From a004868d28ea25c73adfbe8c1d7039bf20217944 Mon Sep 17 00:00:00 2001 From: Martin Royer Date: Tue, 20 Jan 2026 10:24:13 +0100 Subject: [PATCH 1/9] fix:sliding window alg when identical windows - replace hashing with indexing - simplify functions --- tdaad/topological_embedding.py | 81 +++++++++++++++++++++++- tdaad/utils/window_functions.py | 108 -------------------------------- 2 files changed, 80 insertions(+), 109 deletions(-) delete mode 100644 tdaad/utils/window_functions.py diff --git a/tdaad/topological_embedding.py b/tdaad/topological_embedding.py index 01f90f2..d67f58f 100644 --- a/tdaad/topological_embedding.py +++ b/tdaad/topological_embedding.py @@ -3,6 +3,11 @@ # Author: Martin Royer from functools import partial +import multiprocessing + +from joblib import Parallel, delayed + +import pandas as pd from sklearn.base import BaseEstimator, TransformerMixin from sklearn.pipeline import Pipeline @@ -14,7 +19,6 @@ from gudhi.representations.vector_methods import Atol from tdaad.utils.tda_functions import transform_to_persistence_diagram -from tdaad.utils.window_functions import sliding_window_ppl_pp atol_vanilla_fit = Atol.fit @@ -30,6 +34,71 @@ def local_atol_fit(self, X, y=None, sample_weight=None): Atol.fit = local_atol_fit +def effective_n_jobs(default=-1): + """Return a safe n_jobs based on whether we're already inside a worker process.""" + try: + # If we're in the main process, multiprocessing.current_process().name == 'MainProcess' + if multiprocessing.current_process().name != "MainProcess": + return 1 # inside pool → avoid nested parallelism + except Exception: + pass + return default + + +def sliding_window_ppl_pp( + data, + func, + window_size=120, + step=5, + n_jobs=-1, +): + """ + Apply a processing function to sliding windows over time series data in parallel. + + Each window is identified by its starting index in the original DataFrame, + providing uniqueness and full traceability. + + Parameters + ---------- + data : pd.DataFrame + Input 2D time series data with shape (num_rows, num_features). + func : callable + Function applied to each window. Receives a NumPy array of shape + (window_size, num_features). + window_size : int, optional + Number of consecutive rows per window. + step : int, optional + Stride between successive windows. + n_jobs : int, optional + Number of parallel jobs (joblib). + + Returns + ------- + pd.DataFrame + One row per window. Index = window start index in `data`. + """ + + values = data.to_numpy() + n_rows = len(data) + + # Compute window start positions + start_indices = range(0, n_rows - window_size + 1, step) + + def process_window(start_idx): + window = values[start_idx : start_idx + window_size] + return start_idx, func(window) + + results = Parallel(n_jobs=n_jobs)(delayed(process_window)(i) for i in start_indices) + + # Convert results to DataFrame + result_dict = dict(results) + result_df = pd.DataFrame.from_dict(result_dict, orient="index") + + result_df.index.name = "window_start" + + return result_df + + class TopologicalEmbedding(BaseEstimator, TransformerMixin): """Topological embedding for multiple time series. @@ -68,11 +137,20 @@ def __init__( step: int = 5, tda_max_dim: int = 2, n_centers_by_dim: int = 5, + parallel="auto", ): self.window_size = window_size self.step = step self.tda_max_dim = tda_max_dim self.n_centers_by_dim = n_centers_by_dim + self.parallel = parallel + if parallel == "auto": + n_jobs = effective_n_jobs(default=-1) + elif parallel is True: + n_jobs = -1 + else: + n_jobs = 1 + self.n_jobs = n_jobs def _build_pipeline(self): steps = [] @@ -87,6 +165,7 @@ def _build_pipeline(self): "window_size": self.window_size, "step": self.step, "func": func, + "n_jobs": self.n_jobs, }, ), ) diff --git a/tdaad/utils/window_functions.py b/tdaad/utils/window_functions.py deleted file mode 100644 index a97dbb0..0000000 --- a/tdaad/utils/window_functions.py +++ /dev/null @@ -1,108 +0,0 @@ -"""Window Functions.""" - -# Author: Martin Royer - -import hashlib -import numpy as np -import pandas as pd - -from joblib import Parallel, delayed - - -def hash_window(window: np.ndarray) -> str: - """Hash encoding of sliding window index.""" - return hashlib.sha1(np.ascontiguousarray(window).view(np.uint8)).hexdigest() - - -def sliding_window_3D_view(data, window_size, step): - """ - Create a 3D sliding window view over a 2D array without copying data. - - This function returns overlapping sliding windows from a 2D input array - using NumPy's `as_strided` for memory-efficient view creation. The resulting - 3D array has shape `(num_windows, window_size, num_features)`, where each - window contains `window_size` rows from the original data, spaced by `step`. - - Parameters - ---------- - data : np.ndarray - Input 2D array of shape (num_rows, num_features). - window_size : int - Number of consecutive rows to include in each window. - step : int - Step size (stride) between successive windows. - - Returns - ------- - np.ndarray - 3D array of shape (num_windows, window_size, num_features), where each - entry is a view into the original `data`. - - Notes - ----- - - This function uses `np.lib.stride_tricks.as_strided`, which does not copy - the data. Be cautious when modifying the output array. - - The number of windows returned is calculated as: - floor((num_rows - window_size) / step) + 1 - """ - num_rows, num_features = data.shape - - shape = (num_rows - window_size + 1, window_size, num_features) - strides = (data.strides[0], data.strides[0], data.strides[1]) - - windows = np.lib.stride_tricks.as_strided(data, shape=shape, strides=strides) - return windows[::step] - - -def sliding_window_ppl_pp(data, func, window_size=120, step=5, n_jobs=-1): - """ - Apply a processing function to sliding windows over time series data in parallel. - - This function slices a 2D time series (Pandas DataFrame) into overlapping windows, - applies a user-defined function (`func`) to each window in parallel, and returns - the aggregated results as a DataFrame indexed by a hash of each window. - - Parameters - ---------- - data : pd.DataFrame - Input 2D time series data with shape (num_rows, num_features). Must be indexable - and convertible to a NumPy array. - func : callable - Function to apply to each window. It should accept a NumPy array of shape - (window_size, num_features) and return a result (e.g., scalar, dict, or Series). - step : int, optional (default=5) - Step size (stride) between successive windows. - window_size : int, optional (default=120) - Number of consecutive rows to include in each sliding window. - n_jobs : int, optional (default=-1) - Number of parallel jobs to run. Passed to `joblib.Parallel`. - Use -1 to utilize all available CPUs. - - Returns - ------- - pd.DataFrame - DataFrame where each row corresponds to a window. The index is a unique hash of the - window content (via `hash_window`), and each row contains the result of `func(w)`. - - Notes - ----- - - Requires the helper function `_sliding_window_3D_view()` to create window views. - - Requires a `hash_window()` function that generates a unique, hashable ID for a window. - - Function assumes that `func(w)` returns something convertible to a dictionary-like format - (e.g., dict, Series) for use with `pd.DataFrame.from_dict`. - - Example - ------- - >>> def mean_window(w): - ... return {'mean': w.mean()} - >>> result = sliding_window_ppl_pp(X, func=mean_window, window_size=10, step=2) - >>> print(result.head()) - """ - windows = sliding_window_3D_view(data.to_numpy(), window_size, step) - - results = Parallel(n_jobs=n_jobs)( - delayed(lambda wdw: (hash_window(wdw), func(wdw)))(w) for w in windows - ) - - post_result = pd.DataFrame.from_dict(dict(results), orient="index") - return post_result From ae5df2bb7831db8ddc783a11c2900cc48d6379a6 Mon Sep 17 00:00:00 2001 From: Martin Royer Date: Tue, 20 Jan 2026 10:54:01 +0100 Subject: [PATCH 2/9] fix decision function --- tdaad/anomaly_detectors.