINDOW})',\n",
|
||
" fontsize=13, fontweight='bold', y=1.02)\n",
|
||
"\n",
|
||
"traj_groups = {}\n",
|
||
"for r in lr_results:\n",
|
||
" key = (r['pair'], r['cond'])\n",
|
||
" if key not in traj_groups:\n",
|
||
" traj_groups[key] = []\n",
|
||
" traj_groups[key].append(r['traj'])\n",
|
||
"\n",
|
||
"for i, (pair_name, sub_label) in enumerate(PAIRS_TO_PLOT):\n",
|
||
" ax = axes[i]\n",
|
||
" for cond in ['FES', 'NOFES']:\n",
|
||
" key = (pair_name, cond)\n",
|
||
" if key in traj_groups:\n",
|
||
" trajs = traj_groups[key]\n",
|
||
" max_len = max(len(t) for t in trajs)\n",
|
||
" \n",
|
||
" # Pad uneven trajectories with NaNs to average them step-by-step\n",
|
||
" padded = np.full((len(trajs), max_len), np.nan)\n",
|
||
" for j, t in enumerate(trajs):\n",
|
||
" padded[j, :len(t)] = t\n",
|
||
" \n",
|
||
" with warnings.catch_warnings():\n",
|
||
" warnings.simplefilter(\"ignore\", category=RuntimeWarning)\n",
|
||
" mean_traj = np.nanmean(padded, axis=0)\n",
|
||
" # Compute standard error of the mean for the shaded variance area\n",
|
||
" n_present = np.sum(~np.isnan(padded), axis=0)\n",
|
||
" sem_traj = np.nanstd(padded, axis=0, ddof=1) / np.sqrt(n_present)\n",
|
||
" \n",
|
||
" x_vals = np.arange(max_len)\n",
|
||
" ax.plot(x_vals, mean_traj, color=cond_color[cond], label=f'ONLINE_{cond} (avg)', lw=2)\n",
|
||
" \n",
|
||
" # Add a shaded semi-transparent region to show confidence interval / Variance\n",
|
||
" ax.fill_between(x_vals, mean_traj - sem_traj, mean_traj + sem_traj, \n",
|
||
" color=cond_color[cond], alpha=0.15, edgecolor='none')\n",
|
||
" \n",
|
||
" ax.axhline(0.5, color='gray', linestyle='--', lw=0.8, alpha=0.6)\n",
|
||
" ax.set_title(sub_label, fontweight='bold')\n",
|
||
" ax.set_xlabel(f'Sliding window start (trial index)')\n",
|
||
" ax.grid(axis='y', alpha=0.3)\n",
|
||
" ax.spines[['top','right']].set_visible(False)\n",
|
||
" \n",
|
||
"axes[0].set_ylabel('Average MI Accuracy within window')\n",
|
||
"axes[0].legend(loc='lower left')\n",
|
||
"\n",
|
||
"plt.tight_layout()\n",
|
||
"plt.savefig('avg_within_session_mi_trajectory_by_pair.png', dpi=150, bbox_inches='tight')\n",
|
||
"plt.show()\n",
|
||
"print('Saved: avg_within_session_mi_trajectory_by_pair.png')"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 44,
|
||
"id": "ddedb148",
|
||
"metadata": {},
|
||
"outputs": [
|
||
{
|
||
"data": {
|
||
"image/png": 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hRW/S6zwu3rjm1fGWFio7eiNfRxDpzWRNJ+du+vTpZp4bX3PNNfTkk096jGzYt2+f+eKbG3pTe//+/fLiiy+aUT+ueVu0XNOkTZ061XQ8cjLCJTd07hR9Lb0xrq/jHjSbNm1apvVvu+028/jYY495lGvKvtdff11q1Khh5i9y0f/XUV06CkhHYLjfvNd/a2BCRwdpYCgnwRTX/DkZ0+3pPriPqHHN+eQtxZlrhIr7SB89fxMmTJDcyu51sqLBDA0C6X5ntU1fpWZz7WvGkTfaznKbNs/XXG1p0qRJHvXbs2dPpvePvr/vuOMOM7+UBvC8cd8fbb/dunUzbeqtt94y71G9uaOjxb7//vtMz01JSTEpCVu1akUKOAAAbIj+R2b0P+h/uND/oP8BwP8YAQQgrGhARlN/dejQwYx40TlYdO6ODz74QFavXm1ShN1111253u7jjz8uH3/8sbnxq7/817l51q1bJytWrDCjDXQkhK+DJzpfkd5g1pEJOh+N3rjXm+t6g3/Dhg05vpmsI2U0AKEBLPdAhI4MKl68uCnX+UtcAQdf0TlhpkyZYkZF6CiMfv36mRFIixYt8prK65///KdZ9vzzz0tSUpK0a9dOfv/9d5k1a5a5iT979uxM+6z7Nm/ePPPvjAEgnYvHtU5O6OvpiCkNhGlgSQOJmi7w5MmTHikDNYimRowYIb179zYjXbRd6d/tt99uynVbXbt2NdvQwKPOU5Rbesw0OKHp1bQNaCBKRzY1btw42+d1797djFjSwFn16tU9lrnS/ul50X3U49mjRw/Ja5BFR5Bparu7777bpG/QuZh09JM/3hO5oedcj//SpUtNW9AArr5/tC1pAFjT17nTY6xBszvvvNMEeXWUnB5vbYc6ek7nc9LritL0djoyzBWUVNpOdDSQXh82bdpk2pHLypUr5ezZs2YZAACwH/ofmdH/oP/hQv+D/geAAmABQBhZt26d9e9//9tq1KiRlZCQYDmdTis2Nta6+uqrrQkTJlinTp3yWL9v3746PMCjbOzYsaZsz549HuXbtm2zOnXqZLZXrFgxq23bttb3339vtWzZ0qpUqZLHujktc9HX07q4O3funDVy5EirfPnyVlRUlFW7dm3rpZdesp599lmz/vr163N0TM6fP2/FxMSY53z99dcey2655RZT/uijj2Z6nrfjkNWxyW7/Fi1aZNWrV8/sQ9myZa2hQ4dav/zyi9mObs/d2bNnTVnNmjXN+iVKlLA6dOhgbdiwweu+vfbaa2Y7ur67o0ePWg6HwyzbvXt3Do6SZc2ZM8dq166dqaO+dunSpa0WLVpYb775ZqZ1p0yZYlWpUsW0L/f9SEtLM8tq1KhhRUdHW+XKlbMGDRpkHT9+PNM51mPo7Ri4mz9/vjnvhQoV8tpGvDl06JBZf8yYMZmWbd++3bRbbcO6Pfe2r+dOz6E3WdV1xYoVVoMGDayiRYta8fHxpj3puc1t+8/IF++f5ORka/To0VaFChXM+axVq5b1/PPPW/PmzTPrr1q1ymP9M2fOWBMnTrTq169vFSlSxLxnqlevbvXu3dv65JNPzDqLFy82zx0wYECmOrz33numzXXv3t2jvFevXlZiYqJ5HwIAAPuh/5EZ/Q/6Hy70P+h/APA/h/6nIAJNAICCMXjwYHnhhRfM6JiMc+UArlEqOipl9+7d6Sn/UPD27t0rNWvWNCOl9H0LAAAQiuh/4GLofwQH+h9AeCIABAAhStOHaVotd5qSSlPAaYotnfcG8EZTxml6sgcffFBGjhzJQQqQ/v37m1SRmjLOW9pDAACAYEL/A3lF/yM40P8AwhMBIAAIUWPGjJG1a9eaHNplypSRHTt2mHltTp8+LR9++KG0bds20FUEAAAAYBP0PwAACD3OQFcAAJA3zZo1MwGgGTNmmF9U6cTy11xzjTzyyCNmGQAAAAD4Cv0PAABCDyOAAAAAAAAAAAAAbCYi0BUAAAAAAAAAAACAbxEAAgAAAAAAAAAAsBkCQAAAAAAAAAAAADZDAAgAAAAAAAAAAMBmCAABAAAAAAAAAADYDAEgAAAAAAAAAAAAmyEABAAAAAAAAAAAYDMEgAAAAAAAAAAAAGyGABAAAAAAAAAAAIDNEAACAAAAAAAAAAAQe/k/sFYPyaZfefQAAAAASUVORK5CYII=",
|
||
"text/plain": [
|
||
"<Figure size 1680x1080 with 4 Axes>"
|
||
]
|
||
},
|
||
"metadata": {},
|
||
"output_type": "display_data"
|
||
},
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"Saved: avg_within_session_trajectory_cross_overlay.png\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"# Re-calculate trajectories for BOTH MI and REST trials to support the requested 2x2 overlay\n",
|
||
"WINDOW_BOTH = 8\n",
|
||
"\n",
|
||
"lr_results_all = []\n",
|
||
"for r in results:\n",
|
||
" for trial_type in ['MI', 'REST']:\n",
|
||
" successes = np.array([int(t['success']) for t in r['trials'] if t['cls'] == trial_type])\n",
|
||
" if len(successes) < WINDOW_BOTH + 2:\n",
|
||
" continue\n",
|
||
" traj = np.array([successes[i:i+WINDOW_BOTH].mean()\n",
|
||
" for i in range(len(successes) - WINDOW_BOTH + 1)])\n",
|
||
" lr_results_all.append(dict(\n",
|
||
" subj=r['subject'], pair=r['pair'], cond=r['condition'], \n",
|
||
" trial_type=trial_type, traj=traj\n",
|
||
" ))\n",
|
||
"\n",
|
||
"# Create a 2x2 grid: Rows = MI vs REST, Cols = ONLINE FES vs ONLINE NOFES\n",
|
||
