{ "cells": [ { "cell_type": "markdown", "id": "1b28ed17", "metadata": {}, "source": [ "# Worked example: Chicago backtest (committed fixture)\n", "\n", "This notebook uses a **committed sample dataset** at\n", "`docs/tutorials/data/chicago_sample_2024_2025.parquet` so local vignette\n", "rendering is fast and reproducible without live API calls.\n", "\n", "If you want to refresh data from the Socrata API yourself, use:\n", "\n", "```bash\n", "uv run motac fetch chicago --start-year 2024 --end-year 2025 --out-dir docs/tutorials/_local_data\n", "```\n", "\n", "The analysis below intentionally runs against the checked-in fixture." ] }, { "cell_type": "code", "execution_count": 1, "id": "e7227b09", "metadata": { "execution": { "iopub.execute_input": "2026-02-25T11:44:35.774800Z", "iopub.status.busy": "2026-02-25T11:44:35.774533Z", "iopub.status.idle": "2026-02-25T11:57:52.077821Z", "shell.execute_reply": "2026-02-25T11:57:52.076577Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Active cells: 318\n", "Counts shape: (318, 731)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Backtest metrics:\n", " nll: 1.0758\n", " rmse: 1.2192\n", " mae: 0.7499\n", " coverage: 0.9717\n" ] } ], "source": [ "from __future__ import annotations\n", "\n", "from collections import Counter\n", "from pathlib import Path\n", "\n", "import matplotlib.pyplot as plt\n", "import numpy as np\n", "import pandas as pd\n", "import scipy.sparse as sp\n", "\n", "\n", "def find_repo_root(start: Path) -> Path:\n", " for parent in [start] + list(start.parents):\n", " if (parent / \"pyproject.toml\").exists():\n", " return parent\n", " raise RuntimeError(\"Could not find repo root\")\n", "\n", "\n", "root = find_repo_root(Path.cwd())\n", "\n", "from motac.data import load_events_csv # noqa: E402\n", "from motac.models.fit import fit_road_hawkes_mle # noqa: E402\n", "from motac.models.forecast import forecast_probabilistic_horizon # noqa: E402\n", "from motac.models.metrics import mean_negative_log_likelihood # noqa: E402\n", "from motac.spatial.grid_builder import LonLatBounds, build_regular_grid # noqa: E402\n", "\n", "\n", "def scan_event_table(\n", " path: Path,\n", " *,\n", " lat_col: str,\n", " lon_col: str,\n", " mark_col: str | None,\n", " date_col: str,\n", ") -> tuple[tuple[float, float, float, float], Counter, list[str]]:\n", " if path.suffix.lower() in {\".parquet\", \".pq\"}:\n", " frame = pd.read_parquet(path)\n", " else:\n", " frame = pd.read_csv(path)\n", "\n", " frame[lat_col] = pd.to_numeric(frame[lat_col], errors=\"coerce\")\n", " frame[lon_col] = pd.to_numeric(frame[lon_col], errors=\"coerce\")\n", " frame = frame.dropna(subset=[lat_col, lon_col])\n", "\n", " lats = frame[lat_col].astype(float).to_numpy()\n", " lons = frame[lon_col].astype(float).to_numpy()\n", "\n", " marks: Counter = Counter()\n", " if mark_col and mark_col in frame.columns:\n", " marks.update(str(m) for m in frame[mark_col].dropna())\n", "\n", " dates = (\n", " pd.to_datetime(frame[date_col], errors=\"coerce\")\n", " .dropna()\n", " .dt.strftime(\"%Y-%m-%d\")\n", " .tolist()\n", " )\n", "\n", " if lats.size == 0 or lons.size == 0:\n", " raise ValueError(\"No valid lat/lon values found in source file\")\n", "\n", " bounds = (float(np.min(lons)), float(np.max(lons)), float(np.min(lats)), float(np.max(lats)))\n", " return bounds, marks, dates\n", "\n", "\n", "def build_travel_time(\n", " lat: np.ndarray,\n", " lon: np.ndarray,\n", " k: int = 6,\n", " speed_kph: float = 30.0,\n", ") -> sp.csr_matrix:\n", " lat = np.asarray(lat, dtype=float)\n", " lon = np.asarray(lon, dtype=float)\n", " n = int(lat.shape[0])\n", " lat_rad = np.radians(lat)\n", " lon_rad = np.radians(lon)\n", " mean_lat = float(np.mean(lat_rad))\n", " dx = (lon_rad[None, :] - lon_rad[:, None]) * np.cos(mean_lat)\n", " dy = lat_rad[None, :] - lat_rad[:, None]\n", " dist = 6_371_000.0 * np.sqrt(dx**2 + dy**2)\n", " np.fill_diagonal(dist, np.inf)\n", "\n", " k = min(int(k), max(n - 1, 1))\n", " idx = np.argpartition(dist, kth=k, axis=1)[:, :k]\n", " rows = np.repeat(np.arange(n), k)\n", " cols = idx.reshape(-1)\n", " data = dist[np.arange(n)[:, None], idx].reshape(-1)\n", "\n", " speed_mps = speed_kph * 1000.0 / 3600.0\n", " travel_time = data / speed_mps\n", "\n", " rows_sym = np.concatenate([rows, cols, np.arange(n)])\n", " cols_sym = np.concatenate([cols, rows, np.arange(n)])\n", " data_sym = np.concatenate([travel_time, travel_time, np.zeros(n)])\n", " return sp.csr_matrix((data_sym, (rows_sym, cols_sym)), shape=(n, n))\n", "\n", "\n", "fixture_path = root / \"docs\" / \"tutorials\" / \"data\" / \"chicago_sample_2024_2025.parquet\"\n", "if not fixture_path.exists():\n", " raise FileNotFoundError(\n", " \"Committed Chicago tutorial fixture not found at \"\n", " \"docs/tutorials/data/chicago_sample_2024_2025.parquet\"\n", " )\n", "\n", "bounds_tuple, mark_counts, dates = scan_event_table(\n", " fixture_path,\n", " lat_col=\"latitude\",\n", " lon_col=\"longitude\",\n", " mark_col=\"primary_type\",\n", " date_col=\"date\",\n", ")\n", "\n", "mark_order = [m for m, _ in mark_counts.most_common(3)]\n", "min_date = np.datetime64(min(dates), \"D\")\n", "max_date = np.datetime64(max(dates), \"D\")\n", "start_date = str(min_date)\n", "end_date = str(max_date)\n", "\n", "bounds = LonLatBounds(\n", " lon_min=bounds_tuple[0],\n", " lon_max=bounds_tuple[1],\n", " lat_min=bounds_tuple[2],\n", " lat_max=bounds_tuple[3],\n", ")\n", "\n", "grid = build_regular_grid(bounds, cell_size_m=1500.0)\n", "dataset = load_events_csv(\n", " path=fixture_path,\n", " grid=grid,\n", " date_col=\"date\",\n", " lat_col=\"latitude\",\n", " lon_col=\"longitude\",\n", " mark_col=\"primary_type\",\n", " event_id_col=\"id\",\n", " start_date=start_date,\n", " end_date=end_date,\n", " mark_order=mark_order,\n", ")\n", "\n", "counts = np.asarray(dataset.counts)\n", "if counts.ndim == 3:\n", " counts = counts.sum(axis=1)\n", "\n", "active_mask = counts.sum(axis=1) > 0\n", "active_idx = np.where(active_mask)[0]\n", "print(\"Active cells:\", active_idx.shape[0])\n", "\n", "counts = counts[active_idx]\n", "lat = grid.lat[active_idx]\n", "lon = grid.lon[active_idx]\n", "\n", "print(\"Counts shape:\", counts.shape)\n", "\n", "travel_time_s = build_travel_time(lat, lon)\n", "\n", "n_days = counts.shape[1]\n", "horizon = min(14, max(1, n_days // 5))\n", "n_train = n_days - horizon\n", "if n_train < 2:\n", " raise ValueError(\"Not enough days for backtest\")\n", "\n", "y_train = counts[:, :n_train]\n", "y_test = counts[:, n_train : n_train + horizon]\n", "\n", "kernel = np.array([0.6, 0.3, 0.1])\n", "fit = fit_road_hawkes_mle(\n", " travel_time_s=travel_time_s,\n", " kernel=kernel,\n", " y=y_train,\n", " maxiter=60,\n", " stability_mode=\"penalty\",\n", " mu_ridge=1e-4,\n", ")\n", "\n", "prob = forecast_probabilistic_horizon(\n", " travel_time_s=travel_time_s,\n", " mu=np.asarray(fit[\"mu\"], dtype=float),\n", " alpha=float(fit[\"alpha\"]),\n", " beta=float(fit[\"beta\"]),\n", " kernel=kernel,\n", " y_history=y_train,\n", " horizon=horizon,\n", " n_paths=200,\n", " seed=0,\n", ")\n", "\n", "lam = np.asarray(prob[\"count_mean\"])\n", "q = np.asarray(prob[\"count_quantiles\"])\n", "rmse = float(np.sqrt(np.mean((y_test - lam) ** 2)))\n", "mae = float(np.mean(np.abs(y_test - lam)))\n", "nll = mean_negative_log_likelihood(y=y_test, mean=lam)\n", "coverage = float(np.mean((y_test >= q[0]) & (y_test <= q[-1])))\n", "\n", "print(\"Backtest metrics:\")\n", "print(\" nll:\", round(nll, 4))\n", "print(\" rmse:\", round(rmse, 4))\n", "print(\" mae:\", round(mae, 4))\n", "print(\" coverage:\", round(coverage, 4))" ] }, { "cell_type": "code", "execution_count": 2, "id": "b7344b87", "metadata": { "execution": { "iopub.execute_input": "2026-02-25T11:57:52.081116Z", "iopub.status.busy": "2026-02-25T11:57:52.080636Z", "iopub.status.idle": "2026-02-25T11:57:52.555235Z", "shell.execute_reply": "2026-02-25T11:57:52.554033Z" } }, "outputs": [ { "data": { "image/png": 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", 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cqsYhhKhderUD+Dmfz4fT6aRZs2Y0bNiQAwcOVHj/4MGDDB8+HID09HQKCwvZtm0baWlpAKxYsQKfz0fPnj3rPHZxeUW7VqJ4XBiTmmNq1KbCe+EtuxLeKg3Hj9vIy5hDg3F/VClKEWocR3ZSsm8daLTED/91hRsIzM39iZPz9GG8jiJ04VFB7dvj9VBYZqewzE5BmY2CUhuFZTYKS/2vC0vtZ9+34VX8I+VWUxTx4bHERcQQHx579nH2eUQsVlMUGo0mqHGK0KYoCm6fB5fHhcvrxul14fKefX52m8fnIcZspVFUMuFGs9ohi4tQNXGaPn06w4cPJyUlhaKiIubOncuqVatYsmQJGo2GadOm8cwzz9C5c2e6dOnCRx99xA8//MDnn38O+Eefhg0bxuTJk/n73/+O2+1m6tSpjBs3rsp31Im6oyg+7NuXAGBJG1bpD47YQZNwHNlF6eHtOH7cTnir6+s6TBFifG4nuYveB8DSfQSmBi0qvK+PisWQ0AT3mROUHttNZLtel21TURRKPWUUltrOS4jOJkCltrMJkf+9Ilf159zZnEXYnEUcLjhW6fsGrZ648BgSImKJCyRWZ5OriFjizTEY9cZq96smn89HkauYImcJdmcxdmcRRc4SilzF2MuKsLtKKHYWo6Cg0+jQaf0PvUaHXqs/+1qL/vz3tGff05x7ff5z/dn9dJoLnwden+3jXJv6Cq895yUzLq8LZ/mfgW3uswlOxSTH6T13jMvjPvd++fYKbbpwez0oVP0m9pgwK40syRc8YsKsknSrTNXEKScnhwkTJnD69GmsViudOnViyZIlDB48GIBHH32UsrIyHnvsMfLz8+ncuTMZGRm0bNky0MYnn3zC1KlTGThwIFqtlrFjx/LXv/5VrVMSl1B6eCeegiy0pnAi2/epdB9jXEOs3Udg27SAvGVzMDfvhEYXcgOjog4VrvsCT2E2uqhYYvuOq3Sf8OadsZ05QcnhnXiadziXEJUnQWX280aI/K+d3qpfUtNptESHWYk2W4gJsxJtthId5n8eY7YE3os2WSjzOMl15J99FPj/LDn3vKDUhtvnIav4DFnFZy7ap8UU+bOEKq7CqJXFFIlWUzuzLRRFoczjpMhZfDYJKg48L3L9fJs/QSpxOaqVGFzLdBotRp0Ro96IUWfAqDNg0hnRaXXkluT7E/mzjz05Fa+6hBvMNIpKopGlAQ0tSTS2JNPI0oDEiDh0spRLnQi5dZzUIOs41Y2sT1/E8eM2LD1uJn7wvRfdz1dWwvFZU/E57MQNvhdrj5vrMEoRCnyKjzK3k8LsIxz57AXK8BHW51a8iSmUuB043KWUuEopcTuwlxWRZ8si355NiU6Lrxq/jZv1Yf6EJ8xKTJjlZwmR/3m02UqkMTxoSYrH6yG/zEZuSd7PEit/cnXGkY/T47xsO+WjVoHk6meXBePCYzGdHbXy+LwUnZf8/DzpsbuKKXIWYXeWBPZz+zw1Or8IYzgWUyQWYyRRpkgsJv+f5c81aPAqXjw+L16ft9Lngdc+Lx6l4vPz3/MqF+7r8XnOvvZdcKzX58V39nJqZZ/nuUTGiEl3XlKjN2L42XbTeUmPUWc8+6i43XTe9vPb1l8mwSlxOThVlM1JexY/2bM4aT/NSXsW2SW5Fy0vpNfqaRCVSKOoc6NTjS3JNIhKCvw7qG8URcHpcVLkKqHIWUKxq4RIYwQtYlOC3ld18gBJnJDEqS64C7M58e4UQKHJQ29jiL30pVT7jgxyv/072rAImjz0Drrwq/vvxefzUVBmI9eRT56jgFxHwdk/8/Eqvopf4jojRr3h3BfyeX9e+KVtuOCLu7ZGKX5+Pg63P7EpcZXicJeeTXYclLhLcZy3vcRdiqN8u8txdt+yGo9eaACLKapCEuRPjizEmK3+12cTojC9KbgnHgSKolDidpBbUnDeyNWFo1ZV+XyijBF4Ff/fRU0YdIZAEmQJiyTqZ8mQ5WfPI40RIT/q4VN8FZIpvVZfZ/8vrpTb6+Z0UQ4ni7ICSdUpexanirJxXWQdMw0a4iNi/SNTURUv+0WZIussdq/PS4nLcV4SVHz2Uq4/ISq/rFtcvu3sn56fJfB9Urrz2/T7gh5fdfIAuQYi6oR9+1JAwdyi82WTJoCozgOwb1uCKzuTgtXziB9ef8voKIqC3VlUISHKKy0gt+RsklRaQEGp7aK/CQebXqvHVElCFfiN+bwkzf9exe1unweH24HDVeZPjM5PfNylOFyllHrKghKrTlEw+xSiLIlEmiIJN5oJN4QTYTATbgwn3BCGxRRFjNmKZ+U8jCcOkjJgInH1eJRSo9EQaYwg0hhBs5jGle7j8XnJLy08b6TqbFJ1dhSrfNTq/PlZGjREmiLOJTvGiknPzxOhKFNkSCaWV0qr0aLVaTHoDGqHUm0GnYGU6EakRDeqsN2n+MgtyfcnUkXlo1T+R7GrhDMleZwpyWPH6b0VjrOYImlkaXD20p//kl9jSzJx4TGXnEfl9Lj8I5Mu/wjlucTHP4+tYjLk31ZSw+Qd/N9ZUcYIIk0RxIZH17idYJERJ66tEacyj9M/F0FR8KHgU3woioKi+PApZ1+j4Dtvm3Lefufvo5x9fuE+vgqvvV43Z5Z+iM9VRlT3ERgSU862799Hr9UTpjdhNpgI04dhNoRh1psg5xi2z17FgIYm97+KKamZ2h9fpRyuUv9IUem5UaJAguQoIK+0EHcVVrXWarTEmqP9l1nM0ZiO7iMyPwe9oqBt2Apju164fO7zJp6em7xacaLqhdt//ltbXTHpjIQbzUT8LNmJMISf2240E244mxAZzUQYzJi8XvJn/xFdaRGxA8YTnT7msn0Vrv+S/JWfEN66G8m3T6/9kwth5aNWeY4C9Fo9FlMkEYbwCnU+xdWv/Je2k/bss4nUaU6eTazyHAUXPc6kN9EwKpGGUUl4z076Lx8BKnKVVOn77GLCDeZAEuT/M5IoYwRRJv8vC1GmCKKMkec9j8CkN9X6hHgZcbrGFbtKyC7OJas4h6wi/wTU7LMTUQvLVCovE2MEjHB8LRyvxnEtEwAwrXyFcLOFML2JMIMJsz6MsLMJVoXnhjD/PuclYBWeG8Iw6YxV/k/o8rjIKy0kLzDRtzwhOndJraqjK9FhFuLCY/zzUsz+OSjxETHEmf1zU6LDLIEfbAVrP6cg8xgagwnF64Ef9hDbKI3oG26pxod3js/nq5BonX/30Pl3Cp1/99CF2/2JmEGrv0jiYybCeH6CZL7sXI6LyfnmXXSlRRgTU6o8x83cvAus/ITSY3tQvJ5r+qaC80etxLVLo9FgDbNgDbOQmti6wntl7jJOFWVXGJ06WZRFVlEOTo+TzIITZBZcfHFonUZ7YdJTSSJkMUUGkqQIY0SNvxNCybX7zVKPlf8WkVV85oLEKKv4DMWXuX1ap9Gi1WjRaDRoNFq0Gg1azj3XaLRo0Zy3j/+5f59z2y+2j1arRXPevq5TP6KUlWCKa4QxtsF5ffqP9fg8lHnKKHU7KfWUUXb2z1JPWWAipFOj4CyzBeXz02g0Z5Mrf9LlT7zOJWBlHid5JfnklhZQ5CyuUpsRxvCzyVBMYMKu/0//61hzdJUvDZQe30fBmk8BiB/2AD6ng7yl/yR/xb8xJqYQ3qJLtc9Zq9USpvWfX6grPb6X4u9XAPjXbKpiAmRMboY23ILPYafs5EHMKamXP0iIa1SYIYwWsU1pEdu0wnaPz0t28RlO2rPIKs7BoDWcTYIiAyNAkaYIzPqwa3ZZBEmcQpRP8VFQajubHOWQXZJ7NknKIav4DGWXuesmOsxCcmQCyZGJJEclkBQZT3JkIkmR8XX6W6jz1I+cXPcE6PQ0veN36CKsVT5WURTcXjen1vyHM1v+h8cah2XMb3H6vGcTrTJKPc6fPXdS5i67IAErc/vfK7/EWOr2H1PA5ZMxk8540YSofPQoWAmJt7SInK/fAsVHZMd+RHXqj6IouLIzKdq1gpz5b9DovpcxxFx8Zfz6TPG6A2s2RXUdTFjjNpc54hx/+ZWOlOxbR2nmLkmchKgBvVYXmDwuKieJk4q8Pi+5jvxzI0ZF50aNsktyL3kdWYOGuPCYs8lRAkmRCSRHnX0eER8yIwu2QF26XtVKmsA/MmTUG0npczua3Wvx5uUQe2Q/0b1urVEsPsWHy+Oi1OM8L5nyJ1yl7rLAqJdRZzjvNu8YIozhdfKblaIonFn4N7z2XAyxDYgfOhnwfw7xwx7AdeYEzlOHyPrvyzSa9CLaq3Bl4cINX+PO/QldhJXYm+6p9vHhLbr4E6cju6DfnbUQoRDiWieJUy1ze92cKckLJERZRWfILvH/mVOSGyjRUBmtRktiRNy5xCgygeSoRJIjE0iIiMMY4neFeB1F/jIZgKXb8Bq3ozWaiR1wD2cW/JWCdV8Q2fEm9FEx1W9HoyXM4L9cFUP1kri6YN+2GMfBzaDTkzjmcbSmc4mRRm8g6bbfc/Kf03CfOU7OgrdJGjvtqhoqdxdkUbjuC8C/grzOXP1bpSuUXyktrlEbQghxKZI41SK7s5jJX/3+kuutGLT6QFJ0LjnyP48Pj63XE+mKvl9xri5dw9aXP+ASIjvciH3rIpynDpG/6hMSR00NUpShwZmVSd6yOQDEDRh/QVkR8JcWSbrt95z6+GkcBzZRuO4LYvrcVseR1g5FUchd/AGKx4W5eSci299Yo3b0ljgM8Y1x5/7kL7/SNj3IkQohrnWSONUi/22U/hVbKyRGZ0eOkiLjiTVH14uF16pLUXzYt52tS9et8rp01aHRaIkbch+n5kyn+PuVWNKGEdawVTBCVZ3PVUbOV38Br4fwVmlYuo+86L5hjdsQP3Qyud/OomD1PIyJTYm4rnsdRls7Svavp/TITjQ6A/HDJl/Rvxdz887+xOnILkmchBBBJ4lTLdJoNPzt5hfqbI5MKCk9vANPYTbasMgajx78XFij64js2I/i3avJy/iQhhNeuCo+19wl/8SddwpdVCwJo6Ze9pwsXQfhys7Evm0xOQv+SqNJMzHGV75QYn3gLSshb+mHAET3vrVKC6ReSnjzzti3/I/SI7tQFOWq+DcihAgdV99QR4iJNEVck1/ctq3+SeFRnW9Cawje6sOx/e9GYwjD+dMBSvatDVq7ainas8Z/671GS+LoR6tcWiZu8L2EpaSiOB1kf/4yvrJLL0ERygpWzcVbUoghtiHR6b+44vbCmqaCVo/HloOnICsIEQohxDmSOImgcxdkUXp4BwCW64cGtW29JY7oXv4frnnL/43PFZzSHmpw558md9F7AET3uQ1z0/ZVPlaj05N06+/QWeJx550i5+u3UOqoZEswlZ08FLikGz/8ATT6K7/hQWs0B5YxcBzZdcXtCSHE+SRxEkF3ri5dFwyxDYLevrXnKPTWBLxFeRRu/Dro7dcFxesme/4bKK4ywlJSazTJWxdhJfm236PRG3H8uI2C1fNqIdLao/i8ZxNHhciO/TA36xi0ts0t/HfXlWZK4iSECC5JnERQ+dxOinYtB8CSNqxW+tAaTMQOnAiAbcNXeGxnaqWf2pS/8hNcWYfRmiNJHP0omhrePWlq0JL4Eb8GoHDdFxTv3xDMMGuVbcu3uLIz0YZFEnf27zNYws8uS1B6bA+KzxvUtoUQ1zZJnERQlexbh6+0GL01gfBW19daPxFtb/DP8fG4yFvx71rrpzY4Dm3DtukbABJunoreEndF7UV17Ie15ygAznzzDq6cY1ccY23z2HMDI2SxA8ZXe3HUyzEmN0drjkRxOnCeOhTUtoUQ1zZJnERQ2c+uFG65fmiNR1GqQqPREDf4PkBDyb51lJ3YX2t9BZOnKJ+che8AYOk+ImhLCcQOGI+5eScUdxlZ/30Jb2lRUNqtLblL/oniLsPUuC1RXQYEvX2NVoe5WSdA5jkJIYJLEicRNGUnD+E8fRiNzkBUl4G13p8puXmgn9ylH4b85GjF5yXn67fwOewYk5oTN2BC0NrWaHUkjnkcfXQinsIccub/JWQvUZUc3OJfIV2rI2H4g2hqaR2z8lXESyVxEkIEkaqJ06xZs+jUqRMWiwWLxUJ6ejqLFi26YD9FURg+fDgajYavvvqqwnvHjx9n5MiRhIeHk5iYyLRp0/B4PHV0BuJ89u3+0aaI1F5Vvq3+SsX2vwuNKRxX1hGKdq2skz5rqnD9fMqO7UFjCCPxF48H5Q6y8+nCo0j+5ZNoDCZKM78nf8XHQW0/GHyuUnKX/APwT/I3JqbUWl/mFv4RJ+epQ3jr8XINQojQomri1LhxY1566SW2bdvG1q1bGTBgAKNHj2bv3r0V9nvzzTcrXQvJ6/UycuRIXC4X69ev56OPPmLOnDk8/fTTdXUK4iyvw07J3rN16WppUnhldBFWYvr8EvCvB+RzOuqs7+ooO7GfgjWfAhA/bDLGuCtb5PFijIlNSRj1MAC2TQso2rOmVvqpqYLvPsNrz0VvTSTmxttrtS+DNRFDXENQfJQd3VOrfQkhrh2qJk6jRo1ixIgRtG7dmuuuu44XXniByMhINm7cGNhn586dvP7663z44YcXHL906VL27dvHxx9/TJcuXRg+fDjPP/887777Li6Xqy5P5ZpXtGsFiteNMbnlFdelqy5r9+EYYhvgLSmk4GyR2FDiLS0i+6s3QfER2bEfUZ3612p/ke3Sie49FoDc/83CefpwrfZXVc7so9g2LQQgftivgrow6sUELtfJsgRCiCAJmTlOXq+XefPmUVJSQnq6v76Uw+Hgrrvu4t133yU5OfmCYzZs2EDHjh1JSkoKbBs6dCh2u/2CUStRexSfN7CIoTUIdemqS6MzEDtoEgC2zQtx55+u0/4vRVEUziz8G157LobYBsQPnVwn/cb0G0d4qzQUj4usz1/BW2Krk34vRlF8/jWbFB8RbdMJb5VWJ/2WJ04OSZyEEEGieuK0e/duIiMjMZlM/PrXv2b+/PmkpqYC8Nhjj9GrVy9Gjx5d6bFZWVkVkiYg8Dor6+KlFpxOJ3a7vcJD1Jzj8A48thy0YZFEpPZWJYbwVmmYW3QBr4e85R+pEkNl7NsWn50IrSdxzONoTeY66Vej0ZI4+hEMcQ3x2nPJ/uJVFK96c/+KtmfgPHkQjdFM3OB766xfc9MOoNXhKcjCLeVXhBBBoHri1KZNG3bu3MmmTZt46KGHmDhxIvv27WPBggWsWLGCN998M+h9zpw5E6vVGng0adIk6H1cS8qXIIjqPKBOLr9URqPREDdoEmi0OA5uCYkRBmf2UfKX+ZO4uIHjMTVoUaf9a8MiSLrtCTSmcMpO7CcvY3ad9l/OU1xA/kr/RPXY/nde8bpV1aE1mQlrdB0ApZnf11m/Qoirl+qJk9FopFWrVqSlpTFz5kw6d+7MW2+9xYoVKzh8+DDR0dHo9Xr0ej0AY8eOpX///gAkJyeTnZ1dob3y15Vd2is3ffp0bDZb4HHixInaOblrgL8u3U5AgyUtuHXpqsuY0ARLN//E9LyM2areju9zlZEz/3UUr5vwVmlYuo9UJQ5jfGMSRz8CaLBvW4x9x7I6jyF/2Uf4nA6MyS3r9MaBcuYWXQBwHNlZ530LIa4+qidOP+fz+XA6nTz55JN8//337Ny5M/AAeOONN5g92/+bc3p6Ort37yYnJydwfEZGBhaLJXC5rzImkymwBEL5Q9SMf26TgrllFwwxF09W60rMjbejNUfiPnMC+/YM1eLIXfJP3Hmn0EXGkjBqap3P+zpfROtuxPQb549r8QeU/XSgzvp2HNlF8d7vQKMlYcSDtboo6sWYm/uXJSiT8itCiCBQNXGaPn06a9as4ejRo+zevZvp06ezatUq7r77bpKTk+nQoUOFB0BKSgrNmzcHYMiQIaSmpjJ+/Hh27drFkiVLeOqpp5gyZQomkzqXjK4l/rp0KwCwpg1XORo/nTmKmL53AlCw5j+qrKBdvOc7ir9fARotiWMerbM1rS4luvdYItreAD4P2Z+/gqcov9b79Hlc5C5+HwBLt2GYGrSs9T4rY2rQEm1YBL6ykpC5w1AIUX+pmjjl5OQwYcIE2rRpw8CBA9myZQtLlixh8ODBVTpep9OxcOFCdDod6enp3HPPPUyYMIE//elPtRy5ACjeuxZfWTH66ETMLbuoHU6A5frBGBJS8JUWU/DdZ3Xatzv/NGcWvQdAdJ/bMDdtX6f9X4xGoyFh1FQMCSl4SwrJ/vwVfJ7aXbKjcN0XeAqy0EXGEtvvzlrt61L85Vc6AlAql+uEEFdIr2bn//znP6u1v6IoF2xr2rQp3377bbBCElWkKEqd1aWrLo1WR/zgezk99znsWxdj6ToEY0Lt3wCgeN1kz38DxVVKWEoqMX1uq/U+q0NrNJP8yyc4+eETOE8dIm/xB8SP/E2tXEZ05f5E4fqvAIgbeh9aU3jQ+6gOc/POlPywkdLM72t94U0hxNUt5OY4ifrBeeoQrqwj/rp0nYNfpPVKmZt3Ivy67qD4yFs2u9KkO9jyV36CK+swWnMkiaMfDalkspwhJpnEXzwOGi1Fu1Zg33phiaMrpSgKuYveB58Hc8vriWhzQ9D7qC5zC/96TmU/HQjZ1eWFEPWDJE6iRspHmyLa9w6JOTyViRs4EXR6So/swvHjtlrty/HjNmybvgEg4eapdXrLfXWFt+hM7IDxgP/uw9JjwS1HUrx7NWXH96LRG4kfNlnVifHlDNFJ6GOSQfFRekwWxxVC1JwkTqLavCU2iveV16ULjUnhlTHENsDa42YA8pfNQfG6a6UfT1E+Od+8A4Cl+wgiruteK/0Ek7XnKCI79AXFR/aXr+OxnQlKu15HUWAB0pgbb8cQnRiUdoMh/OyyBDLPSQhxJSRxEtVWtGs5eD2YGrQirGErtcO5pJjeY9FFROPOP41tSy1clvJ5yfn6LXwOO8ak5sQNmBD0PmqDRqMhfsSvMSa3wOewk/Xfl/G5nVfcbv6Kf+Nz2DEkpGDtOSoIkQZP+bIEUrdOCHElJHES1aL4vNi3LwVQfcHLqtCawonpfxcABWv/G/SabYXr51N2bA8aQxiJv3gcjd4Q1PZrk9ZgIvm236MNt+DKziT3f7OuaC5Y6fF9/qQa/Gs26VS99+QC5qYdQKPFnX8ad2HO5Q8QQohKSOIkqsXx43Y8tjNozerVpauuqM43YUxuieJ0kL9qbtDaLTuxn4I1nwIQP2wyxriGQWu7ruitCSSN/R1odRTv/Q7bpgU1akfxuv1FfIGoLoMIa9w2mGEGhTYsAlOg/IqMOgkhakYSJ1Et5+rSDVStLl11aTRa4of4C8sW7VyOMyvzitv0lhaR/dWboPiI7NiPqE79r7hNtZhT2gcK7+av+LhGpUkKN36DO/cntOEWYgfcE+QIgye8uf/uOkmchBA1JYmTqDJ3/qmzE2vVr0tXXWFN2p0dIVPIy/jwii5JKYrCmYV/w2vPRR+TTPzQycELVCWWtGFEdR4Iio+c+W/gLsiq8rHugiwK1/4XgLhBE9GZo2orzCtWvixBaeZuKb8ihKgRSZxElfnr0kF4q+sxRCepHE31xQ0Yj0ZvpOz4Pkp+2FjjduzbluA4uBm0epJ+8X9oTeYgRqkOjUZD/LDJmBpdh6+smKz/voTPVXrZ4xRFIXfJP1A8LsKadSSyQ786iLbmTA1boTWF4ysrxnn6iNrhCCHqIUmcRJX43E6Kvl8J1I9J4ZXRWxOwpo8BIH/5RzW6i8yZfZT8ZXMAiBs4HlODFkGMUF0avYGksdPQRcbgPnOCnAVvoyi+Sx5T8sMGSg/vAJ0+ZNZsuhSNVkdYefkVuVwnhKgBSZxElRTv/Q5fWQn66CTMLbuqHU6NRaePQRcVh8d2JrBgZVX5XGXkzH8dxesmvFUalu4jaylK9eijYkm67feg0+M4sInCdV9edF9fWQl5Sz8EILrXrRjjGtVVmFdE5jkJIa6EJE7ishRFwb71bF26tKFoNPX3n43WYCJuoH/V7ML1X+Kx51X52Nwl/8SddwpdZCwJo6aG/OhKTYU1uo74YQ8AULD6P5Qc3FLpfvmr/4O3uABDbAOie/2iLkO8IhXLr1z+cqQQQpyv/v4EFHXGefIgruxMNHpjSNalq66I1D6YGrdBcTvJX/VJlY4p3vMdxd+vAI2WxDGPhmyZmWCxdBmIJW0YADlfv4Ur96cK75ed+jGQTMcPewCt3ljnMdaUISYZfXQS+LyUHpfyK0KI6pHESVxWoC5dap+QvmOqqjQaDfGD7wPO1lU7efCS+7vzT3Pm7BpF0X1uw9y0fa3HGAriBt9LWEoqiquU7P++jLesBPAvgpr77d8BhcgOfQMrctcn5vLLdUfkcp0QonokcRKX5C2xUbx/PQDWejopvDKmhq2I7HQTAHlLP7zoJGjF6ybnqzdQXKWENWlHTJ/b6jJMVWl0epJu/R06Szzu/FPkfPWmf+X4rYtwZWeiDYsgduBEtcOskfAWMs9JCFEzkjiJS7LvPFuXrmFrTCFel666YvvfjcYYhvPUIYr3rKl0n/yVc3GePozWHEnimEfRaHV1HKW6dBFWkm/7PRq9kdLD28ld/AH5q/8DQOxN96CPjFY3wBoKa9bRX34l72TQChwLIa4NkjiJi1J8Xoq2+9duKp/vcjXRR8UQ03ssAPkrPrlg3SLHj9sCJUgSbp6K3hJf5zGGAlODlsSPfAiAoh0ZKK4yTI3bENV1kMqR1ZwuLCLwi4BDRp2EENUgiZO4KMehbXjsuWjDLUSk9lI7nFph6XEz+ugkvMX5FK6fH9juKcon55t3/Pt0H0HEdd3VCjEkRHXoi7XnLf4XWh0Jwx+s13dXwnnznDK/VzkSIUR9Ur+/+UStOleXbkC9umuqOrR6I3Fn5+nYNi7AXZiD4vOSs+Cv+Bx2jEnNiRswQeUoQ0PsgHuI6XcniWMexZjYVO1wrti5eU7fX3ahTyGEKKdq4jRr1iw6deqExWLBYrGQnp7OokWLAMjPz+fhhx+mTZs2mM1mUlJS+O1vf4vNZqvQxvHjxxk5ciTh4eEkJiYybdo0PB6PGqdzVXHlnTo7cVaD5fohaodTq8Lb9CCsWUcUr5v85f+icP18yo7uRmMII/EXj6HRG9QOMSRotDpi+txGZLurY/TR1LA1GqMZX2kRriAUfhZCXBv0anbeuHFjXnrpJVq3bo2iKHz00UeMHj2aHTt2oCgKp06d4rXXXiM1NZVjx47x61//mlOnTvH5558D4PV6GTlyJMnJyaxfv57Tp08zYcIEDAYDL774opqnVu/Zt9fvunTV4V+e4F5++sfvKPlhAyUHNgEQP2xyvVkNW1SfRqfH3KwDjoNbcBzZhalBS7VDEkLUAxrlSsrE14LY2FheffVV7r///gve++9//8s999xDSUkJer2eRYsWcfPNN3Pq1CmSkvw/3P/+97/zxBNPcObMGYzGql1estvtWK1WbDYbFsvVvbBhVfhcZRz/62R8TgfJ454ivB6XWKmO3EXvBxLGyA59SRz9iMoRidpm27qIvCX/IKxpexre8ye1wxFCqKQ6eUDIzHHyer3MmzePkpIS0tPTK92n/IT0ev9A2YYNG+jYsWMgaQIYOnQodrudvXtlReCaKt77HT6nA31McqA8xbUgpt84dJZ4jIlNAyVHxNWtfJ5T2YkD+FxlKkcjhKgPVL1UB7B7927S09MpKysjMjKS+fPnk5qaesF+ubm5PP/88zzwwLkfaFlZWRWSJiDwOisr66J9Op1OnE5n4LXdbr/S07hqXE116apLF24hZcrfAK659ZquVfqYBuitCXhsZyg7vpfwVmlqhySECHGq/1Rs06YNO3fuZNOmTTz00ENMnDiRffv2VdjHbrczcuRIUlNTefbZZ6+4z5kzZ2K1WgOPJk2aXHGbVwvnyQO4co7669KdXVn7WqLR6iRpuoZoNJrAsgQOWZZACFEFqidORqORVq1akZaWxsyZM+ncuTNvvfVW4P2ioiKGDRtGVFQU8+fPx2A4d4dTcnIy2dnZFdorf52cnHzRPqdPn47NZgs8Tpw4EeSzqr/KR5si218ddemEuBxziy4AlB7ZqWocQoj6QfXE6ed8Pl/gMprdbmfIkCEYjUYWLFhAWFhYhX3T09PZvXs3OTk5gW0ZGRlYLJZKL/eVM5lMgSUQyh8CPMWFFO/fAIAlbbjK0QhRN8zNOgAa3Lk/4bHnqR2OECLEqTrHafr06QwfPpyUlBSKioqYO3cuq1atYsmSJYGkyeFw8PHHH2O32wNzkRISEtDpdAwZMoTU1FTGjx/PK6+8QlZWFk899RRTpkzBZDKpeWr1UtHOZeDzYGp0HaYGLdQOR4g6oTNHYWrYCuepQ5Rm7iKq8wC1QxJChDBVE6ecnBwmTJjA6dOnsVqtdOrUiSVLljB48GBWrVrFpk3+9XRatapYXDYzM5NmzZqh0+lYuHAhDz30EOnp6URERDBx4kT+9Ce5rbi6FJ8X+/alwNVZl06ISzE374Tz1CEcV1Hi5P8/nYGpYSvCrrIC3UKoSdXE6Z///OdF3+vfvz9VWWKqadOmfPvtt8EM65rkOLQVb1Gevy5du8qXgxDiamVu0ZnCdV8Eyq9cDXeT2rcuIi9jNrqIaFKm/l1WwBciSOr/t4MIivK6dJYuA6/aunRCXExYo+vQGMPwOey4so+qHc4V8zrsFHz3mf95SSFFe1arHJEQVw9JnASuvJP+CvEaLVFXeV06ISqj0Rkwp7QHoPTILpWjuXIFq+fhKysBnf+igm3jAilkLESQSOIkAqNN4a3SMFgTVY5GCHUEliXIrN+JkzP7KPYdGQAk3fo7NKZw3HkncRzapnJkQlwdJHG6xvlcpRR9vwoASzeZFC6uXebmnQAoPbEfn9t5mb1Dk6Io5GXMBsVHRNt0Iq7rjqXrYABsmxaoHJ0QV4caJU4tWrQgL+/C9U4KCwtp0UJuY69Pivd8h1Jel+7sDw4hrkWGuEboLPHg9VB2fN/lDwhBjgObKTu2B43OQOzACQBYu48ErZ6y4/soO3lI5QiFqP9qlDgdPXoUr9d7wXan08nJkyevOChRNxRFOTcpPG3YVXEnkRA1pdFoCD9bfqU+Xq5TPG7yln8EgPWGWzBE+y+76y1xRHboA4Bt49eqxSfE1aJayxEsWHBuqHfJkiVYrdbAa6/Xy/Lly2nWrFnQghO1y/nTD7hyjl2zdemE+Dlzi84U7VqO48gu4tQOpppsmxfiKcxGFxlDdK9fVHgvuudoir9fRcmBTbgLsjDEXLwklRDi0qqVOI0ZMwbw/2Y2ceLECu8ZDAaaNWvG66+/HrTgRO2ybV0EQGSHvujMkSpHI4T6zM06AhrcZ47jKSpAHxWjdkhV4ikqoGDd5wDEDrgHrdFc4X1jYgrmll0pPbwD26ZviB82WY0whbgqVOvajM/nw+fzkZKSQk5OTuB1eX25AwcOcPPNN9dWrCKIPMUFlPzgX5ldVgoXwk8XbsGY7J+nWZ8u1+WvmoviKsPUsDWRHfpWuk/0DaMBKNq1Aq/DXpfhCXFVqdGklszMTOLj44Mdi6hDRTuXn61L1wZTcnO1wxEiZIS3qF/znJynfqT4+xUAxA2576JzFcOadsCY3BLF48K+dXFdhijEVaXGJVeWL1/O8uXLAyNP5/vwww+vODBReyrUpZMlCISowNyiM4Xrv6wX5VcURSE3w/99G9mhL2GNrrvovhqNhugbbiHnqzewbVuENX00WoMUQxeiumr0jfDcc88xZMgQli9fTm5uLgUFBRUeIrQ5Dm4J1KWLbCt16YQ4X1ijNmgMJrwlhbhyjqsdziWV7FuL86cDaAwmYm+657L7R7RLR29NxOewU3x2/TYhRPXUaMTp73//O3PmzGH8+PHBjkfUAVugLt0gKfwpxM9o9AbCUtpTeng7pZm7MCU1UzukSvncTvKW/xuA6F63ordc/j5AjVaHtefN5C39kMJNC4jqOgiNVlfboQpxVanRiJPL5aJXr17BjkXUAVfuT5Qd3Q0aLRapSydEpQLznEK4bl3hhq/wFuWhtyZg7TmqysdFdR6ANiwST0EWjoNbajFCIa5ONUqcfvWrXzF37txgxyLqgH3bEgDCW6ehtyaoHI0Qocl8diHMshAtv+KxncG24SsAYgdOqNZcJa3RjCVtKACFG79GUZTaCFGIq1aNLtWVlZXx/vvvs2zZMjp16oTBUPFyz1/+8pegBCeCx+d2UrjhK+w7zk4KTxuuckRChC5DfGN0UbF4i/IpO/FDYAQqVOSt+DeKx0VYk3ZE1GCeoqXbCGwbF+A8eRDnTz8Q1qRdLUQpxNWpRonT999/T5cuXQDYs2dPhfc0Gs0VByWCR1EUSvatI2/Fv/HacwEIv6475uYdVY5MiNCl0WgwN+9M8fcrKc3cGVKJU9mJ/ZTsWwdozi4/UP3vXH1kNJEd+1G0cxmFG74mWRInIaqsRonTypUrgx2HqAXO00fIy/iQshP7AdBb4okdNJGItumS4ApxGeEtziZOR76HgWpH46coPnKXzgYgqstATMk1L6puveEWinYuw3FoC67cnzDGNw5WmEJc1Wq8jpMIXd4SG/mr5voXuURBozcS3etWrDfcIuu2CFFF5madAHDlHMVTXIA+Uv3yK8Xfr8KVdRiNKZyYfndeUVvGuEaEt+6O49AWbJu+IWHkQ0GKUoirW40mh990000MGDDgoo+qmjVrFp06dcJisWCxWEhPT2fRokWB98vKypgyZQpxcXFERkYyduxYsrOzK7Rx/PhxRo4cSXh4OImJiUybNg2Px1OT06r3FK+bwo0LOD5rKkU7lwEKke1vpMlDbxNz4y8laRKiGnQRVoxJ/lX1SzO/Vzka8Dkd5K/8BICYPrehj4y+4jaj08+WYdm9Ck+xrMEnRFXUaMSpfH5TObfbzc6dO9mzZ88FxX8vpXHjxrz00ku0bt0aRVH46KOPGD16NDt27KB9+/Y89thj/O9//+O///0vVquVqVOncuutt7Ju3ToAvF4vI0eOJDk5mfXr13P69GkmTJiAwWDgxRdfrMmp1VuOQ9vIWzYbd/5pAIzJLYgfcj9hTdqqHJkQ9Ze5RWdc2ZmUZn5PVMd+qsZSsO4LvCWFGGIbYO0+Iihtmhq3xdToOpwnD2LfuojY/ncFpV0hrmYaJYj3oj777LMUFxfz2muv1biN2NhYXn31VW677TYSEhKYO3cut912GwA//PAD7dq1Y8OGDdxwww0sWrSIm2++mVOnTpGUlAT4F+d84oknOHPmDEajsUp92u12rFYrNpsNi8VS49jV4Mr9ibyMOZQe2QH4f0uO6X83UZ1vCulSEULUB6WZ33N67nPoImNI+e0Hqs0NdBdkceK9R8DrIemXTxJxXfegtV3yw0ayv3gVbVgkKQ//Ha3RHLS2hagvqpMHBPUn6z333FPjOnVer5d58+ZRUlJCeno627Ztw+12M2jQoMA+bdu2JSUlhQ0bNgCwYcMGOnbsGEiaAIYOHYrdbmfv3r0X7cvpdGK32ys86htvWQm5GbP56YPH/UmTVo/1htE0eegdLF0GStIkRBCYmrRFozfiLS7AfeaEanHkLfsIvB7MLToT3rpbUNsOv647+phkfGXFFO1aEdS2hbgaBfWn64YNGwgLC6vWMbt37yYyMhKTycSvf/1r5s+fT2pqKllZWRiNRqKjoyvsn5SURFZWFgBZWVkVkqby98vfu5iZM2ditVoDjyZNmlQrZjWVF+g9MWsq9s0LweclvHU3mjz4BnEDJ6A1hasdohBXDa3eSFhKKgCOzJ2qxFCa+T2Og5tBoyVu0L1BH/XSaHVE97wFANumhSg+b1DbF+JqU6M5TrfeemuF14qicPr0abZu3cqMGTOq1VabNm3YuXMnNpuNzz//nIkTJ7J69eqahFVl06dP5/HHHw+8ttvt9SJ5Kj22l7ylH+LKOQr4F+mLGzSJ8JZd1Q1MiKuYuUVnSo/spPTIrkCCUVcUn5fcDP/yA5a0YRgTaud7KrJTf/LXzMNjy6Fk/wYi2/eplX6EuBrUKHGyWq0VXmu1Wtq0acOf/vQnhgypXv0zo9FIq1atAEhLS2PLli289dZb3HHHHbhcLgoLCyuMOmVnZ5OcnAxAcnIymzdvrtBe+V135ftUxmQyYTLVnzvM3LYc8pf/i5L9/kuU2rAIYvregeX6oWh0sqKEELUpvHkX8vmIsuP78HlcaPVVmzsZDPbtGbjPHEdrjiSm7+211o/WYMLabTgFaz6lcOPXRKT2lrXehLiIGv3UnT17drDjCPD5fDidTtLS0jAYDCxfvpyxY8cCcODAAY4fP056ur/EQHp6Oi+88AI5OTkkJiYCkJGRgcViITU1tdZirCs+VxmFG+Zj27gAxeMCjZaoroOI7TsOXYT18g0IIa6YIaEJusgYvMUFOE/8gLl5pzrp11taRMGaeQDE9B2HzhxVq/1Z0oZRuH4+rqwjlB3bg7mZVBcQojJXNFyxbds29u/3r0rdvn17unat3iWj6dOnM3z4cFJSUigqKmLu3LmsWrWKJUuWYLVauf/++3n88ceJjY3FYrHw8MMPk56ezg033ADAkCFDSE1NZfz48bzyyitkZWXx1FNPMWXKlHo1ovRz/jIpa8lb/m+8RXkAhDVtT9zg+zAlNVM3OCGuMYHyK7tX4cjcVWeJU8F3n+ErLcKQ0ATL9dUbya8JXbiFqM4DsG9bTOHGryVxEuIiapQ45eTkMG7cOFatWhW4jFZYWMhNN93EvHnzSEhIqHI7EyZM4PTp01itVjp16sSSJUsYPHgwAG+88QZarZaxY8fidDoZOnQof/vb3wLH63Q6Fi5cyEMPPUR6ejoRERFMnDiRP/3pTzU5rZDgPH2Y3KUf4vzpBwD01gR/mZQ2N8jQuRAqMTfvRPHuVZQe2QUDxtd6f64zJ7BvXQxA3OB70Wh1td4ngLXnKOzbl1J6eAeunOMYE1PqpF8h6pMareN0xx13cOTIEf71r3/Rrp2/OOS+ffuYOHEirVq14j//+U/QA61NobCOk6e4gIJVcynatRJQ0BhM/jIpPUfJit9CqMxTXMDxt34FQNNHP6zVS+WKopA178+UHtlJeOvuJN/+ZK31VZnsL16j5IcNRHbqT+Koh+u0byHUUp08oEYjTosXL2bZsmWBpAkgNTWVd999t9qTw691iseNbcv/KFj7OYqrFIDIDn2Jveke9JY4laMTQgDoI2MwJjbDlXOU0qPfE9n+xlrrq/TH7ZQe2QlaPXGDql6JIVisN4ym5IcNFO9ZS2y/u+R7SIifqVHi5PP5MBgMF2w3GAz4fL4rDupaoCgKjkNbyVs2B0+Bf80pU4OWxA25j7DGUiZFiFBjbtEJV85RHEd21VripHjd5C3z33xj7TESQ2yDWunnUsIatSYsJZWy4/uwbfkfcQMn1HkMQoSyGi2AOWDAAB555BFOnToV2Hby5Ekee+wxBg4cGLTgrlau3J/Imvdnsv/7Ep6CLHQR0STcPIWG974kSZMQIcrcvAsApZm7CGKlqgpsWxfhzj/tL53U57Za6aMqrDf4i//ad2TgczpUi0OIUFSjEad33nmHW265hWbNmgUWjjxx4gQdOnTg448/DmqAVxNvaTEF332GfesiUHyg02PtcTMxvcfKit9ChLiwJm3R6Ax4i/Jx5/4U9MUovSU2Cr77LwAx/e9S9TshvNX1GOIb4879CfuODKLPJlJCiBomTk2aNGH79u0sW7aMH37w3/3Vrl27CnXlxDmKz0vRjmXkr/4PvtIiwF8fKm7gRFWG4oUQ1ac1mAhLSaU0cxelmbuCnjjlr/4PitOBMbkFUZ1uCmrb1aXRaLH2vIXc//0N2+aFWLuPQKO7cHqGENeial2qW7FiBampqdjtdjQaDYMHD+bhhx/m4Ycfpnv37rRv357vvvuutmKtl0qP7eHkP6eRu/h9/5os8Y1JvvNpkn/5pCRNQtQz5hadAXAc2RXUdp1ZmRTtWAbU7fIDlxLVoS+6iGi8RfkU71undjhBpyg+HD9ux1NcoHYoop6pVuL05ptvMnny5Epv1bNarTz44IP85S9/CVpw9Z0z+yinP34GV84xtGERxA25n8aT/0L42S9fIUT9Ym7u/79bdnwviscdlDYVRSEvYzagEJHaG3NKaFQ90OgNWLqPBMC28etam9ellvyVn5D16Qtk//flq+7cRO2qVuK0a9cuhg0bdtH3hwwZwrZt2644qKuFKakZEW3TsaQNo8lD7/iHu0PgN0khRM0YE1PQRUSjuJ2UnTwQlDZLDmyk7PheNHojcXWwuGZ1WK4fgsYQhivnuH+JhKuEfftSbBu+AsB56hBlx/eqG5CoV6qVOGVnZ1e6DEE5vV7PmTNnrjioq0nirY8TP2wyunB1FtYUQgSPRqMNlFwpDcLlOp/HRf6yfwH+O9n01qpVXagrOnMkUV39c1dtG79WOZrgcBzeQe7iDwACn3fhhqvj3ETdqFbi1KhRI/bs2XPR97///nsaNJB5O+fTaGq04oMQIkSVX64Lxjwn26Zv8Nhy0EXFEp0+5orbqw3WHiNBo6X06G6cp4+oHc4VcWYfJfvL10DxEdmpPw3uehrQUHp4O64zx9UOT9QT1fqpPmLECGbMmEFZWdkF75WWlvLMM89w8803By04IYQINeWJkyvrCF6HvcbteIryKVz3JQBxAyagNYYFJb5gM1gTiUztDUDhpvo7MuOx55H16QsorjLCmnYgYcSvMcQ2JLxNDwAKNy5QOUJRX1QrcXrqqafIz8/nuuuu45VXXuHrr7/m66+/5uWXX6ZNmzbk5+fzxz/+sbZiFUII1emjYjAkpAAKpUd317id/JWfoLjLMDVqQ0T7PsELsBaUL4hZsm89bluOytFUn89ZStanL+ItyscQ35ik234fWF6hfKSveM93eOx5KkYp6otqJU5JSUmsX7+eDh06MH36dH7xi1/wi1/8gj/84Q906NCBtWvXkpSUVFuxCiFESCi/M7am85zKTh6kePcqAOKG3IdGowlSZLXDlNzcP7dL8WHbtFDtcKpF8XnJnv86rpyj6CKsJN/xR3RhEYH3wxpdR1iTduDzYNv6rYqRivqi2hNwmjZtyrfffktubi6bNm1i48aN5Obm8u2339K8efPaiFEIIUJKYJ5TDcqvKIqPvKUfAhDZqT9hDVsFPb7aYO15CwBFO5fjLS1WOZqqURSFvCX/pPTwDjR6I0m/nI4hOvGC/cpH1Iq2L8XnLK3rMEU9U+OZyzExMXTv3p0ePXoQExMTzJiEECKkhaWkgk6P156LO+9ktY4t3vMdzlOH0BjDiO1/Ty1FGHzmFl0wJjZFcZdh375U7XCqxLbpG+zblwAaEkc/Slij1pXuF946DUNcQ3xOB/adGXUbpKh35JYvIYSoJq3BhLlJOwBKM7+v8nE+Vyn5K/z1PKN7jUUfVX9+6dRoNFhv8I862bf8L2gLgNaW4h82kL/8IwBiB00kom3Pi+5bXmIGwLb5fyheT53EKOonSZyEEKIGyi/XVWdhyML1X+EtzkcfnYi1Z/27AzkytQ+6qDi8JYUU7VmtdjgXVXbyIGe+/isAlrRhWHtc/rOO7NjPX2LGnntVlpgRwSOJkxBC1EB53brS43tRvJcffXEX5mDb5L/lPW7gRLR6Y63GVxs0On0