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/tdaad/anomaly_detectors.py b/tdaad/anomaly_detectors.py index c105655..a437cf3 100644 --- a/tdaad/anomaly_detectors.py +++ b/tdaad/anomaly_detectors.py @@ -160,7 +160,7 @@ def score_samples(self, X, y=None): def decision_function(self, X): """Return the distance to the decision boundary.""" - return self.offset_ - self.score_samples(X) + return self.score_samples(X) - self.offset_ def predict(self, X): """Predict inliers (1) and outliers (-1) using learned threshold.""" From 20394f5a4d573ca28f50007dee129ed9ccbd1bbd Mon Sep 17 00:00:00 2001 From: Martin Royer Date: Tue, 20 Jan 2026 17:27:39 +0100 Subject: [PATCH 3/9] outdated monkey patching --- examples/oua_tutorial.ipynb | 178 +++++++++++-------------- tdaad/anomaly_detectors.py | 7 +- tdaad/utils/local_elliptic_envelope.py | 44 ------ 3 files changed, 80 insertions(+), 149 deletions(-) delete mode 100644 tdaad/utils/local_elliptic_envelope.py diff --git a/examples/oua_tutorial.ipynb b/examples/oua_tutorial.ipynb index ae67f59..59dd12d 100644 --- a/examples/oua_tutorial.ipynb +++ b/examples/oua_tutorial.ipynb @@ -24,15 +24,17 @@ "metadata": {}, "outputs": [], "source": [ + "import numpy as np\n", + "\n", "def ornstein_uhlenbeck_anomaly(\n", - " t,\n", - " size=1,\n", - " noise_scale=1,\n", - " mean_reverting=1,\n", - " anomaly_freq=1,\n", - " anomaly_duration=.1,\n", - " anomaly_scale=1,\n", - " seed=314,\n", + " t,\n", + " size=1,\n", + " noise_scale=1,\n", + " mean_reverting=1,\n", + " anomaly_freq=1,\n", + " anomaly_duration=.1,\n", + " anomaly_scale=1,\n", + " seed=314,\n", "):\n", " rng = np.random.RandomState(seed)\n", " length, = t.shape\n", @@ -319,10 +321,19 @@ " Atol2__Atol Center 1\n", " Atol2__Atol Center 2\n", " \n", + " \n", + " window_start\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", " \n", " \n", " \n", - " 5876e224e0e2cc76cf88d99658e19a5d05f17053\n", + " 0\n", " 8.014427\n", " 8.337348\n", " 0.139429\n", @@ -331,7 +342,7 @@ " 0.869459\n", " \n", " \n", - " efa37009e7d2560f20e9baed56c1dd228fb57324\n", + " 5\n", " 7.646981\n", " 8.840381\n", " 0.905686\n", @@ -340,7 +351,7 @@ " 0.000000\n", " \n", " \n", - " 59b90ed4fa88ee1a1db0b4de013b52ebc509cb7c\n", + " 10\n", " 8.490968\n", " 7.406048\n", " 1.041629\n", @@ -349,7 +360,7 @@ " 0.006830\n", " \n", " \n", - " c389c33d12111c0f7710f8d0c02fe459cf6d03d0\n", + " 15\n", " 8.781508\n", " 7.212324\n", " 1.795035\n", @@ -358,7 +369,7 @@ " 0.957346\n", " \n", " \n", - " 78405d0ae4b74c3bb0232b5ca3963e421d920151\n", + " 20\n", " 10.458802\n", " 5.208043\n", " 1.027982\n", @@ -376,7 +387,7 @@ " ...\n", " \n", " \n", - " 02b39cfe47c2e5b6c8efcc391f71294fa3d308e9\n", + " 930\n", " 9.582538\n", " 4.739616\n", " 0.158071\n", @@ -385,7 +396,7 @@ " 0.000000\n", " \n", " \n", - " ed2c3fa613fbe7d8c3f1ac35e1a7cae4257b1f5e\n", + " 935\n", " 9.188312\n", " 5.705798\n", " 0.003870\n", @@ -394,7 +405,7 @@ " 0.000000\n", " \n", " \n", - " a6cf12b25e6e042083b9bb6de3b5a6032e8ba9de\n", + " 940\n", " 9.862403\n", " 6.028840\n", " 0.504404\n", @@ -403,7 +414,7 @@ " 0.723518\n", " \n", " \n", - " 0d55a03c9d97f415f1451826bd98971b0dee2235\n", + " 945\n", " 8.202467\n", " 7.330862\n", " 0.080560\n", @@ -412,7 +423,7 @@ " 0.000000\n", " \n", " \n", - " 3139931912f8b6d1541e63495662bbc421644b45\n", + " 950\n", " 8.475916\n", " 6.191814\n", " 1.013029\n", @@ -426,83 +437,47 @@ "" ], "text/plain": [ - " Atol0__Atol Center 1 \\\n", - "5876e224e0e2cc76cf88d99658e19a5d05f17053 8.014427 \n", - "efa37009e7d2560f20e9baed56c1dd228fb57324 7.646981 \n", - "59b90ed4fa88ee1a1db0b4de013b52ebc509cb7c 8.490968 \n", - "c389c33d12111c0f7710f8d0c02fe459cf6d03d0 8.781508 \n", - "78405d0ae4b74c3bb0232b5ca3963e421d920151 10.458802 \n", - "... ... \n", - "02b39cfe47c2e5b6c8efcc391f71294fa3d308e9 9.582538 \n", - "ed2c3fa613fbe7d8c3f1ac35e1a7cae4257b1f5e 9.188312 \n", - "a6cf12b25e6e042083b9bb6de3b5a6032e8ba9de 9.862403 \n", - "0d55a03c9d97f415f1451826bd98971b0dee2235 8.202467 \n", - "3139931912f8b6d1541e63495662bbc421644b45 8.475916 \n", - "\n", - " Atol0__Atol Center 2 \\\n", - "5876e224e0e2cc76cf88d99658e19a5d05f17053 8.337348 \n", - "efa37009e7d2560f20e9baed56c1dd228fb57324 8.840381 \n", - "59b90ed4fa88ee1a1db0b4de013b52ebc509cb7c 7.406048 \n", - "c389c33d12111c0f7710f8d0c02fe459cf6d03d0 7.212324 \n", - "78405d0ae4b74c3bb0232b5ca3963e421d920151 5.208043 \n", - "... ... \n", - "02b39cfe47c2e5b6c8efcc391f71294fa3d308e9 4.739616 \n", - "ed2c3fa613fbe7d8c3f1ac35e1a7cae4257b1f5e 5.705798 \n", - "a6cf12b25e6e042083b9bb6de3b5a6032e8ba9de 6.028840 \n", - "0d55a03c9d97f415f1451826bd98971b0dee2235 7.330862 \n", - "3139931912f8b6d1541e63495662bbc421644b45 6.191814 \n", - "\n", - " Atol1__Atol Center 1 \\\n", - "5876e224e0e2cc76cf88d99658e19a5d05f17053 0.139429 \n", - "efa37009e7d2560f20e9baed56c1dd228fb57324 0.905686 \n", - "59b90ed4fa88ee1a1db0b4de013b52ebc509cb7c 1.041629 \n", - "c389c33d12111c0f7710f8d0c02fe459cf6d03d0 1.795035 \n", - "78405d0ae4b74c3bb0232b5ca3963e421d920151 1.027982 \n", - "... ... \n", - "02b39cfe47c2e5b6c8efcc391f71294fa3d308e9 0.158071 \n", - "ed2c3fa613fbe7d8c3f1ac35e1a7cae4257b1f5e 0.003870 \n", - "a6cf12b25e6e042083b9bb6de3b5a6032e8ba9de 0.504404 \n", - "0d55a03c9d97f415f1451826bd98971b0dee2235 0.080560 \n", - "3139931912f8b6d1541e63495662bbc421644b45 1.013029 \n", + " Atol0__Atol Center 1 Atol0__Atol Center 2 \\\n", + "window_start \n", + "0 8.014427 8.337348 \n", + "5 7.646981 8.840381 \n", + "10 8.490968 7.406048 \n", + "15 8.781508 7.212324 \n", + "20 10.458802 5.208043 \n", + "... ... ... \n", + "930 9.582538 4.739616 \n", + "935 9.188312 5.705798 \n", + "940 9.862403 6.028840 \n", + "945 8.202467 7.330862 \n", + "950 8.475916 6.191814 \n", "\n", - " Atol1__Atol Center 2 \\\n", - "5876e224e0e2cc76cf88d99658e19a5d05f17053 2.369379 \n", - "efa37009e7d2560f20e9baed56c1dd228fb57324 0.737120 \n", - "59b90ed4fa88ee1a1db0b4de013b52ebc509cb7c 1.851082 \n", - "c389c33d12111c0f7710f8d0c02fe459cf6d03d0 1.523272 \n", - "78405d0ae4b74c3bb0232b5ca3963e421d920151 1.873740 \n", - "... ... \n", - "02b39cfe47c2e5b6c8efcc391f71294fa3d308e9 1.707738 \n", - "ed2c3fa613fbe7d8c3f1ac35e1a7cae4257b1f5e 1.839969 \n", - "a6cf12b25e6e042083b9bb6de3b5a6032e8ba9de 1.867278 \n", - "0d55a03c9d97f415f1451826bd98971b0dee2235 2.732715 \n", - "3139931912f8b6d1541e63495662bbc421644b45 2.501380 \n", + " Atol1__Atol Center 1 Atol1__Atol Center 2 \\\n", + "window_start \n", + "0 0.139429 2.369379 \n", + "5 0.905686 0.737120 \n", + "10 1.041629 1.851082 \n", + "15 1.795035 1.523272 \n", + "20 1.027982 1.873740 \n", + "... ... ... \n", + "930 0.158071 1.707738 \n", + "935 0.003870 1.839969 \n", + "940 0.504404 1.867278 \n", + "945 0.080560 2.732715 \n", + "950 1.013029 2.501380 \n", "\n", - " Atol2__Atol Center 1 \\\n", - "5876e224e0e2cc76cf88d99658e19a5d05f17053 1.041305 \n", - "efa37009e7d2560f20e9baed56c1dd228fb57324 0.000000 \n", - "59b90ed4fa88ee1a1db0b4de013b52ebc509cb7c 0.934886 \n", - "c389c33d12111c0f7710f8d0c02fe459cf6d03d0 0.009076 \n", - "78405d0ae4b74c3bb0232b5ca3963e421d920151 0.000000 \n", - "... ... \n", - "02b39cfe47c2e5b6c8efcc391f71294fa3d308e9 0.000000 \n", - "ed2c3fa613fbe7d8c3f1ac35e1a7cae4257b1f5e 0.000000 \n", - "a6cf12b25e6e042083b9bb6de3b5a6032e8ba9de 0.128751 \n", - "0d55a03c9d97f415f1451826bd98971b0dee2235 0.000000 \n", - "3139931912f8b6d1541e63495662bbc421644b45 0.205330 \n", - "\n", - " Atol2__Atol Center 2 \n", - "5876e224e0e2cc76cf88d99658e19a5d05f17053 0.869459 \n", - "efa37009e7d2560f20e9baed56c1dd228fb57324 0.000000 \n", - "59b90ed4fa88ee1a1db0b4de013b52ebc509cb7c 0.006830 \n", - "c389c33d12111c0f7710f8d0c02fe459cf6d03d0 0.957346 \n", - "78405d0ae4b74c3bb0232b5ca3963e421d920151 0.000000 \n", - "... ... \n", - "02b39cfe47c2e5b6c8efcc391f71294fa3d308e9 0.000000 \n", - "ed2c3fa613fbe7d8c3f1ac35e1a7cae4257b1f5e 0.000000 \n", - "a6cf12b25e6e042083b9bb6de3b5a6032e8ba9de 0.723518 \n", - "0d55a03c9d97f415f1451826bd98971b0dee2235 0.000000 \n", - "3139931912f8b6d1541e63495662bbc421644b45 1.519385 \n", + " Atol2__Atol Center 1 Atol2__Atol Center 2 \n", + "window_start \n", + "0 1.041305 0.869459 \n", + "5 0.000000 0.000000 \n", + "10 0.934886 0.006830 \n", + "15 0.009076 0.957346 \n", + "20 0.000000 0.000000 \n", + "... ... ... \n", + "930 0.000000 0.000000 \n", + "935 0.000000 0.000000 \n", + "940 0.128751 0.723518 \n", + "945 0.000000 0.000000 \n", + "950 0.205330 1.519385 \n", "\n", "[191 rows x 6 columns]" ] @@ -528,7 +503,7 @@ "outputs": [ { "data": { - "image/png": "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", + "image/png": "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", "text/plain": [ "
" ] @@ -569,13 +544,6 @@ "id": "f8b04c86", "metadata": {}, "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "X.shape[0]=1000, self.window_size=50, self.step=5, so running self.padding_length_=0...\n" - ] - }, { "data": { "text/plain": [ @@ -906,6 +874,14 @@ "y[\"TDA anomalies\"] = anomaly_score\n", "y.plot(subplots=True)" ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "765811fb", + "metadata": {}, + "outputs": [], + "source": [] } ], "metadata": { diff --git a/tdaad/anomaly_detectors.py b/tdaad/anomaly_detectors.py index a437cf3..ba54f2c 100644 --- a/tdaad/anomaly_detectors.py +++ b/tdaad/anomaly_detectors.py @@ -10,10 +10,10 @@ from sklearn.base import _fit_context, TransformerMixin from sklearn.utils._param_validation import Interval from sklearn.utils.validation import check_is_fitted +from sklearn.covariance import EllipticEnvelope from tdaad.utils.remapping_functions import score_flat_fast_remapping from tdaad.topological_embedding import TopologicalEmbedding -from tdaad.utils.local_elliptic_envelope import EllipticEnvelope class TopologicalAnomalyDetector(EllipticEnvelope, TransformerMixin): @@ -21,7 +21,7 @@ class TopologicalAnomalyDetector(EllipticEnvelope, TransformerMixin): Anomaly detection for multivariate time series using topological embeddings and robust covariance estimation. This detector extracts topological features from sliding windows of time series data and - uses a robust Mahalanobis distance (via EllipticEnvelope) to score anomalies. + uses a robust Mahalanobis distance (via PandasEllipticEnvelope) to score anomalies. Read more in the :ref:`User Guide `. @@ -164,8 +164,7 @@ def decision_function(self, X): def predict(self, X): """Predict inliers (1) and outliers (-1) using learned threshold.""" - scores = self.score_samples(X) - return np.where(scores < self.offset_, -1, 1) + return np.where(self.decision_function(X) < 0, -1, 1) def transform(self, X): """Alias for score_samples. Returns anomaly scores.""" diff --git a/tdaad/utils/local_elliptic_envelope.py b/tdaad/utils/local_elliptic_envelope.py deleted file mode 100644 index 463d328..0000000 --- a/tdaad/utils/local_elliptic_envelope.py +++ /dev/null @@ -1,44 +0,0 @@ -"""Pandas Elliptic Envelope.""" - -# Author: Martin Royer - -import pandas as pd - -from sklearn.utils.validation import check_is_fitted -from sklearn.covariance import EllipticEnvelope - - -def pandas_mahalanobis(self, X): - """Compute the negative Mahalanobis distances of embedding matrix X. - - Parameters - ---------- - X : array-like of shape (n_samples, n_features) - The embedding matrix. - - Returns - ------- - negative_mahal_distances : pandas.DataFrame of shape (n_samples,) - Opposite of the Mahalanobis distances. - """ - return pd.DataFrame(index=X.index, data=self.mahalanobis(X)) - - -def pandas_score_samples(self, X): - """Compute the negative Mahalanobis distances. - - Parameters - ---------- - X : array-like of shape (n_samples, n_features) - The data matrix. - - Returns - ------- - negative_mahal_distances : array-like of shape (n_samples,) - Opposite of the Mahalanobis distances. - """ - check_is_fitted(self) - return -pandas_mahalanobis(self, X) - - -EllipticEnvelope.score_samples = pandas_score_samples From 0896c127dde5b43b2effc7556f6186059c99b4ef Mon Sep 17 00:00:00 2001 From: Martin Royer Date: Tue, 20 Jan 2026 17:40:30 +0100 Subject: [PATCH 4/9] transform Atol monkey patch into subclass + narrow override --- tdaad/topological_embedding.py | 22 ++++++++++++---------- 1 file changed, 12 insertions(+), 10 deletions(-) diff --git a/tdaad/topological_embedding.py b/tdaad/topological_embedding.py index d67f58f..b7c77ce 100644 --- a/tdaad/topological_embedding.py +++ b/tdaad/topological_embedding.py @@ -21,17 +21,19 @@ from tdaad.utils.tda_functions import transform_to_persistence_diagram -atol_vanilla_fit = Atol.fit - - -def local_atol_fit(self, X, y=None, sample_weight=None): - """local modification to prevent FutureWarning triggered by np.concatenate(X) when X is a pd.Series.""" - if hasattr(X, "values"): - X = X.values - return atol_vanilla_fit(self=self, X=X) +class PandasAtol(Atol): + """ + ATOL vectorization with pandas-compatible input handling. + This subclass converts pandas Series or DataFrame inputs to NumPy arrays + before delegating to the base Atol implementation, avoiding warnings + caused by np.concatenate on pandas objects. + """ -Atol.fit = local_atol_fit + def fit(self, X, y=None, sample_weight=None): + if hasattr(X, "values"): + X = X.values + return super().fit(X, y=y, sample_weight=sample_weight) def effective_n_jobs(default=-1): @@ -177,7 +179,7 @@ def _build_pipeline(self): [ ( f"Atol{i}", - Atol( + PandasAtol( quantiser=KMeans( n_clusters=self.n_centers_by_dim, random_state=202312, From bfd7079083e13fb8d45bc9da3b54eb361ebf0892 Mon Sep 17 00:00:00 2001 From: Martin Royer Date: Tue, 20 Jan 2026 17:56:25 +0100 Subject: [PATCH 5/9] some cleanup --- tdaad/topological_embedding.py | 206 ++++++++++++--------------------- tdaad/utils/tda_functions.py | 26 +---- 2 files changed, 74 insertions(+), 158 deletions(-) diff --git a/tdaad/topological_embedding.py b/tdaad/topological_embedding.py index b7c77ce..bf79cfd 100644 --- a/tdaad/topological_embedding.py +++ b/tdaad/topological_embedding.py @@ -6,7 +6,6 @@ import multiprocessing from joblib import Parallel, delayed - import pandas as pd from sklearn.base import BaseEstimator, TransformerMixin @@ -25,9 +24,8 @@ class PandasAtol(Atol): """ ATOL vectorization with pandas-compatible input handling. - This subclass converts pandas Series or DataFrame inputs to NumPy arrays - before delegating to the base Atol implementation, avoiding warnings - caused by np.concatenate on pandas objects. + Converts pandas inputs to NumPy arrays before calling the base + implementation to avoid warnings caused by np.concatenate on pandas objects. """ def fit(self, X, y=None, sample_weight=None): @@ -36,68 +34,49 @@ def fit(self, X, y=None, sample_weight=None): return super().fit(X, y=y, sample_weight=sample_weight) -def effective_n_jobs(default=-1): - """Return a safe n_jobs based on whether we're already inside a worker process.""" - try: - # If we're in the main process, multiprocessing.current_process().name == 'MainProcess' - if multiprocessing.current_process().name != "MainProcess": - return 1 # inside pool → avoid nested parallelism - except Exception: - pass - return default - - -def sliding_window_ppl_pp( - data, - func, - window_size=120, - step=5, - n_jobs=-1, -): +def resolve_n_jobs(parallel): + """ + Resolve n_jobs safely, avoiding nested parallelism. + """ + if parallel == "auto": + try: + if multiprocessing.current_process().name != "MainProcess": + return 1 + except Exception: + pass + return -1 + + if parallel is True: + return -1 + + return 1 + + +def sliding_window_apply( + data: pd.DataFrame, + window_fn, + window_size: int, + step: int, + n_jobs: int, +) -> pd.DataFrame: """ Apply a processing function to sliding windows over time series data in parallel. - Each window is identified by its starting index in the original DataFrame, - providing uniqueness and full traceability. - - Parameters - ---------- - data : pd.DataFrame - Input 2D time series data with shape (num_rows, num_features). - func : callable - Function applied to each window. Receives a NumPy array of shape - (window_size, num_features). - window_size : int, optional - Number of consecutive rows per window. - step : int, optional - Stride between successive windows. - n_jobs : int, optional - Number of parallel jobs (joblib). - - Returns - ------- - pd.DataFrame - One row per window. Index = window start index in `data`. + Returns a DataFrame indexed by window start index. """ - values = data.to_numpy() n_rows = len(data) - # Compute window start positions start_indices = range(0, n_rows - window_size + 1, step) def process_window(start_idx): window = values[start_idx : start_idx + window_size] - return start_idx, func(window) + return start_idx, window_fn(window) results = Parallel(n_jobs=n_jobs)(delayed(process_window)(i) for i in start_indices) - # Convert results to DataFrame - result_dict = dict(results) - result_df = pd.DataFrame.from_dict(result_dict, orient="index") - + result_df = pd.DataFrame.from_dict(dict(results), orient="index") result_df.index.name = "window_start" - return result_df @@ -117,12 +96,12 @@ class TopologicalEmbedding(BaseEstimator, TransformerMixin): Size of the sliding window algorithm to extract subsequences as input to named_pipeline. step : int, default=5 Size of the sliding window steps between each window. + tda_max_dim : int, default=2 + The maximum dimension of the topological feature extraction. n_centers_by_dim : int, default=5 The number of centroids to generate by dimension for vectorizing topological features. The resulting embedding will have total dimension =< tda_max_dim * n_centers_by_dim. The resulting embedding dimension might be smaller because of the KMeans algorithm in the Archipelago step. - tda_max_dim : int, default=2 - The maximum dimension of the topological feature extraction. Examples ---------- @@ -146,98 +125,55 @@ def __init__( self.tda_max_dim = tda_max_dim self.n_centers_by_dim = n_centers_by_dim self.parallel = parallel - if parallel == "auto": - n_jobs = effective_n_jobs(default=-1) - elif parallel is True: - n_jobs = -1 - else: - n_jobs = 1 - self.n_jobs = n_jobs def _build_pipeline(self): - steps = [] - steps.append(("Standard scaler", StandardScaler())) - func = partial(transform_to_persistence_diagram, tda_max_dim=self.tda_max_dim) - steps.append( - ( - "Sliding persistence diagram transformer", - FunctionTransformer( - func=sliding_window_ppl_pp, - kw_args={ - "window_size": self.window_size, - "step": self.step, - "func": func, - "n_jobs": self.n_jobs, - }, - ), - ) + n_jobs = resolve_n_jobs(self.parallel) + persistence_fn = partial( + transform_to_persistence_diagram, + tda_max_dim=self.tda_max_dim, ) - steps.append( - ( - "Archipelago", - ColumnTransformer( - [ - ( - f"Atol{i}", - PandasAtol( - quantiser=KMeans( - n_clusters=self.n_centers_by_dim, - random_state=202312, - n_init="auto", - ) - ), - i, + + window_transformer = FunctionTransformer( + func=sliding_window_apply, + kw_args=dict( + window_fn=persistence_fn, + window_size=self.window_size, + step=self.step, + n_jobs=n_jobs, + ), + ) + + archipelago = ColumnTransformer( + transformers=[ + ( + f"atol_dim_{i}", + PandasAtol( + quantiser=KMeans( + n_clusters=self.n_centers_by_dim, + random_state=202312, + n_init="auto", ) - for i in range(self.tda_max_dim + 1) - ] - ), - ) + ), + i, + ) + for i in range(self.tda_max_dim + 1) + ] ) - return Pipeline(steps).set_output(transform="pandas") + + pipeline = Pipeline( + steps=[ + ("scale", StandardScaler()), + ("sliding_persistence", window_transformer), + ("archipelago", archipelago), + ] + ) + + return pipeline.set_output(transform="pandas") def fit(self, X, y=None): - """ - Fit the internal pipeline to the data. - - Parameters - ---------- - X : pandas.DataFrame - Input feature matrix. - - y : array-like, optional - Target values (not used here, but accepted for compatibility with sklearn). - - Returns - ------- - self : object - Fitted transformer. - """ self.pipeline_ = self._build_pipeline() self.pipeline_.fit(X, y) return self def transform(self, X): - """ - Apply transformations to the input data using the fitted pipeline. - - Parameters - ---------- - X : pandas.DataFrame - Input data to transform. - - Returns - ------- - X_transformed : array-like or DataFrame - Transformed data. - """ return self.pipeline_.transform(X) - - def fit_transform(self, X, y=None, **fit_params): - """ - Fit to data, then transform it. - - Returns - ------- - X_transformed : array-like - """ - return self.fit(X, y).transform(X) diff --git a/tdaad/utils/tda_functions.py b/tdaad/utils/tda_functions.py index 105bd5c..3705e28 100644 --- a/tdaad/utils/tda_functions.py +++ b/tdaad/utils/tda_functions.py @@ -16,32 +16,12 @@ def _numpy_data_to_similarity(X, filter_nan=True): def transform_to_persistence_diagram(X, tda_max_dim=0): - """Persistence Diagram Transformer for point cloud. - - For a given point cloud, form a similarity matrix and apply a RipsPersistence procedure + """For a given point cloud, form a similarity matrix and apply a RipsPersistence procedure to produce topological descriptors in the form of persistence diagrams. - - Read more in the :ref: `User Guide `. - - Parameters: - tda_max_dim : int, default=0 - The maximum dimension of the topological feature extraction. - - Example - ------- - >>> n_timestamps = 100 - >>> n_sensors = 5 - >>> import numpy as np - >>> np.corrcoef(X) - >>> import pandas as pd - >>> timestamps = pd.to_datetime('2024-01-01', utc=True) + pd.Timedelta(1, 'h') * np.arange(n_timestamps) - >>> X = pd.DataFrame(np.random.random(size=(n_timestamps, n_sensors)), index=timestamps) - >>> PersistenceDiagramTransformer().fit_transform(X.to_numpy()) """ - sim_target = [_numpy_data_to_similarity(X)] + sim_target = _numpy_data_to_similarity(X) rips_transformer = RipsPersistence( homology_dimensions=range(tda_max_dim + 1), input_type="lower distance matrix", ) - rips_target = rips_transformer.transform(sim_target) - return rips_target[0] + return rips_transformer.fit_transform([sim_target])[0] From d6dada113842fb05e78ff64e1528c48ad9035b85 Mon Sep 17 00:00:00 2001 From: Martin Royer Date: Tue, 20 Jan 2026 18:17:28 +0100 Subject: [PATCH 6/9] TopologicalEmbedding massive pipeline cleanup --- tdaad/topological_embedding.py | 163 +++++++++++++-------------------- tdaad/utils/tda_functions.py | 6 +- 2 files changed, 70 insertions(+), 99 deletions(-) diff --git a/tdaad/topological_embedding.py b/tdaad/topological_embedding.py index bf79cfd..836352b 100644 --- a/tdaad/topological_embedding.py +++ b/tdaad/topological_embedding.py @@ -2,22 +2,16 @@ # Author: Martin Royer -from functools import partial -import multiprocessing - -from joblib import Parallel, delayed -import pandas as pd - from sklearn.base import BaseEstimator, TransformerMixin from sklearn.pipeline import Pipeline -from sklearn.preprocessing import StandardScaler -from sklearn.preprocessing import FunctionTransformer +from sklearn.preprocessing import FunctionTransformer, StandardScaler from sklearn.compose import ColumnTransformer from sklearn.cluster import KMeans from gudhi.representations.vector_methods import Atol +from gudhi.sklearn.rips_persistence import RipsPersistence -from tdaad.utils.tda_functions import transform_to_persistence_diagram +from tdaad.utils.tda_functions import numpy_data_to_similarity class PandasAtol(Atol): @@ -34,82 +28,33 @@ def fit(self, X, y=None, sample_weight=None): return super().fit(X, y=y, sample_weight=sample_weight) -def resolve_n_jobs(parallel): - """ - Resolve n_jobs safely, avoiding nested parallelism. +class SlidingWindowTransformer(BaseEstimator, TransformerMixin): """ - if parallel == "auto": - try: - if multiprocessing.current_process().name != "MainProcess": - return 1 - except Exception: - pass - return -1 - - if parallel is True: - return -1 - - return 1 - - -def sliding_window_apply( - data: pd.DataFrame, - window_fn, - window_size: int, - step: int, - n_jobs: int, -) -> pd.DataFrame: - """ - Apply a processing function to sliding windows over time series data in parallel. + Slice a 2D numpy array into overlapping windows. - Returns a DataFrame indexed by window start index. + Output: list of 2D numpy arrays, one per window. """ - values = data.to_numpy() - n_rows = len(data) - - start_indices = range(0, n_rows - window_size + 1, step) - def process_window(start_idx): - window = values[start_idx : start_idx + window_size] - return start_idx, window_fn(window) + def __init__(self, window_size=40, step=5): + self.window_size = window_size + self.step = step - results = Parallel(n_jobs=n_jobs)(delayed(process_window)(i) for i in start_indices) + def fit(self, X, y=None): + return self - result_df = pd.DataFrame.from_dict(dict(results), orient="index") - result_df.index.name = "window_start" - return result_df + def transform(self, X): + n_rows = X.shape[0] + self.window_index_ = list(range(0, n_rows - self.window_size + 1, self.step)) + return [X[i : i + self.window_size] for i in self.window_index_] class TopologicalEmbedding(BaseEstimator, TransformerMixin): - """Topological embedding for multiple time series. - - Slices time series into smaller time series windows, forms an affinity matrix on each window - and applies a Rips procedure to produce persistence diagrams for each affinity - matrix. Then uses Atol [ref:Atol] on each dimension through the - gudhi.representation.Archipelago representation to produce topological vectorization. - - Read more in the :ref:`User Guide `. - - Parameters - ---------- - window_size : int, default=40 - Size of the sliding window algorithm to extract subsequences as input to named_pipeline. - step : int, default=5 - Size of the sliding window steps between each window. - tda_max_dim : int, default=2 - The maximum dimension of the topological feature extraction. - n_centers_by_dim : int, default=5 - The number of centroids to generate by dimension for vectorizing topological features. - The resulting embedding will have total dimension =< tda_max_dim * n_centers_by_dim. - The resulting embedding dimension might be smaller because of the KMeans algorithm in the Archipelago step. - - Examples - ---------- - >>> n_timestamps = 100 - >>> n_sensors = 5 - >>> timestamps = pd.to_datetime('2024-01-01', utc=True) + pd.Timedelta(1, 'h') * np.arange(n_timestamps) - >>> X = pd.DataFrame(np.random.random(size=(n_timestamps, n_sensors)), index=timestamps) - >>> TopologicalEmbedding(n_centers_by_dim=2, tda_max_dim=1).fit_transform(X) + """ + Topological embedding for multivariate time series using sliding windows, + persistent homology (Rips), and ATOL vectorization. + + Pipeline: + Sliding windows -> similarity -> RipsPersistence -> ColumnTransformer(Atol) """ def __init__( @@ -118,39 +63,37 @@ def __init__( step: int = 5, tda_max_dim: int = 2, n_centers_by_dim: int = 5, - parallel="auto", + filter_nan: bool = True, ): self.window_size = window_size self.step = step self.tda_max_dim = tda_max_dim self.n_centers_by_dim = n_centers_by_dim - self.parallel = parallel + self.filter_nan = filter_nan def _build_pipeline(self): - n_jobs = resolve_n_jobs(self.parallel) - persistence_fn = partial( - transform_to_persistence_diagram, - tda_max_dim=self.tda_max_dim, + # FunctionTransformer to convert windows -> distance/similarity matrices + similarity_fn = FunctionTransformer( + func=lambda X_list: [ + numpy_data_to_similarity(x, filter_nan=self.filter_nan) for x in X_list + ] ) - window_transformer = FunctionTransformer( - func=sliding_window_apply, - kw_args=dict( - window_fn=persistence_fn, - window_size=self.window_size, - step=self.step, - n_jobs=n_jobs, - ), + # Batched RipsPersistence + rips_transformer = RipsPersistence( + homology_dimensions=range(self.tda_max_dim + 1), + input_type="lower distance matrix", ) - archipelago = ColumnTransformer( + # ColumnTransformer: one Atol per homology dimension + archipelago_transformer = ColumnTransformer( transformers=[ ( f"atol_dim_{i}", - PandasAtol( + Atol( quantiser=KMeans( n_clusters=self.n_centers_by_dim, - random_state=202312, + random_state=42, n_init="auto", ) ), @@ -160,20 +103,46 @@ def _build_pipeline(self): ] ) + # Full sklearn pipeline pipeline = Pipeline( steps=[ - ("scale", StandardScaler()), - ("sliding_persistence", window_transformer), - ("archipelago", archipelago), + ("scaler", StandardScaler()), + ( + "windows", + SlidingWindowTransformer( + window_size=self.window_size, step=self.step + ), + ), + ("similarity", similarity_fn), + ("rips", rips_transformer), + ("archipelago", archipelago_transformer), ] ) - return pipeline.set_output(transform="pandas") + return pipeline def fit(self, X, y=None): + """ + Fit the full pipeline to the data. + + Parameters + ---------- + X : np.ndarray, shape (n_samples, n_features) + Input multivariate time series. + + y : Ignored + """ self.pipeline_ = self._build_pipeline() self.pipeline_.fit(X, y) return self def transform(self, X): + """ + Apply the fitted pipeline to the input data. + + Returns + ------- + X_transformed : np.ndarray + Topological feature embedding. + """ return self.pipeline_.transform(X) diff --git a/tdaad/utils/tda_functions.py b/tdaad/utils/tda_functions.py index 3705e28..0c7c9b5 100644 --- a/tdaad/utils/tda_functions.py +++ b/tdaad/utils/tda_functions.py @@ -7,7 +7,7 @@ from gudhi.sklearn.rips_persistence import RipsPersistence -def _numpy_data_to_similarity(X, filter_nan=True): +def numpy_data_to_similarity(X, filter_nan=True): r"""Transforms numpy matrix X into similarity matrix :math:`1-\mathbf{Corr}(X)`.""" target = 1 - np.corrcoef(X, rowvar=False) # this filters when a variable is constant -> nan on all rows @@ -18,8 +18,10 @@ def _numpy_data_to_similarity(X, filter_nan=True): def transform_to_persistence_diagram(X, tda_max_dim=0): """For a given point cloud, form a similarity matrix and apply a RipsPersistence procedure to produce topological descriptors in the form of persistence diagrams. + + no longer used in topological embedding """ - sim_target = _numpy_data_to_similarity(X) + sim_target = numpy_data_to_similarity(X) rips_transformer = RipsPersistence( homology_dimensions=range(tda_max_dim + 1), input_type="lower distance matrix", From afeb86da1bd288e9d997ecdeefe949050c328c78 Mon Sep 17 00:00:00 2001 From: Martin Royer Date: Tue, 20 Jan 2026 18:56:45 +0100 Subject: [PATCH 7/9] leanest package --- examples/oua_tutorial.ipynb | 750 ++++++++++++----------------- pyproject.toml | 2 +- tdaad/__init__.py | 4 +- tdaad/anomaly_detectors.py | 54 ++- tdaad/topological_embedding.py | 21 +- tdaad/utils/__init__.py | 0 tdaad/utils/remapping_functions.py | 58 --- tdaad/utils/tda_functions.py | 29 -- tests/test_all.py | 23 +- 9 files changed, 358 insertions(+), 583 deletions(-) delete mode 100644 tdaad/utils/__init__.py delete mode 100644 tdaad/utils/remapping_functions.py delete mode 100644 tdaad/utils/tda_functions.py diff --git a/examples/oua_tutorial.ipynb b/examples/oua_tutorial.ipynb index 59dd12d..10993ed 100644 --- a/examples/oua_tutorial.ipynb +++ b/examples/oua_tutorial.ipynb @@ -135,7 +135,7 @@ }, { "cell_type": "code", - "execution_count": 3, + "execution_count": 13, "id": "57a00032", "metadata": {}, "outputs": [ @@ -145,7 +145,7 @@ "" ] }, - "execution_count": 3, + "execution_count": 13, "metadata": {}, "output_type": "execute_result" }, @@ -161,10 +161,12 @@ } ], "source": [ - "from tdaad.utils.tda_functions import transform_to_persistence_diagram\n", + "from tdaad.topological_embedding import numpy_data_to_similarity, RipsPersistence\n", "from gudhi import plot_persistence_diagram\n", "\n", - "global_pdiagram = transform_to_persistence_diagram(X, tda_max_dim=2)\n", + "sim_matrix = numpy_data_to_similarity(X)\n", + "rips = RipsPersistence(homology_dimensions=range(3), input_type=\"lower distance matrix\")\n", + "global_pdiagram = rips.transform([sim_matrix])[0]\n", "plot_persistence_diagram(global_pdiagram)" ] }, @@ -186,7 +188,7 @@ }, { "cell_type": "code", - "execution_count": 4, + "execution_count": 18, "id": "de943a32", "metadata": {}, "outputs": [ @@ -255,7 +257,8 @@ "swv = np.lib.stride_tricks.sliding_window_view(X.index, X.shape[0]//2)[::200, :]\n", "\n", "for window in swv:\n", - " pdiagram = transform_to_persistence_diagram(X.loc[window], tda_max_dim=2)\n", + " sim_matrix = numpy_data_to_similarity(X.loc[window])\n", + " pdiagram = rips.transform([sim_matrix])[0]\n", " X.loc[window].plot()\n", " ax = plot_persistence_diagram(pdiagram)\n", " ax.set_title(str(window[-1]))" @@ -289,200 +292,29 @@ }, { "cell_type": "code", - "execution_count": 5, + "execution_count": 25, "id": "bf1787bd", "metadata": {}, "outputs": [ { "data": { - "text/html": [ - "
\n", - "\n", - "\n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - "
Atol0__Atol Center 1Atol0__Atol Center 2Atol1__Atol Center 1Atol1__Atol Center 2Atol2__Atol Center 1Atol2__Atol Center 2
window_start
08.0144278.3373480.1394292.3693791.0413050.869459
57.6469818.8403810.9056860.7371200.0000000.000000
108.4909687.4060481.0416291.8510820.9348860.006830
158.7815087.2123241.7950351.5232720.0090760.957346
2010.4588025.2080431.0279821.8737400.0000000.000000
.....................