"# In each subplot, overlay Pair 1 (FES CALIB) vs Pair 2 (NOFES CALIB)\n",
|
||
"fig, axes = plt.subplots(2, 2, figsize=(14, 9), sharey=True, sharex=True)\n",
|
||
"fig.suptitle(f'Cross-Subject Average Trajectory split by Online Condition & Trial Type (window = {WINDOW_BOTH})\\n'\n",
|
||
" 'Lines overlay Calibration Types: Pair 1 (FES) vs Pair 2 (NOFES)',\n",
|
||
" fontsize=13, fontweight='bold', y=1.02)\n",
|
||
"\n",
|
||
"TRIAL_TYPES = ['MI', 'REST']\n",
|
||
"ONLINE_CONDS = ['FES', 'NOFES']\n",
|
||
"\n",
|
||
"# Define distinct line colors / styles for the Calibration pairs to avoid confusion with Online Conds\n",
|
||
"# Pair 1 (FES_CALIB) -> dark orange-ish\n",
|
||
"# Pair 2 (NOFES_CALIB) -> dark blue-ish\n",
|
||
"calib_style = {\n",
|
||
" 'Pair1': {'color': '#d95f02', 'label': 'FES_CALIB (Pair 1)'},\n",
|
||
" 'Pair2': {'color': '#1f78b4', 'label': 'NOFES_CALIB (Pair 2)'}\n",
|
||
"}\n",
|
||
"\n",
|
||
"import warnings\n",
|
||
"\n",
|
||
"for row_idx, trial_type in enumerate(TRIAL_TYPES):\n",
|
||
" for col_idx, online_cond in enumerate(ONLINE_CONDS):\n",
|
||
" ax = axes[row_idx, col_idx]\n",
|
||
" \n",
|
||
" for pair_prefix, style_info in calib_style.items():\n",
|
||
" # Extract trajectories matching this specific combination:\n",
|
||
" # (trial_type, online_cond, pair starts with Pair1 or Pair2)\n",
|
||
" match_subset = [r['traj'] for r in lr_results_all \n",
|
||
" if r['trial_type'] == trial_type \n",
|
||
" and r['cond'] == online_cond \n",
|
||
" and r['pair'].startswith(pair_prefix)]\n",
|
||
" \n",
|
||
" if not match_subset:\n",
|
||
" continue\n",
|
||
" \n",
|
||
" max_len = max(len(t) for t in match_subset)\n",
|
||
" padded = np.full((len(match_subset), max_len), np.nan)\n",
|
||
" for j, t in enumerate(match_subset):\n",
|
||
" padded[j, :len(t)] = t\n",
|
||
" \n",
|
||
" with warnings.catch_warnings():\n",
|
||
" warnings.simplefilter(\"ignore\", category=RuntimeWarning)\n",
|
||
" mean_traj = np.nanmean(padded, axis=0)\n",
|
||
" n_present = np.sum(~np.isnan(padded), axis=0)\n",
|
||
" sem_traj = np.nanstd(padded, axis=0, ddof=1) / np.sqrt(n_present)\n",
|
||
" \n",
|
||
" x_vals = np.arange(max_len)\n",
|
||
" ax.plot(x_vals, mean_traj, color=style_info['color'], label=style_info['label'], lw=2)\n",
|
||
" ax.fill_between(x_vals, mean_traj - sem_traj, mean_traj + sem_traj, \n",
|
||
" color=style_info['color'], alpha=0.15, edgecolor='none')\n",
|
||
" \n",
|
||
" ax.axhline(0.5, color='gray', linestyle='--', lw=0.8, alpha=0.6)\n",
|
||
" ax.set_title(f'ONLINE: {online_cond} | Trials: {trial_type}', fontweight='bold')\n",
|
||
" ax.grid(axis='y', alpha=0.3)\n",
|
||
" ax.spines[['top','right']].set_visible(False)\n",
|
||
" \n",
|
||
" if row_idx == 1:\n",
|
||
" ax.set_xlabel('Sliding window start (trial index)')\n",
|
||
" if col_idx == 0:\n",
|
||
" ax.set_ylabel('Average Accuracy within window')\n",