gCbFtXICi+FSO6ELugiyyPpuJ4nER3iqtypPvtXojlm7DgauzxIwIHkmchBCiBoxJzdCGW1BcZZSdPHjZ/fNX/AvF4yKsaQfC21z8slGos3QdhMYUjjvvJI5DoVViy1taRNanL+Bz2DEmNSfxF49Vq8yVJW3o2RIzxyjNDG4hZ3H1UDVxmjlzJt27dycqKorExETGjBnDgQMV6z9lZWUxfvx4kpOTiYiI4Prrr+eLL76osE9+fj533303FouF6Oho7r//foqL68ddH0KI+qk65VdKj++lZP8G0GiJG3xvyC8/cClaUziW64cAoVWGRfG4yf78Vdx5p9BFxZF8xx/QGs3VakNnjiKqywAgtM5NhBZVE6fVq1czZcoUNm7cSEZGBm63myFDhlBSUhLYZ8KECRw4cIAFCxawe/dubr31Vm6//XZ27NgR2Ofuu+9m7969ZGRksHDhQtasWcMDDzygxikJIa4h4eXznC4xQVzxeclbOhuAqK6DMCU1q4vQapW1+0jQ6ik7sb9Ko221TVEUznw7y18s2Wimwbg/oo+KrVFb1h6j/CVmMr/HmZUZ5EjF1UDVxGnx4sVMmjSJ9u3b07lzZ+bMmcPx48fZtu3c8O/69et5+OGH6dGjBy1atOCpp54iOjo6sM/+/ftZvHgx//jHP+jZsyd9+vTh7bffZt68eZw6dUqtUxNCXAPKJ4g7T/2It7So0n2Kdq3ElZ2J1hRObN9xdRlerdFHxRLZ4UbAP9dJbQXffUbx7tWg0ZI09ncYE5vWuC1DdCIR7dIBAnPShDhfSM1xstlsAMTGnvtNoVevXnz66afk5+fj8/mYN28eZWVl9O/fH4ANGzYQHR1Nt27dAscMGjQIrVbLpk2bKu3H6XRit9srPIQQorr0ljgM8Y3xl1+5sAC6r6yE/FWfABDT9w50EdY6jrD2RJ+9fb/kwCbcBVmqxVH0/SoKv/sMgPjhDxDeossVtxl9dkHM4r1r8djOXHF74uoSMomTz+fj0UcfpXfv3nTo0CGw/bPPPsPtdhMXF4fJZOLBBx9k/vz5tGrlX203KyuLxMSKK8Hq9XpiY2PJyqr8P/PMmTOxWq2BR5MmTWrvxIQQV7VLLUtQsO5zfA47hriGWNKG1XFktcuYmIK5ZdezZVi+USWG0qO7OfO/WQBY08dg6To4KO2aGrQkrGkH/7ltrl8lZkTtC5nEacqUKezZs4d58+ZV2D5jxgwKCwtZtmwZW7du5fHHH+f2229n9+6aF9ecPn06Npst8Dhx4sSVhi+EuEYF6tb9rPyKO/8Uts3+2mdxg+5Fo9OrEl9tKh+ZKdq1Aq+jbkfuXbk/kf35K+DzENGuF7E33R3U9svPzb5zGd6yksvsLa4lIZE4TZ06lYULF7Jy5UoaN24c2H748GHeeecdPvzwQwYOHEjnzp155pln6NatG++++y4AycnJ5ORUrNbt8XjIz88nOTm50v5MJhMWi6XCQwghaiIspT1o9XhsZ/AUnA5sz1v2Efg8mFt2JbzV9SpGWHvCmnbAmNwSxePCvnVxnfXrKS4ka94L+JwOTI3bkHDLw2g0wf1xZm7ZFUNCCoqrjKLtS4LatqjfVE2cFEVh6tSpzJ8/nxUrVlxQJNjhcACg1VYMU6fT4fP5F15LT0+nsLCwwoTyFStW4PP56Nmz/q6VIoSoH7TGMMKatAHAcXZZAseRnTgObQWtjrhBk1SMrnZpNBqi0/0jM7Zti/C5nbXep8/tJPu/L+Gx5aCPSSb5l0/WymKiGo2G6BvOK8MS4iVmRN1RNXGaMmUKH3/8MXPnziUqKoqsrCyysrIoLfVXp27bti2tWrXiwQcfZPPmzRw+fJjXX3+djIwMxowZA0C7du0YNmwYkydPZvPmzaxbt46pU6cybtw4GjZsqOLZCSGuFebmXQD/ek6K10Nehn/5AUu34RjjG1/iyPovou0N6K2J+Bx2ir9fWat9KT4vOV+/hfPUIbTmSJLv+CO68Nq7YhDZvg+6qFi8JYUU7/2u1voR9YuqidOsWbOw2Wz079+fBg0aBB6ffvopAAaDgW+//ZaEhARGjRpFp06d+Ne//sVHH33EiBEjAu188skntG3bloEDBzJixAj69OnD+++/r9ZpCSGuMeHlC2Ee24Nt6yLcuT+hDbcQ0+eXKkdW+zRaHdaeowAo3PQNis9ba33lr/g3jgObQKcn6bYnMMbV7i/HGp3Bv2YVULjx65AsMSPqnqqzFatSC6h169YXrBT+c7GxscydOzdYYQkhRLUYk5ujNUfhKy0if8W/AYjtOw6dOVLlyOpGVOcBFKz5FE9BFo6DW4hoe0PQ+7BtXRy4ey9x1FTMKalB76Mylq6DKVj7Oe7cnyj9cQfhrdPqpF8RukJicrgQQtRnGq0uUH4FnxdjYgpRXQepG1Qd0hrDsKQNBcpHZoJbINdxaBt5S/8JQEy/O4lsf2NQ278UbVhEYJmDQinDIpDESQghgiKQOAFxg++rVnHZq4Gl2wg0OgPOkwdx/vRD0Np1Zh0he/5fQPER1XkA0b3HBq3tqrL2GAlaHWXH91J26sc671+EFkmchBAiCCLa9MSY3AJL95GYm3VUO5w6p4+MJrJjPwAKNwRnZMZjzyXr0xdR3GWYm3UkfviDqhRI1lviiWzfBwDbxq/qvH8RWiRxEkKIINCZo2h8/6vED7lP7VBUY73hFkCD49AWXLk/XVFbPqeDrE9fwFtcgCGhCYljp6m6iKi1vMTMD+qWmBHqk8RJCCFEUBjjGhF+nb9u6JWUYVG8HrK/fB1XznF0EdEk3/EHdGERwQqzRkxJzTC36CJlWIQkTkIIIYIn+oYxABTtXoWnuKDaxyuKQu7iDyg9shONwUTy7dMxWBMvf2AdqFhipkjlaIRaJHESQggRNGFN2mJq1Aa8Huxbvq328bYNX1G0cxmgIXH0o5gatgp+kDUU1qwjxqTmKG4n9m11V2JGhBZJnIQQQgRVoEDu9qX4XKVVPq543zryV34MQNzgSUS06VEr8dVUhRIzW7+tkxIzIvRI4iSEECKowq/rhiG2Ab6yYop2rajSMWU//cCZBW8DYOk+AmuPm2szxBqLaJuO3hLvLzGze7Xa4QgVSOIkhBAiqDRaHdYe/jIstk0LL1uGxZ1/mqz/vozidRPeuntIF0bW6PSBEjO2TQtqtcSMCE2SOAkhhAi6yE790YZb8NhyKNm/4aL7eR1FZH36Aj6HHWNySxLHPBryi4dGdRmINiwCd/5pHAe3qh2OqGOq1qqrT3w+Hy6XS+0wRCUMBgM6XWh/0QpxrdEaTFi7DadgzacUbvyaiNTeFyxeqXjcZH/+Mu780+gt8STfPh2tMUyliKtOazRjuX4oheu/9J9b255qhyTqkCROVeByucjMzMTnk8rYoSo6Oprk5GRVVhUWQlTOkjaMwvXzcWUdoezYngorqiuKwpmF71J2Yj8aUzjJd/wRfVSMitFWj6XbCAo3LcB58gBlP/1AWOO2aock6ogkTpehKAqnT59Gp9PRpEkTtFq5uhlKFEXB4XCQk5MDQIMGDVSOSAhRThduIarzAOzbFlO44esKiVPB6nkU7/0OtDqSxv4OY2KKipFWnz4qhqgO/SjatZzCDV+T/EtJnK4VkjhdhsfjweFw0LBhQ8LDw9UOR1TCbDYDkJOTQ2Jioly2EyKEWHuOwr59KaVHduDKOYYxsSn2ncspXPc5APHDHyS8eWeVo6wZ6w23ULRrOY6DW3DlncIY11DtkEQdkOGTy/B6/XdMGI1GlSMRl1Ke1LrdbpUjEUKczxCTHJgDVLhpAY7MXeQueg+A6F63YukyUM3wrogxvjHhrbsBCrZNC9QOR9QRSZyqSObOhDb5+xEidFnPlmEp3rOW7C9eA5+XiNTexPS/U93AgsBf2BiKv1+Fp7hQ3WBEnZDESdS5SZMmMWbMGLXDEELUkbCGrQhLSQWfB8XpIKxJOxJGTUWjqf8/gsKapGJq2BrF68a+dZHa4Yg6oOq/2pkzZ9K9e3eioqJITExkzJgxHDhw4IL9NmzYwIABA4iIiMBisdC3b19KS88t45+fn8/dd9+NxWIhOjqa+++/n+Li4ro8lavOs88+S5cuXdQOQwhxlYjudSsAhtgGJN32BFr91TH9QaPRYA2UmFmMz1WmckSitqmaOK1evZopU6awceNGMjIycLvdDBkyhJKSksA+GzZsYNiwYQwZMoTNmzezZcsWpk6dWuHutrvvvpu9e/eSkZHBwoULWbNmDQ888IAapySEEKIS4S270ui+V2h078vowqPUDieoItr0QB+TjK+06iVmRD2mhJCcnBwFUFavXh3Y1rNnT+Wpp5666DH79u1TAGXLli2BbYsWLVI0Go1y8uTJKvVrs9kUQLHZbBe8V1paquzbt08pLS2txpmEhkWLFim9e/dWrFarEhsbq4wcOVL58ccfA++fOHFCGTdunBITE6OEh4craWlpysaNG5XZs2crQIXH7NmzlczMTAVQduzYEWijoKBAAZSVK1cqiqIoHo9Hue+++5RmzZopYWFhynXXXae8+eabFeKaOHGiMnr06KCea33+exJC1H+FWxYph/98q3LsnV8rPq9H7XBENV0qD/i5kLrAbLPZAIiNjQX8t5dv2rSJxMREevXqRVJSEv369WPt2rWBYzZs2EB0dDTdunULbBs0aBBarZZNmzYFPUZFUfC5ylR5KIpSrVhLSkp4/PHH2bp1K8uXL0er1fKLX/wCn89HcXEx/fr14+TJkyxYsIBdu3bx+9//Hp/Pxx133MH//d//0b59e06fPs3p06e54447qtSnz+ejcePG/Pe//2Xfvn08/fTT/OEPf+Czzz6ryccthBD1QlTnm/wlZgpzKPlho9rhiFoUMus4+Xw+Hn30UXr37k2HDh0AOHLkCOCfb/Paa6/RpUsX/vWvfzFw4ED27NlD69atycrKIjExsUJber2e2NhYsrKyKu3L6XTidDoDr+12e5XjVNxOjr56d3VPLyiaTfsETTXKEYwdO7bC6w8//JCEhAT27dvH+vXrOXPmDFu2bAkkqq1atQrsGxkZiV6vJzk5uVoxGgwGnnvuucDr5s2bs2HDBj777DNuv/32arUlhBD1hdZg8q+U/t1n2DZ+TUS7XnK371UqZEacpkyZwp49e5g3b15gW3mJkwcffJB7772Xrl278sYbb9CmTRs+/PDDGvc1c+ZMrFZr4NGkSZMrjj8UHTp0iDvvvJMWLVpgsVho1qwZAMePH2fnzp107do1kDQF07vvvktaWhoJCQlERkby/vvvc/z48aD3I4QQocSaNgyN3ojz9GHKju9VOxxRS0JixGnq1KmBSd2NGzcObC8vn5Gamlph/3bt2gV+ECcnJwfKbZTzeDzk5+dfdLRk+vTpPP7444HXdru9ysmTxmCi2bRPqrRvsGkMpmrtP2rUKJo2bcoHH3xAw4YN8fl8dOjQAZfLFVhtuzrKJ+Sff8nw5wtOzps3j9/97ne8/vrrpKenExUVxauvvlorl02FECKU6CKsRHbqT9H2pf4SM007qB2SqAWqJk6KovDwww8zf/58Vq1aRfPmzSu836xZMxo2bHjBEgUHDx5k+PDhAKSnp1NYWMi2bdtIS0sDYMWKFfh8Pnr2rLxitclkwmSqXhJSTqPRVOtymVry8vI4cOAAH3zwATfeeCNAhblhnTp14h//+Af5+fmVjjoZjcbAqunlEhISADh9+jRdu3YFYOfOnRX2WbduHb169eI3v/lNYNvhw4eDck5CCBHqonuOomh7BqWHt+M6cxxjQv2qwScuT9VLdVOmTOHjjz9m7ty5REVFkZWVRVZWVmCNJo1Gw7Rp0/jrX//K559/zo8//siMGTP44YcfuP/++wH/6NOwYcOYPHkymzdvZt26dUydOpVx48bRsOG1WzcoJiaGuLg43n//fX788UdWrFhRYZTtzjvvJDk5mTFjxrBu3TqOHDnCF198wYYNGwB/0pqZmcnOnTvJzc3F6XRiNpu54YYbeOmll9i/fz+rV6/mqaeeqtBv69at2bp1K0uWLOHgwYPMmDGDLVu21Om5CyGEWgyxDQlv0wOAwo3fqByNqBW1fIffJfGzW94579b3882cOVNp3LixEh4erqSnpyvfffddhffz8vKUO++8U4mMjFQsFoty7733KkVFRVWO42pdjiAjI0Np166dYjKZlE6dOimrVq1SAGX+/PmKoijK0aNHlbFjxyoWi0UJDw9XunXrpmzatElRFEUpKytTxo4dq0RHR1f4O9m3b5+Snp6umM1mpUuXLsrSpUsrLEdQVlamTJo0SbFarUp0dLTy0EMPKU8++aTSuXPnQFyyHIEQ4mpW+tMB5fCfb1UOv3i74rbnqR2OqILqLEegUZRq3uN+FbLb7VitVmw2GxaLpcJ7ZWVlZGZm0rx5c8LCQv8S3bVK/p6EEKHk1L+eouzEfqzpY4gbMF7tcMRlXCoP+LmQuatOCCGEuFqUl2Ep2r4Un7P0MnuL+kQSJyGEECLIwlunYYhrhM/pwL4zQ+1wRBBJ4iSEEEIEmUajxdrzFgBsm/+H4vWoHJEIFkmchBBCiFoQ2bEvuohovPZcivetUzscESSSOAkhhBC1QKs3YunmX3PQtvHratcbFef4XKXkr5qLMytT7VAkcRJCCCFqiyVtKBpDGK6cY5Rmfq92OPWOoigU7V7NiVm/pXDdF+RlfKh6AiqJkxBCCFFLdOYooroMAPyjTqLqyk79yKmP/siZBX/FW5yPPjoJa4+b1Q4rNGrVCSGEEFcra49R2LcupjRzF86sTEzJzS9/0DXMU1RA/qpPKP5+JQAaQxgxfcZi6XEzWr1R5egkcRJCCCFqlSE6kYh26ZTsW4dt0wISRz+idkghSfG4sW1eSMG6z1FcZQBEdupPbP+70UddWFNVLXKp7iqlKAoPPPAAsbGxaDSaC4rxCiGEqDvRN4wBoHjvWjy2M+oGE2IURaHkwGZOvP8o+Ss/RnGVYWrYmoaTXiJx1MMhlTSBJE5XrcWLFzNnzhwWLlzI6dOn6dChg9oh1UizZs1488031Q5DCCGuiKlBC8KadQTFh23zQrXDCRmuM8fJ+s+fyP78ZTwFWegiY0i45WEaTnqRsEat1Q6vUnKp7ip1+PBhGjRoQK9evWp0vKIoeL1e9Hr5JyKEEMEQ3fMWso7uxr5zGdE33o4uLELtkFTjLS2iYM2n2LctAcWHRmfA2nMU0b1vRWs0qx3eJcmI01Vo0qRJPPzwwxw/fhyNRkOzZs1wOp389re/JTExkbCwMPr06cOWLVsCx6xatQqNRsOiRYtIS0vDZDKxdu1afD4fM2fOpHnz5pjNZjp37sznn39eob+9e/dy8803Y7FYiIqK4sYbb+Tw4cMAbNmyhcGDBxMfH4/VaqVfv35s3749cKyiKDz77LOkpKRgMplo2LAhv/3tbwHo378/x44d47HHHkOj0aDRaOrg0xNCiNphbtkVQ0IKiquMou1L1Q5HFYrPi23rYk7Mmop96yJQfIS36UnjB98k9qa7Qz5pAhlxqjZFUXB6Xar0bdIZq5Q8vPXWW7Rs2ZL333+fLVu2oNPp+P3vf88XX3zBRx99RNOmTXnllVcYOnQoP/74I7Gx564fP/nkk7z22mu0aNGCmJgYZs6cyccff8zf//53WrduzZo1a7jnnntISEigX79+nDx5kr59+9K/f39WrFiBxWJh3bp1eDz+8gJFRUVMnDiRt99+G0VReP311xkxYgSHDh0iKiqKL774gjfeeIN58+bRvn17srKy2LVrFwBffvklnTt35oEHHmDy5Mm186EKIUQd0Wg0RN9wC2e+eQfblv9h7XEzGr1B7bDqTOnR3eQu/RD3meMAGBJSiB9yH+ZmHVWOrHokcaomp9fFhC8eVaXvf419kzC96bL7Wa1WoqKi0Ol0JCcnU1JSwqxZs5gzZw7Dh/tXsf3ggw/IyMjgn//8J9OmTQsc+6c//YnBgwcD4HQ6efHFF1m2bBnp6ekAtGjRgrVr1/Lee+/Rr18/3n33XaxWK/PmzcNg8H8BXHfddYH2BgwYUCG2999/n+joaFavXs3NN9/M8ePHSU5OZtCgQRgMBlJSUujRowcAsbGx6HQ6oqKiSE5OvoJPTgghQkNk+z7kr5qLtyif4r3fEdV5wOUPqufcBVnkLf8XjgObANCaI4npeyeW6wej0epUjq765FLdNeDw4cO43W569+4d2GYwGOjRowf79++vsG+3bt0Cz3/88UccDgeDBw8mMjIy8PjXv/4VuBS3c+dObrzxxkDS9HPZ2dlMnjyZ1q1bY7VasVgsFBcXc/y4/zeOX/7yl5SWltKiRQsmT57M/PnzA6NVQghxtdHoDFi7jwSgcOPXKIpP5Yhqj89VSv7KTzjx3iP+pEmjxdJtBE0eegdrt2H1MmkCGXGqNpPOyL/Gvqla37UtIuLcZMXi4mIA/ve//9GoUaOKsZj8I19m86WvR0+cOJG8vDzeeustmjZtislkIj09HZfLf7mzSZMmHDhwgGXLlpGRkcFvfvMbXn31VVavXn3RZEwIIeozS9fBFKz9HHfuT5T+uIPw1mlqhxRUiuKjePca8ld+jLe4AABz807EDb4XY0KKytFdOUmcqkmj0VTpclkoadmyJUajkXXr1tG0aVMA3G43W7Zs4dFHH73ocampqZhMJo4fP06/fv0q3adTp0589NFHuN3uShOddevW8be//Y0RI0YAcOLECXJzcyvsYzabGTVqFKNGjWLKlCm0bduW3bt3c/3112M0GvF6vTU8cyGECD3asAgs1w/GtnEBhRu/vqoSp7KTB8lb+iHOU4cA0MckEzdoEuGtu101N/hI4nQNiIiI4KGHHmLatGnExsaSkpLCK6+8gsPh4P7777/ocVFRUfzud7/jsccew+fz0adPH2w2G+vWrcNisTBx4kSmTp3K22+/zbhx45g+fTpWq5WNGzfSo0cP2rRpQ+vWrfn3v/9Nt27dsNvtTJs2rcIo1Zw5c/B6vfTs2ZPw8HA+/vhjzGZzIMFr1qwZa9asYdy4cZhMJuLj42v98xJCiNpm7X4zts3/o+z4XspO/UhYw1Zqh3RFPEX55K/8hOLdqwDQGMOI6fNLrN1HXnUT4FWd4zRz5ky6d+9OVFQUiYmJjBkzhgMHDlS6r6IoDB8+HI1Gw1dffVXhvePHjzNy5EjCw8NJTExk2rRpMk/mZ1566SXGjh3L+PHjuf766/nxxx9ZsmQJMTExlzzu+eefZ8aMGcycOZN27doxbNgw/ve//9G8ub/WUlxcHCtWrKC4uJh+/fqRlpbGBx98EBh9+uc//0lBQQHXX38948ePDyyJUC46OpoPPviA3r1706lTJ5YtW8Y333xDXFwc4J+sfvToUVq2bElCQkItfTpCCFG39JY4Itv3AcC28St1g7kCPo+LgnVfcmLWw4GkKbLTAJr8+h2i08dcdUkTgEZRFEWtzocNG8a4cePo3r07Ho+HP/zhD+zZs4d9+/ZVmGsD8MYbb5CRkcGiRYuYP38+Y8aMAcDr9dKlSxeSk5N59dVXOX36NBMmTGDy5Mm8+OKLVYrDbrdjtVqx2WxYLJYK75WVlZGZmUnz5s0JCwsLynmL4JO/JyFEfePMPsrJf/wfaLQ0eehtDDH15+5hRVFwHNhM3vI5eApzADA1uo64IffXy9GzS+UBP6fqpbrFixdXeD1nzhwSExPZtm0bffv2DWzfuXMnr7/+Olu3bqVBgwYVjlm6dCn79u1j2bJlJCUl0aVLF55//nmeeOIJnn32WYxG9SspCyGEED9nSmqGuUUXSo/sxLZ5IfFDf6V2SFXiyjlGbsZsyo7uBkAXGUvswPFEtr/xqpnHdCkhtRyBzWYDqLAgo8Ph4K677uLdd9+tdC2fDRs20LFjR5KSkgLbhg4dit1uZ+/evZX243Q6sdvtFR5CCCFEXYu+YTQARbtW4HUUqRzNpXkdReQu/oCf/vE7yo7uRqMzEN37Npo89FeiOvS9JpImCKHJ4T6fj0cffZTevXtXKEj72GOP0atXL0aPHl3pcVlZWRWSJiDwOisrq9JjZs6cyXPPPRekyIUQQoiaCWvWEWNSc1zZmdi3LSbmxl+qHdIFFJ8X+7YlFKz5FF+Zf5maiLY3EDtwAobopMscffUJmcRpypQp7Nmzh7Vr1wa2LViwgBUrVrBjx46g9jV9+nQef/zxwGu73U6TJk2C2ocQQghxORqNhuj00eR89Sa2rd9iveEWtIbQWfLGkbmLvIzZuM+cAMCY2JS4wffWuzIpwRQSidPUqVNZuHAha9asoXHjxoHtK1as4PDhw0RHR1fYf+zYsdx4442sWrWK5ORkNm/eXOH97OxsgIuW6TCZTIEFHIUQQgg1RbTrhX7lJ3hsZ8j+/FX0UbGXP6gOeOy5lGb6a4dqzVHE9ruTqK6D6u2K38GiauKkKAoPP/ww8+fPZ9WqVYFb3Ms9+eST/OpXFSfLdezYkTfeeINRo0YBkJ6ezgsvvEBOTk7gNveMjAwsFgupqalBjVWELvn7EULUVxqtDmvPUeQt/ZDSI8G9wnLFNFos3YYTc+Pt6MyRakcTElRNnKZMmcLcuXP5+uuviYqKCsxJslqtmM1mkpOTKx01SklJCSRZQ4YMITU1lfHjx/PKK6+QlZXFU089xZQpU4IyqqTT+TNrl8t12fIiQj0OhwNAyrQIIeolS9owNDoD3tJitUMJ0Gi1hLfuhjG+8eV3voaomjjNmjULgP79+1fYPnv2bCZNmlSlNnQ6HQsXLuShhx4iPT2diIgIJk6cyJ/+9KegxKjX6wkPD+fMmTMYDAa02pC6EfGapygKDoeDnJwcoqOjA4muEELUJxqtDsv1Q9QOQ1SBqgtghorLLXzlcrnIzMzE57t6q1jXd9HR0SQnJ18zt8MKIYQInnqzAGZ9YTQaad26NS6XS+1QRCUMBoOMNAkhhKgTkjhVkVarlVIeQgghxDVOJuwIIYQQQlSRJE5CCCGEEFUkiZMQQgghRBXJHCfOLZ4oxX6FEEKIa0/5z/+qLDQgiRNQVOSvSC316oQQQohrV1FREVar9ZL7yDpOgM/n49SpU0RFRQV9HaDyAsInTpy47NoQ1yL5fC5NPp9Lk8/n0uTzuTT5fC7tWvp8FEWhqKiIhg0bXnahaxlxwr/UwPnFhWuDxWK56v/hXQn5fC5NPp9Lk8/n0uTzuTT5fC7tWvl8LjfSVE4mhwshhBBCVJEkTkIIIYQQVSSJUy0zmUw888wzmEwmtUMJSfL5XJp8Ppcmn8+lyedzafL5XJp8PpWTyeFCCCGEEFUkI05CCCGEEFUkiZMQQgghRBVJ4iSEEEIIUUWSONWyd999l2bNmhEWFkbPnj3ZvHmz2iGFhJkzZ9K9e3eioqJITExkzJgxHDhwQO2wQtJLL72ERqPh0UcfVTuUkHHy5Enuuece4uLiMJvNdOzYka1bt6odVkjwer3MmDGD5s2bYzabadmyJc8//3yVSklcjdasWcOoUaNo2LAhGo2Gr776qsL7iqLw9NNP06BBA8xmM4MGDeLQoUPqBKuCS30+brebJ554go4dOxIREUHDhg2ZMGECp06dUi/gECCJUy369NNPefzxx3nmmWfYvn07nTt3ZujQoeTk5KgdmupWr17NlClT2LhxIxkZGbjdboYMGUJJSYnaoYWULVu28N5779GpUye1QwkZBQUF9O7dG4PBwKJFi9i3bx+vv/46MTExaocWEl5++WVmzZrFO++8w/79+3n55Zd55ZVXePvtt9UOTRUlJSV07tyZd999t9L3X3nlFf7617/y97//nU2bNhEREcHQoUMpKyur40jVcanPx+FwsH37dmbMmMH27dv58ssvOXDgALfccosKkYYQRdSaHj16KFOmTAm89nq9SsOGDZWZM2eqGFVoysnJUQBl9erVaocSMoqKipTWrVsrGRkZSr9+/ZRHHnlE7ZBCwhNPPKH06dNH7TBC1siRI5X77ruvwrZbb71Vufvuu1WKKHQAyvz58wOvfT6fkpycrLz66quBbYWFhYrJZFL+85//qBChun7++VRm8+bNCqAcO3asboIKQTLiVEtcLhfbtm1j0KBBgW1arZZBgwaxYcMGFSMLTTabDYDY2FiVIwkdU6ZMYeTIkRX+DQlYsGAB3bp145e//CWJiYl07dqVDz74QO2wQkavXr1Yvnw5Bw8eBGDXrl2sXbuW4cOHqxxZ6MnMzCQrK6vC/zGr1UrPnj3le/oibDYbGo2G6OhotUNRjdSqqyW5ubl4vV6SkpIqbE9KSuKHH35QKarQ5PP5ePTRR+nduzcdOnRQO5yQMG/ePLZv386WLVvUDiXkHDlyhFmzZvH444/zhz/8gS1btvDb3/4Wo9HIxIkT1Q5PdU8++SR2u522bdui0+nwer288MIL3H333WqHFnKysrIAKv2eLn9PnFNWVsYTTzzBnXfeeU3UrrsYSZyE6qZMmcKePXtYu3at2qGEhBMnTvDII4+QkZFBWFiY2uGEHJ/PR7du3XjxxRcB6Nq1K3v27OHvf/+7JE7AZ599xieffMLcuXNp3749O3fu5NFHH6Vhw4by+Ygac7vd3H777SiKwqxZs9QOR1Vyqa6WxMfHo9PpyM7OrrA9Ozub5ORklaIKPVOnTmXhwoWsXLmSxo0bqx1OSNi2bRs5OTlcf/316PV69Ho9q1ev5q9//St6vR6v16t2iKpq0KABqampFba1a9eO48ePqxRRaJk2bRpPPvkk48aNo2PHjowfP57HHnuMmTNnqh1ayCn/Lpbv6UsrT5qOHTtGRkbGNT3aBJI41Rqj0UhaWhrLly8PbPP5fCxfvpz09HQVIwsNiqIwdepU5s+fz4oVK2jevLnaIYWMgQMHsnv3bnbu3Bl4dOvWjbvvvpudO3ei0+nUDlFVvXv3vmDpioMHD9K0aVOVIgotDocDrbbiV7tOp8Pn86kUUehq3rw5ycnJFb6n7XY7mzZtku/ps8qTpkOHDrFs2TLi4uLUDkl1cqmuFj3++ONMnDiRbt260aNHD958801KSkq499571Q5NdVOmTGHu3Ll8/fXXREVFBeYTWK1WzGazytGpKyoq6oK5XhEREcTFxckcMOCxxx6jV69evPjii9x+++1s3ryZ999/n/fff1/t0ELCqFGjeOGFF0hJSaF9+/bs2LGDv/zlL9x3331qh6aK4uJifvzxx8DrzMxMdu7cSWxsLCkpKTz66KP8+c9/pnXr1jRv3pwZM2bQsGFDxowZo17QdehSn0+DBg247bbb2L59OwsXLsTr9Qa+q2NjYzEajWqFrS61b+u72r399ttKSkqKYjQalR49eigbN25UO6SQAFT6mD17ttqhhSRZjqCib775RunQoYNiMpmUtm3bKu+//77aIYUMu92uPPLII0pKSooSFhamtGjRQvnjH/+oOJ1OtUNTxcqVKyv9rpk4caKiKP4lCWbMmKEkJSUpJpNJGThwoHLgwAF1g65Dl/p8MjMzL/pdvXLlSrVDV41GUa7R5WSFEEIIIapJ5jgJIYQQQlSRJE5CCCGEEFUkiZMQQgghRBVJ4iSEEEIIUUWSOAkhhBBCVJEkTkIIIYQQVSSJkxBCCCFEFUniJIQQQghRRZI4CSHqraNHj6LRaNi5c6faoQghrhGSOAkhas2kSZMqrfm1atUqNBoNhYWFV9R+kyZNOH36dMjW8JPEToirjxT5FULUSy6XC6PRSHJystqhCCGuITLiJIQICV988QXt27fHZDLRrFkzXn/99QrvN2vWjOeff54JEyZgsVh44IEHLhjRmTRpEhqN5oLHqlWrACgoKGDChAnExMQQHh7O8OHDOXToUKCPOXPmEB0dzZIlS2jXrh2RkZEMGzaM06dPXzTugoIC7r77bhISEjCbzbRu3ZrZs2cD0Lx5cwC6du2KRqOhf//+geP+8Y9/0K5dO8LCwmjbti1/+9vfAu+Vn9e8efPo1asXYWFhdOjQgdWrV1/JRyyECAJJnIQQqtu2bRu3334748aNY/fu3Tz77LPMmDGDOXPmVNjvtddeo3PnzuzYsYMZM2Zc0M5bb73F6dOnA49HHnmExMRE2rZtC/gTq61bt7JgwQI2bNiAoiiMGDECt9sdaMPhcPDaa6/x73//mzVr1nD8+HF+97vfXTT2GTNmsG/fPhYtWsT+/fuZNWsW8fHxAGzevBmAZcuWcfr0ab788ksAPvnkE55++mleeOEF9u/fz4svvsiMGTP46KOPKrQ9bdo0/u///o8dO3aQnp7OqFGjyMvLq/4HLIQIHkUIIWrJxIkTFZ1Op0RERFR4hIWFKYBSUFCgKIqi3HXXXcrgwYMrHDtt2jQlNTU18Lpp06bKmDFjKuyTmZmpAMqOHTsu6PuLL75QwsLClLVr1yqKoigHDx5UAGXdunWBfXJzcxWz2ax89tlniqIoyuzZsxVA+fHHHwP7vPvuu0pSUtJFz3HUqFHKvffeW+l7F4uvZcuWyty5cytse/7555X09PQKx7300kuB991ut9K4cWPl5ZdfvmgsQojaJyNOQohaddNNN7Fz584Kj3/84x8V9tm/fz+9e/eusK13794cOnQIr9cb2NatW7cq9bljxw7Gjx/PO++8E2h3//796PV6evbsGdgvLi6ONm3asH///sC28PBwWrZsGXjdoEEDcnJyLtrXQw89xLx58+jSpQu///3vWb9+/SVjKykp4fDhw9x///1ERkYGHn/+8585fPhwhX3T09MDz/V6Pd26dasQqxCi7snkcCFErYqIiKBVq1YVtv300081butysrKyuOWWW/jVr37F/fffX+0+DAZDhdcajQZFUS66//Dhwzl27BjffvstGRkZDBw4kClTpvDaa69Vun9xcTEAH3zwQYUkDkCn01U7XiFE3ZIRJyGE6tq1a8e6desqbFu3bh3XXXddtZKJsrIyRo8eTdu2bfnLX/5yQR8ej4dNmzYFtuXl5XHgwAFSU1OvKP6EhAQmTpzIxx9/zJtvvsn7778PgNFoBKgwapaUlETDhg05cuQIrVq1qvAon0xebuPGjYHnHo+Hbdu20a5duyuKVQhxZWTESQihuv/7v/+je/fuPP/889xxxx1s2LCBd955p8KdZlXx4IMPcuLECZYvX86ZM2cC22NjY2ndujWjR49m8uTJvPfee0RFRfHkk0/SqFEjRo8eXePYn376adLS0mjfvj1Op5OFCxcGkpvExETMZjOLFy+mcePGhIWFYbVaee655/jtb3+L1Wpl2LBhOJ1Otm7dSkFBAY8//nig7XfffZfWrVvTrl073njjDQoKCrjvvvtqHKsQ4srJiJMQQnXXX389n332GfPmzaNDhw48/fTT/OlPf2LSpEnVamf16tWcPn2a1NRUGjRoEHiUzzuaPXs2aWlp3HzzzaSnp6MoCt9+++0Fl+eqw2g0Mn36dDp16kTfvn3R6XTMmzcP8M9L+utf/8p7771Hw4YNAwnar371K/7xj38we/ZsOnbsSL9+/ZgzZ84FI04vvfQSL730Ep07d2bt2rUsWLAgcMeeEEIdGuVSF++FEELUuaNHj9K8eXN27NhBly5d1A5HCHEeGXESQgghhKgiSZyEEEIIIapILtUJIYQQQlSRjDgJIYQQQlSRJE5CCCGEEFUkiZMQQgghRBVJ4iSEEEIIUUWSOAkhhBBCVJEkTkIIIYQQVSSJkxBCCCFEFUniJIQQQghRRZI4CSGEEEJU0f8DQzdL9CRVDF0AAAAASUVORK5CYII=", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "daily_total = counts.sum(axis=0)\n", "\n", "plt.figure(figsize=(8, 3))\n", "plt.plot(daily_total, color=\"#3b4cc0\")\n", "plt.title(\"Daily event totals\")\n", "plt.xlabel(\"Day index\")\n", "plt.ylabel(\"Count\")\n", "plt.tight_layout()\n", "plt.show()\n", "\n", "forecast_total = lam.sum(axis=0)\n", "actual_total = y_test.sum(axis=0)\n", "\n", "plt.figure(figsize=(6, 3))\n", "plt.plot(actual_total, label=\"actual\", color=\"#dd8452\")\n", "plt.plot(forecast_total, label=\"forecast\", color=\"#55a868\")\n", "plt.title(\"Held-out totals\")\n", "plt.xlabel(\"Horizon step\")\n", "plt.ylabel(\"Count\")\n", "plt.legend()\n", "plt.tight_layout()\n", "plt.show()" ] } ], "metadata": { "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.11.14" } }, "nbformat": 4, "nbformat_minor": 5 }