|
||
" if row_idx == 0 and col_idx == 0:\n",
|
||
" ax.legend(loc='lower left')\n",
|
||
"\n",
|
||
"plt.tight_layout()\n",
|
||
"plt.savefig('avg_within_session_trajectory_cross_overlay.png', dpi=150, bbox_inches='tight')\n",
|
||
"plt.show()\n",
|
||
"print('Saved: avg_within_session_trajectory_cross_overlay.png')"
|
||
]
|
||
},
|
||
{
|
||
"cell_type": "code",
|
||
"execution_count": 35,
|
||
"id": "cf55268e",
|
||
"metadata": {
|
||
"execution": {
|
||
"iopub.execute_input": "2026-04-22T19:27:28.903912Z",
|
||
"iopub.status.busy": "2026-04-22T19:27:28.903829Z",
|
||
"iopub.status.idle": "2026-04-22T19:27:28.914870Z",
|
||
"shell.execute_reply": "2026-04-22T19:27:28.914546Z"
|
||
}
|
||
},
|
||
"outputs": [
|
||
{
|
||
"name": "stdout",
|
||
"output_type": "stream",
|
||
"text": [
|
||
"=== Aggregate across 8 complete (subject × pair) comparisons ===\n",
|
||
"\n",
|
||
"Metric FES NOFES paired Δ 95% CI (bootstrap) sign\n",
|
||
"----------------------------------------------------------------------------------------------------------------\n",
|
||
"Overall accuracy (markers) 0.821 ± 0.077 0.806 ± 0.075 +0.015 [ -0.040, +0.065] 4/7\n",
|
||
"MI accuracy 0.817 ± 0.108 0.775 ± 0.115 +0.042 [ -0.079, +0.142] 5/7\n",
|
||
"REST accuracy 0.825 ± 0.100 0.837 ± 0.061 -0.012 [ -0.070, +0.039] 4/7\n",
|
||
"MI EARLYSTOP latency (s) 2.523 ± 0.204 2.235 ± 0.209 +0.288 [ +0.058, +0.530] * 6/8\n",
|
||
"REST EARLYSTOP latency (s) 2.135 ± 0.303 2.391 ± 0.270 -0.256 [ -0.416, -0.077] * 2/8\n",
|
||
"Classification amplitude 2.237 ± 2.063 2.362 ± 1.813 +0.151 [ -0.142, +0.476] 4/7\n",
|
||
"Fisher ratio (test SNR) 2.307 ± 2.712 2.542 ± 3.263 +0.090 [ -1.065, +1.225] 3/7\n",
|
||
"μ-band SNR (REST/MI) 1.751 ± 0.671 1.747 ± 0.480 +0.065 [ -0.161, +0.299] 4/7\n",
|
||
"\n",
|
||
"* = 95% bootstrap CI excludes zero (suggestive at this n).\n",
|
||
"Sign column: number of (subject × pair) comparisons where FES > NOFES.\n"
|
||
]
|
||
}
|
||
],
|
||
"source": [
|
||
"def boot_paired_ci(deltas, n_boot=10000, alpha=0.05, seed=0):\n",
|
||
" \"\"\"Bootstrap percentile CI on the mean of paired differences.\"\"\"\n",
|
||
" rng = np.random.default_rng(seed)\n",
|
||
" d = np.asarray([x for x in deltas if x is not None and not (isinstance(x, float) and np.isnan(x))])\n",
|
||
" if len(d) == 0:\n",
|
||
" return (np.nan, np.nan, np.nan)\n",
|
||
" boot_means = d[rng.integers(0, len(d), size=(n_boot, len(d)))].mean(axis=1)\n",
|
||
" lo, hi = np.percentile(boot_means, [100*alpha/2, 100*(1-alpha/2)])\n",
|
||
" return float(d.mean()), float(lo), float(hi)\n",
|
||
"\n",
|
||
"\n",
|
||
"# Collect all (subject × pair) where both FES and NOFES exist\n",
|
||
"paired = []\n",
|
||
"for subj in subjects:\n",
|
||
" for pair in PAIRS:\n",
|
||
" fes = next((r for r in results if r['subject']==subj and r['pair']==pair['name']\n",
|
||
" and r['condition']=='FES'), None)\n",
|
||
" nof = next((r for r in results if r['subject']==subj and r['pair']==pair['name']\n",
|
||
" and r['condition']=='NOFES'), None)\n",
|
||
" if fes and nof: paired.append((fes, nof))\n",
|
||
"\n",
|
||
"print(f'=== Aggregate across {len(paired)} complete (subject × pair) comparisons ===\\n')\n",
|
||
"\n",
|
||
"METRICS_SUMMARY = [\n",
|
||
" ('acc', 'Overall accuracy (markers)'),\n",
|
||
" ('mi_acc', 'MI accuracy'),\n",
|
||
" ('rest_acc', 'REST accuracy'),\n",
|
||
" ('mi_latency', 'MI EARLYSTOP latency (s)'),\n",
|
||
" ('rest_latency', 'REST EARLYSTOP latency (s)'),\n",
|
||
" ('amp', 'Classification amplitude'),\n",
|
||
" ('fisher', 'Fisher ratio (test SNR)'),\n",
|
||
" ('mu_snr', 'μ-band SNR (REST/MI)'),\n",
|
||
"]\n",
|
||
"\n",
|
||
"hdr = (f'{\"Metric\":<28} {\"FES\":>18} {\"NOFES\":>18} '\n",
|
||
" f'{\"paired Δ\":>9} {\"95% CI (bootstrap)\":>24} {\"sign\":>10}')\n",
|
||
"print(hdr); print('-' * len(hdr))\n",
|
||
"\n",
|
||
"def fmt_mean_sd(arr):\n",
|
||
" a = np.array([x for x in arr if x is not None and not (isinstance(x, float) and np.isnan(x))])\n",
|
||
" if len(a) == 0: return ' -- '\n",
|
||
" sd = a.std(ddof=1) if len(a) > 1 else 0.0\n",
|
||
" return f'{a.mean():>8.3f} ± {sd:6.3f}'\n",
|
||
"\n",
|
||
"for k, label in METRICS_SUMMARY:\n",
|
||
" fes_v = [f[k] for f, _ in paired]\n",
|
||
" nof_v = [n[k] for _, n in paired]\n",
|
||
" deltas = [f - n for f, n in zip(fes_v, nof_v)\n",
|
||
" if f is not None and n is not None\n",
|
||
" and not (isinstance(f, float) and np.isnan(f))\n",
|
||
" and not (isinstance(n, float) and np.isnan(n))]\n",
|
||
" if not deltas:\n",
|
||
" print(f'{label:<28} {\"(no data)\":<18} {\"\":<18}')\n",
|
||
" continue\n",
|
||
" mean_d, lo, hi = boot_paired_ci(deltas)\n",
|
||
" d_arr = np.array(deltas)\n",
|
||
" n_pos, n_neg = int((d_arr > 0).sum()), int((d_arr < 0).sum())\n",
|
||
" ci_crosses_zero = (lo < 0 < hi)\n",
|
||
" marker = ' ' if ci_crosses_zero else ' *'\n",
|
||
" print(f'{label:<28} {fmt_mean_sd(fes_v):>18} {fmt_mean_sd(nof_v):>18} '\n",
|
||
" f'{mean_d:>+9.3f} [{lo:>+7.3f},{hi:>+7.3f}]{marker} '\n",
|
||
" f'{n_pos}/{n_pos+n_neg}')\n",
|
||
"\n",
|
||
"print('\\n* = 95% bootstrap CI excludes zero (suggestive at this n).')\n",
|
||
"print('Sign column: number of (subject × pair) comparisons where FES > NOFES.')"
|
||
]
|
||
}
|
||
],
|
||
"metadata": {
|
||
"kernelspec": {
|
||
"display_name": "venv",
|
||
"language": "python",
|
||
"name": "python3"
|
||
},
|
||
"language_info": {
|
||
"codemirror_mode": {
|
||
"name": "ipython",
|
||
"version": 3
|
||
},
|
||
"file_extension": ".py",
|
||
"mimetype": "text/x-python",
|
||
"name": "python",
|
||
"nbconvert_exporter": "python",
|
||
"pygments_lexer": "ipython3",
|
||
"version": "3.13.7"
|
||
}
|
||
},
|
||
"nbformat": 4,
|
||
"nbformat_minor": 5
|
||
}
|