9309.5825384.7396160.1580711.7077380.0000000.000000
9359.1883125.7057980.0038701.8399690.0000000.000000
9409.8624036.0288400.5044041.8672780.1287510.723518
9458.2024677.3308620.0805602.7327150.0000000.000000
9508.4759166.1918141.0130292.5013800.2053301.519385
\n", - "

191 rows × 6 columns

\n", - "
" - ], "text/plain": [ - " Atol0__Atol Center 1 Atol0__Atol Center 2 \\\n", - "window_start \n", - "0 8.014427 8.337348 \n", - "5 7.646981 8.840381 \n", - "10 8.490968 7.406048 \n", - "15 8.781508 7.212324 \n", - "20 10.458802 5.208043 \n", - "... ... ... \n", - "930 9.582538 4.739616 \n", - "935 9.188312 5.705798 \n", - "940 9.862403 6.028840 \n", - "945 8.202467 7.330862 \n", - "950 8.475916 6.191814 \n", - "\n", - " Atol1__Atol Center 1 Atol1__Atol Center 2 \\\n", - "window_start \n", - "0 0.139429 2.369379 \n", - "5 0.905686 0.737120 \n", - "10 1.041629 1.851082 \n", - "15 1.795035 1.523272 \n", - "20 1.027982 1.873740 \n", - "... ... ... \n", - "930 0.158071 1.707738 \n", - "935 0.003870 1.839969 \n", - "940 0.504404 1.867278 \n", - "945 0.080560 2.732715 \n", - "950 1.013029 2.501380 \n", - "\n", - " Atol2__Atol Center 1 Atol2__Atol Center 2 \n", - "window_start \n", - "0 1.041305 0.869459 \n", - "5 0.000000 0.000000 \n", - "10 0.934886 0.006830 \n", - "15 0.009076 0.957346 \n", - "20 0.000000 0.000000 \n", - "... ... ... \n", - "930 0.000000 0.000000 \n", - "935 0.000000 0.000000 \n", - "940 0.128751 0.723518 \n", - "945 0.000000 0.000000 \n", - "950 0.205330 1.519385 \n", - "\n", - "[191 rows x 6 columns]" + "array([[8.08749090e+00, 8.29919679e+00, 1.39429336e-01, 2.36937873e+00,\n", + " 9.26644191e-01, 6.96280517e-01],\n", + " [7.69527314e+00, 8.76540196e+00, 9.05686145e-01, 7.37119558e-01,\n", + " 0.00000000e+00, 0.00000000e+00],\n", + " [8.55884467e+00, 7.32851193e+00, 1.04162910e+00, 1.85108184e+00,\n", + " 6.44486394e-01, 8.74194056e-04],\n", + " ...,\n", + " [9.88785864e+00, 6.01418384e+00, 5.04403623e-01, 1.86727825e+00,\n", + " 2.35723692e-01, 5.28511461e-01],\n", + " [8.23658921e+00, 7.29718991e+00, 8.05604535e-02, 2.73271515e+00,\n", + " 0.00000000e+00, 0.00000000e+00],\n", + " [8.49385276e+00, 6.16764628e+00, 1.01302941e+00, 2.50138037e+00,\n", + " 3.78286963e-01, 1.15246551e+00]])" ] }, - "execution_count": 5, + "execution_count": 25, "metadata": {}, "output_type": "execute_result" } @@ -497,13 +329,24 @@ }, { "cell_type": "code", - "execution_count": 6, + "execution_count": 28, "id": "20f7444c", "metadata": {}, "outputs": [ { "data": { - "image/png": "iVBORw0KGgoAAAANSUhEUgAAAh8AAAGtCAYAAAC2txYyAAAAOnRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjEwLjYsIGh0dHBzOi8vbWF0cGxvdGxpYi5vcmcvq6yFwwAAAAlwSFlzAAAPYQAAD2EBqD+naQABAABJREFUeJzsnQd4XNXxxUdWtWxZ7r3gRscGF3q3KaEXGwidUEPyB0IIhJIAIYQYCKGFYGroxaZX40KvbmDAYOPeuyzJVi//73ffztPbp63Sruo9oG/Xq9Xuq3fOPXNmbkp1dXW1WFhYWFhYWFg0ENo01BdZWFhYWFhYWABLPiwsLCwsLCwaFJZ8WFhYWFhYWDQoLPmwsLCwsLCwaFBY8mFhYWFhYWHRoLDkw8LCwsLCwqJBYcmHhYWFhYWFRYPCkg8LCwsLCwuLBkWaNDFUVVXJmjVrJCcnR1JSUhp7cywsLCwsLCxiAD1LCwsLpXfv3tKmTZvmRT4gHv369WvszbCwsLCwsLCoA1auXCl9+/ZtXuQDxUM3vkOHDo29ORYWFhYWTQh/eGmuzF6WJ5Mu21965GY19uZYeFBQUGDEA43jzYp8aKoF4mHJh4WFhYWForisUj5aul0qq9JlxpJCufSQ7o29SRYhEItlwhpOLSwsLJKAyqpqefyzpfLtyq2NvSktBvPX5pvjCt75fm1jb45FPWDJh0WTRGlFpbz7/Vq56KlZctWLc90Bx6J54/NFm+TMR7+S5Zu3S0vH2/PWyG1vz5dx//1Cnvt6uXmtpLxSFq4vNMa8poANhSWyckuRNBd8uzLffT5vVX6z2naLJp52sbBYvbVYTvrP57KxsNR97TcHDpRhfTsm/LsgNaltbFVVQ+F/XyyTLxZvlkc/XSJ/P2mPsO+b8fN66dIuU4b3S/w5byh8MH+9eayoqpYbX/tBnv1qhSzeuE3KKqrk2GG95J7ThktmWmqjbV9BSbkcd/9nUlRWKZ9dd5h0zM6Qpo55q4JVJCYolx4yuNG2x6LusMqHRZPDhz9vMMSjU3a6dGnnDIir84oT/j3frdwq+94xXS5/bnbCP9siNFYFzuO0+RvCzv6ZzV741Cw567GvpbCkXJojyiur5JMFG83zU0b0EVLgP60tMMQDvDNvrZz/xExDABoLD3+0WDYUlsq20gpZsK5QmgNQO8BRu/Uwjzb10nxhyUcD4+OFG+U/Hy4yaQWL0PhxjTPA/Hrv/rL/kK5BQSuRM6izH//akJx3v1/nqiwEg7unLDBy+Z3v/2zOl0XisCrPkcnXFZTIj2sKQr6H1+ElBMU3vl0jzREzl26RwtIK6do+Q+4eN1xeuHhfueOUPWTGHw+RZy/cR9plpMqXSzbLFS/MbZTtW5tfbPwoiqWbmn4aLL+o3N3OPx21syBY2tRL84UlHw1881z+7Gy5a8oCueTp2ca5HQ2vzlllBommkiNuCHy/2iEfe/TJlT4d27qpmESBnPvZZlZd4b720YIN7mzwwQ8XmWP+0EeL5cL/zTQDtUX9kV9cHnTMpwbSEn6QmlA8//WKZnntT/vJuZ4O26m7tGmTIvsO6mLI9KBu7eXAoV3lmYv2Mb//9JdNxgcSCVVJ8Dvd88FCKQ2oMM2FfMxb7aRc+nfOliHd25tjqqkXi+YHSz4aEM9+vVy2BwgHM+rznvzGzO4imcH+OOk7Mwv/x7s/mUF4e2mFPPHZUpMyaIlAEVIJePc+udK3U9ugGXMiwPErKKmQEf07yoUHDjSvfbRgoxnkdaZ9wvDeZoAjX//Ml45ZsDlhzoo8+f3zcxJ63OoLf+ps2k+hyceiDTXkY/7aAldqby7gPp3+s7NvY3Zx0gN+7NWvo0kp4jmKlPL470eLZditH8hXSzYnZNv4vme/Wi6vzFll/n3KXn3M45LmQD4C18Gwvrnm8Ve79zSP0392iF4iUFFZJddNnidH/fsTGfX3aXLoXR/KuvwSSQbytpeZn9YKSz4aCMxunvx8mXl+/v47SE5mmnyzdIvc9tb8sH/DzFAnfY9+ulSue2WejL3nY/nb2/MNKWmJWLhum5RXVkvH7HRDPPq45CNx6oPK/RcfNEiOG9bLPP9k4UYzwKOwtM9MkzvHDZM/HbWT+d3z36yISaVqKti0rdQoa2/PWysPzlgkTQVKhPp1bms8EJyHNSEULSUfXdtnuupHc8Lijdtl+eYiyUhtIwcNddKGofog7Nrb6WP0QyDNGK5ihgnKX17/wQTG+gDPySkPfS43vf6DIKZAPE4e0afZKB9asrxnwIR86E5Oj4/Zy/MS5p1hUvjSrJWyYH2huY+WbS4yY0My4sFR934iB9/1YYudSEaDJR8NBGYaXMy9c7PkxmN3kUfPG2VenzxnVdgb//0f1rnpB/DyrFWyNsDCGaC3FrU81qwD8e69c80A3a9TYtMuDOAMLGCXXh1MBU3ndhkmPw+p0xlVVnqqjN2lhwmUW4vK5bW5q82s8YtFm2TuiryoUnljzrr/NOk7c62pIa8u28rn3PT69/KHl75NWJmzEshhfTrKyP6dzPPpPvUD9UnTLtccuaN5fPO7NfLvqQvNjH1zYL+aMnSf9h3cRdplhi8o3K23c1+H875w3JWI/bJhm7w4c6V5zjFYFgdZ4FxS6nvifz6X71blm4nPzcfvagj2wK7tzHsofa4vuWmoSheteuvXOVsGd2tnjtNnv2xKyHe8One1eYSYUZEElm9JPDH7aMEGY/YlDXnuE9/I/DDXQEtGvcjHnDlzZOTIkbVeX7Jkidx5550yefJk87h1a/NidgzceC3+/Mo8lwDUB9wcj36yxDy/8KBBkp7axuQrD9+5u/ndfdMWhvSHfLnYkVrvO2NPMxBT/fH7w4aYgAgYSJobCN4YOsMFRPV7kHIBvQOeD25SPAP1BfIyFQcY/sgdU2Z76I7dzO9+DsjfJwWkaH53/v5OWuahjxbJ0fd+Imc+9rWc/NAXstvNU4wfpKkpIk99sUw+XLBRMtLaGFmf40b1ULwg2FEaCulixpxI8oGiNXZXJx0xNeCNUKwtKDGln2ltUuTUkX1lxx7tpbi8Uu6b/ouZsTcHxe/rpVvM42E7OddVOOwWUD7CkQ+UIq8v456pC40Jer9/zpBD7/5Ijn/gM3lp5oqInhB+xzGj1JfrfszO3WX6NYfIBQcMlLTUNtI7t625VlAbE+mrSjTwXa0vKDUm09371HS+VvVDPVv1AeOL+pAo7d8zQHJQsRKNt+c5PhWOPd+L+b0pH/8mRT4gFkpA/Bg/frxce+21Mm7cOPNz8cUXS3PB5NmrZO/bp8nVL39nZhp/mvydWx7nvaFvfetHU7USC5C+ke9y26bLGaNrFs27+ghnZvfGd2vkl8BsXDFjwXrjN2DwxaT2+8OHyty/HinXHLWTjAjMGpubXIdSc9mzs42hkyAZCj94zKYgOyMtoeW2OsPYuVcHYwQEh+1c06K5e06ma2QDp43qa9IwBE4CcocsZ3sgjeSa75m6QJoKmLne/YFDZG88ZhcZP8q51iAQ8cJLumctc4JpotIukA+CICDV5SVwOtPfoWs7Q9IfOmukXHH4EGPW5HThzfl5XdOeJS4LNFDbqUdOTOTj57UFIVWHX9Y7x2Jo9/Zmhr9le5kxQTMecSwg6te98r3pmRIOnPtX56w2RPqGY3aWx84bJd1zatZD4R4Y2KVdk/Z9oNzc+uZ8d1LCmKA4JDBxIF1SX2Pye9+vNceWMZdz079LdlLIB9f79ADpfuK80bJzzxxzbt/4Nv77VCeqj3yy2MSuVkE+IBUjRowIqXp4MWjQIJk2bZo0Fzz/9XKTD8VsSKBh5ug3e1Eih3+DqpUVUS5MJNh/B5SNvxy3a5AMy41EvTr3jL7HP/gfvZtjqvJCc57NrW0zJAyjJ2DA9KsG9Eb4ea2aTWtmNzW+j/oPAjqL37VXzecfPLSb22gMo6m36VhOVrr84YgdDSm5/NDB8ul1h8usm8bKxHMcxa8ptc9evqXI+APapqfKOfsOkJMDCs6HCzbEnaJ7z0s+luclWPlwqhWoZGKw/3LJplrkY0i39s5j9/Zy9ZE7mTLVX+3uyOCPfVpTIppoEMDwmFARVRdASrX0U4NXOOzQpZ1R4FA3QgX+hRtq0oM3H7+bUYM4Zv89a4TMvHGsa5Z+LkxFED6IO9772Tz/45E7yiUHDw655sagbg75WLqxaZKPRz5ZIu//uE7SU1Pk1hN2C/rd3gM7m+sdVeSnwNgRCowt7/+w1qiu4e4FSBo4ea++5jhxfkCiu/FyPxaXVxoSfsCQLq7vTMlmKHCf3PHuT3LPBwtcAyzbddeUn+WACTPkH+/+LNdM+i5hxuRm6fmAaHTu3DnoNf4dSiEBpaWlZiU8709jAQapgeTp3+wtxw7rbZ5P+TE49fKmp/dApFklXo6rXvzWPD93vwEybmTtJYYJbIwH9Jrg5gAEZe0vcWQI8qFdH9nWurD9iR8vlhG3TTUVEQ0FBuSnA1Uj5Jw3bSszRk4vGPDLKqsM6SMlokhkuS3VEzqgK3Kz0w3Jy85IlTP2rlGmFAzy39w4Vq49emejXjEwHbVbTzlpz96GqOKxuOXNH01a5vZ3whuIkw2tmmDmxox2p545Zj+R1ONpxsSg5k21zFqWl5ByVyWPkEmO4SGBtMTHgWZcQeSju0M+vLjoICfYMkNcX5CcCoRPftkkN7z2vfz22dl12mfSAxxvAmWvXOe6DQfOkV6H2tvGCw1GnM+Dd+wmX1x/uHx4zaHyqz16SZf2mYZQQF5WbCmSmctq38v3TfvFpJAHdW3nEpVQUN9HMk2nVOnVpWrk6yWbZcL7DoGCgO0VUH0VeLP2G+wolR8tDJ16QRE4cMIMuezZOUZ1JX0Xanz6ZtkWMxaftJcz7usYxIQpkf46GswBPCXcB0MDCtkvAbIZCqTcJn6yRO6fscjsC4UHh9z1kfznw8VmwsGYCm59a36zWYoi4eQjnL9jy5bQ0u0dd9whubm57g/L8TYWPl+8yVU98BpoFz3ygJpXNWuOBEgCeP3b1WEHKS4YjIyjd+gkNx27a8j37Nyzg1x6sNMe+M+vfm9ugtvemS8l5VWGGas06wWzdgY3pLp4q0DYF2ZD/O2LvuCvg8TTXy6T61+dJ6dN/NLc+PUJPHSoJNWBmRNiceCQrnLDsbu4JMjr/dCUC4qQd4am5bb1TbuwH5p20UoDxb1n7Clf3zBGhnSPvhS04q/H72bMqqRjaBuOZ4SqpE9/2dio5APSoTg5MJC+EkWSpepk0qyV5nwo2aYUmdk2DcHqS/yYhavqpWRSvTYfeaoJFkcgHwSevXfobII7xzsZWBg4hlSsqAcoHqgS2q+T4yeKBtf3sbr2pEuDkV6TpEvwCChIPxyzR6+Q5xcir8fo5hN2i9jGPdnkg7GT9Xyo7NB7PFYQcBl6UfHO2qd/yPccGiCxU35cXytFDkkldY4yQrqUU4Lf4ovFwQZVTXnsP7iLSxrbZqQaxROQNk8EisoqZEbAg3XcHr3dtJoS71D+HbZ14ieLXUWYdDzv5fpiPH347JHy0Z8ONZM2Jg0veMZ1iMjvnp8jJz/0eZPzpzVYtUs4UnL99ddLfn6++7NypePobgzoDAwZHuw/uKthlLiS5wYUEd5DKqZbTqaR+7hhQ8nukBQ1+l1/zC5Bg4YfeD/wOFBVMeaej93Swt8dNiSkTArb17SBblcsYFuvfslRYsLlSUmH/PWNH+WFb1aaUmD6DJBnrgve+m6N7Pm3qXLM/Z8a0sOuXH/MznLqiL6m6ofj+tCHi8w2IIsyeHj9HgoNVvUtt6WL6ebtZWYA8ufj8ReQYokHEI9/n76n2d5f793P7Ttw8xs/NkoHW00V7OjZt5P27GMIxJwVW8MaRzn2NF370+R5cvojX3nk5z5ucET9qA+UOHLMNPVI91pINDl1DXyLNoYnH+DigweZR3qv+Nf5SKRfQz0AdUl9xZJyUewWuNb9plOCkKpAKB/hoGoqypYGF649FFcCzxG79nB9EeHgpl3CkA/uz0UbCus8o2aNG8zxEIM7pyyISFApKZ4Z8BhBhNV0f8nBg8Iu004jN65xPHBU9HhVJIg0Qxy9Qb68foycve8A9x7luvcbQE8c7qQqFQNc30diiBnEg5RL/87ZbmqZ55RlM+H0j3H0Abn6pe/MPuAXfPv/DpK3/+9AeeDXe8k3N4yRZy/aR47evadRwtRDePcHC9yqsMc/W2KUlrkrtsonjTQpajDy0bFjx1oqB//m9VDIzMyUDh06BP00BrjB9OQcvKNTmw9hUDPiB4HZIGV/4MThveXIgDLyeojUCzcNchjMWV3T4cD3MPOGzHCDIu0/cf4oY7ILBzf1siK2AZiL+JKnZxklZuSATm6e1D+70yBz7B695NLAQI+3pS4D8UszV5oBC0ZOgMYESXkh+4uBFiAjYkJlHQ+dEfgbM+ERAPWdfWvKhZkes5pEgIH9rf87UO44ZZj889RhpjcF+Xtv6+rGVD66d8gyKSKgaa9Q50k9Bwzgek2Q8hu1g5NCnbV8S8IqXRQYeUcHPp9qBdQ4frwB0Q+MqiiJ3FtnPvq1IciJhNdcSECPV/VT8qJ+gWioqXjJD/oujhfBiHvFm4L0g+NH9RvHQxUrfA1c61TH/f2k3aNuw8Cu7d37K1QVGmXOY+/5RG549fuY9olriLbxqBzs0wMzfnF/p/10QuHxT5fKM18tN1WG/B1jEYGaMRRTZjhQcvvgmXuZ/YVgsyilmvHf+945JvgqOJYEaFUr1fS+ZOM2c81DYHRMVwwInMdo3r5Y8frcNe72pATIFFVHer37Uy+PfbbEKI+kzv56/K6uMnz88N6GcHgBsYKoMokdP/FLcz3cPaXGS5iMfiVNinyMHTs25OujRjl9LZoqmGXQQ4MLdJ+BNdUOOnBzIrkAtSvjCXv2dg19b81bG8Sinfc77+Ni1qqKSBjcrb0xMZ65T3/DbA/fOXRnRL/p9LsYZn94WSjl4objRsaw5uZJPfl2bnidTf720MFGsaEhGvjDy98GdZ6MBtI3GhhevfwAE6AvOsghMwCl4KZjdzEzX44V7yUYPXbuKGMi8yJRhtNQfo9EAtJIRQF4YPqiBi2dI2iEq7I4Z78BLkn2lytznu6d9os7u6SqAowa0El6dMgyj4lQPryVLl54qxX0+kLp8lY0eMG99OQFe8u+gzqbgHvuE1/HLeXHqnyQelnoMwEiz0eq/tEgFYkweDG0e465B0hJeWe9qmIRdAhO4cDxOGUvR/2gC/JVL841qT9w57jh5hxGA0Gba9e//2Da/PVmggBovsVqw9HSCpc/N8dM0phQoJqi6uCnUmMl5MhP6lB6tFqD404305rJYLewqofi6N17yQd/OMQYOEnL6ez/66UO0VGzMiv3XhtoHnj/9F/M2Kjt2VHi/Cv7DgicR1W06gMmgB8HfCknBWKHosb3EXy9fbVkizseh7snFFwnD545wqjKSzZul0ufmW1S3aocJ6IiqMmRD29KheoWf/ULxCOc8tFUoAbPfXBPe2bF5BMhJOT8yFkyG2HmzEyefBszXWZrXOx6YrmRtF78yF1rG0bDgZvsHyfvYZh8NCj5YOD1Ex+/54IBmgGARa6ev3gfMxvWQd9bH49xjUEQCVClewgC+8l+M2jECpQfLnyCjQY0LxhMICOv/vYAEywhBK//7gC3/0Mo8pFXVG4Gt7pC3fB+v0ciASFlZs6M7e+BpmXxAvULqTQesmfyxdVOICEl6AXXtPbL8HsDUGgwJSIvX3PkToYoXnf0zvLPU53l7kfu4JAPGrPVp8+Kt9LFC+3T8MWizca0GynlooCk/u+CvU2g4boMV7atYP8gWdFAukI7rg4PtPD2rhvCGHHli98aIh8uRaHKicr10cDYos3GvOZ1rXTxptDCYfyovia4k8Z8PWCGP3vf/iblEgu4F13fh6fiBSLFpANoAPvzK9+bgB2pok1JN9cLqimg+opqv6z0NqZ6iooPL75a6nQXVtBnSdPg0dJGCq77f54yzHghWDOH7+aeQF3yjqmUoHM/MNbhpXgnoI4cu0ftsbp/AtMuKGkQI1LmO/rOq/o+vFVWTCi+D/Ry8k/IwoHPZRzV6xeVh0UNGdO5B5tSOXWb+lS1XHfdda5pVPt+gEmTJpnf8drEiRPNv5s6lHyo30NBfprGXmpWAhccsIO5YWGaV44ZYl6b+PES+ePLTk8QfBgMePhFvD0jEglkXWYrlOnNCZRCcrGe/+Q3pvpC+wbc/OaPJt9KUHruon1d85qatGhNrMuW69oJu/TKcT0q7CPdENl3yt3ClZUycF87+Tt3sFbnOd8TadayR99cef+qg+TdKw4MG3Q6ZKWb1E19TafzA7ngZCkfgH3924m7mwGQctV4pU7IIFUzmMTOe+KbmBcV8/o9/Mebf5+zn6Ng0SVUP5McO6ZfAPHgnHNNMcvymhwJpPDq+lRHhVM+CAI7dMk2RFWVKR04IwHf05VjdnTL0kOlC0j5PTjjF9nnH9ON7yhS0HS2sdgEKwL5uYHjpdezSR9MdxQiCA/Xuv/c8B4IfDzkA1x84ADp1T5V3p6zXNZvKZCSkhLZsKVQ+uSkyrCebc2/I/10bdtGZly1vzx65jD5w2E7yJWHDJBrDh8U9e+8P3v2yjbft3zDVve1f779nXRIr5Yjduwkb/x2tOzTP0fSpULuevd7KSoqrvUZC1ZvlnfmLjefc//43WTsjp3M84Ed0+XcfXpLbobIbw/sb16b9PWSoL/9YN5K8/q+A3LM45cL18m2oiLp0yFV9u7XPub96JbdRs7bu7f5jE9/XmMeTx7WLeg95WWlct0Rg83v3v12hRRs2y79ctPk0MEda31e/9x08754jmW4H92eM0b0rPW7Xbplmt/lFWx3X/t+xUbplp0iu/VoK92z28T8PR0yRJ46dy+548Sd5bnzR0j3dm3kqJ07m8//auG6eu9HVVViOuFG1nGipFf4mTBhQq3foX7o6/QDacqg/IuGYTBloOV/XlwxZqj5YTAjyHrlLwZ1Bu0bXvvBtOadtzrf7cqJXySS0bQ+QG49ctceMmn2KtN2fZ9BXYysrmkUBmdmhpgHIQ6PnjsqyAtALpPZDjO4zxdtMrKldhfV9sVeSZDad1rEU1cOifGDWQrbwcJsqEK6HYfsWNPAKxyiSao6YyY4ESBUoowHBCedre7SM7m+IsjNefvtIE98vtTM5t+76qCI1QaKl2eulGtfmef+m5kg5X+xENhQfg+/IjPhvZ/NzIdZJmbqGT9tMAsdkm/G4xMOKCfM6DFCY+5LlOdDzz2mOdJuuPgz09rEPGMnJdQrN8ukSw1pC0jrAMn9t8/OMccPsP2U0OINCHe96eyWewMFjnQIMjj3Vc/cLDNjZwbJ65S2Uk1CJ0z3O7eXmVQQH+9XeEIBsrJu3ToZmF4odxzRw8yKly5bZgjgYX1EDujZXbq0q5ClS2PzD/VNF+nb3xlv1q6Obz2c4walme/LSCsx38dYd/LQTDllaHfpkZspG9eskhsO6iIbC9sLlGvu/IVmQuM9lky4bjqkm7RNbyNdsovlD/t2lILidmYMLNiwRqCWY/qmyG453c1nLFy02Bi9q6qr5aCe1XJAj+5GvdiyPcc1t/K3W9avlnicPScPSZf9uzvfAXp0qKx1DHunitxxRE+3gyyKTKjvyaiqllsOc675xUuWSJsYxqpQqKiqknE7Zsr4HbtLz9zyWtvTo02V+R7G6iVLlpprqLqk3LyGP2/Zsviru/ZkGN+2QZZuEzln92w5YXC6ZKVvM9/NtceEIhZLgB9t2rSRgQMHSkZGcIqqwchHSwDmpNMe/tKYMJmpXnH40IgyJ+8JlXc7fXR/k1tFkkX+Vrncb15KNH69T39DPt75fo389bhd3YXrAMatl2c5lUOXHTLYNQ56gZxJQIYoMHCr3wM1wo+rxg6VN79bLZ8v2mzWUWBZcC9UruZmdlZTLTYDNaVriQCpF0M+6uijYD8Zz3Ky0qRHh+C0RDJw1RFD5a15a0ywpzLD63cJB5XdTxnRxxxHUi/kzmMiH+sjkw9SFeTc6dpLnxrIx3uBknGIR6RBiAX4Xpmz2qQSIaoHDAm9WFpd0i76WizB2g+2maZwlGNynLzk419TFxriQR8Mjj3diJG9D5rZVc4IY+RetslRLVBiIADsN56FayfPkx26ZrspDsglvSLunPKzIUoq6WvKpWeHLEP+owHiQcq6B0G3V7qsyS8xwTynXYaUZ5eZAEH30YwYPqu+IHWL8RL06drepKkq25WY/VDTJehZXCbr80ulWqolPSNV+nTMNuehtLxSyjZvl1xJMccqIwLZbpvnNMPLzc4w4yY9NCqySyQjNdX8LVVpeYG+GpgqdYHBeNB+a7FR9vjMgWHMy91L8dk454xUdCef30NRtaHQqFx9urSL6byGAmS4ql2pUdX6da69PRAw2bDNnPO+XSFsqbI6r0gyS6mszDLpk/qA84Ofh+ura26WbCosk8y0FOkT532H6rFmzRpZu3at9O/fP6aJYzi02oXlOMl/e2u+IR6UPL31+wPlyrFOBUZdQO760+sOM0GaAEeOVPPZyQLLcuOXQAZmxVsCEBc3aSJAAGOgvGqsI0/7wdoyKi2Tn/0h0GtAl6z2ggH2rH0c4yIzej9Yk0Oha86MHtgp4sJa8YC+CaCuCzCpkStUWiIZIFWk50FbKUcCaTI1D0MWtQ0/VUaRPD3+/hSRWnpjknbPd1G5m2pUU3U4oDSdHeixcNvb8TcxotcC1xf8xq981Be6T9N+2uCmD1G53g5Upf337JGmkZ+uUHzj6z/IIXd9KOMf/qLWYmRe5UNTUfT6ISWE8ZTJB+fmzL37GzWI+45ePooVgQXIYkm5VFZWGuLRvXt36dKli3TtmCPts7NFUtNlS0m1eUzPyJKc9tmSlZWV9J+cdtnSLjtbUtIypFxSpbiqjXneuUO7oPf16NRBBvbsKKnpmVJclSrbKlLM60WB93dony0d2gf/jf+ne6cc895t5SlSnZoueaVi/t2lYztp27atdOvo/J6fTjmRPyvcT99uudIxp5306dYh7Hu65LY3P9nZfGf78J+XmeVuT12Pb1Glc3y65OaE/H1227bmkfdIaoapAi2pTjX/7phT/2uA85KRmWWuq7XbKqU8JVVKq9MkNT2+fcrOzpZu3bpJUVGRVFTU3X/X6sjHzW/8YFZ3hHhgeKJNOrIeTVoSYUIk4BDoZ990hEz/4yFmtplMEESpGgH4MQA9NOh8SCtwytNYlC5c6ocZLGZQjFcQMWYjyI/a2tqP0wMBETOpP8e+dqtDPpBiFYfGkHKJFYft7KTDmK37GwnFAl07R41dDYF9BjlqE4pStIBNcGNBNXxCHP/9BnUxBmFMttFW7GSGx6wZREpJUcWF6sP5vvXtHyM2svOD6xrfDSWJlObGA62UgQhHc+zHC8x7XMNcE1phRgqGfSQlg1kaoGLQh4XzgEJB2uTmN38Icv9rIymUD8CM/t7T93LJOD1TIOG8jnlSmwwqIXbNpiFmtn6UlztEicFc7+XeHR3FhHGEBd/wQDUEUVZ0aOucG1SH7aXO/d0hUAXjBf1w1AROp2KOKeWdoFMMM3TGRdKQlaZ/yDZDrvl354DygOEftQMlgslUXUA6BxLJsYwEFDcqjtLahA+FpAJBXcYdUFlVZczegIlptO8prag0E0eOK2meuqotXhhFLfDdKZJiju9OPdub4xQvNN0Cga4PWg35wPj31JfLzeqOqAR3vOu07L1g/x3qJPlGAsE+ERdMLMCLoRctOD9ghqUV+PtXHRw1jUQjM4CfA+C8D1faB5mhVJcbyV96qa2T/3jkTiZoUjMfqnKlriBNQD54q2fGHg/cRbrq4BepKxjUGDzxVegy8eGgZs49+3c0wY1zoD4M7S0TTfUg2GrJZLjzTZoCaCMxAnIsAY6gogoaKYxYjbBAm0Zp2W4iwbafuGcf10zLgK37hiqi6SQeHzprhHz8p0PlxUv2NeeFkk4tZQylfGggZKmF207cTW4+oaZLMb0WSGPBXUi/OH8fX4Mx3f6a70oz9yuL6nXNyUyaXywccgOBGhJMWoUxLJxXqWPbdJNWxctAV2YIBPd8pODq3WdNI0D++A58R95xB98cRK8hyVc46HnYUFhi+rGQwo2nZJX7Xz8nUrDPCsQMJgVancV1WlefiR+kA/EuDe3hdPBOjUC4IiFR56TVkI+DhnaVP/9qZyP9YoxEhu+YnS6XB4JvcwXrkmiQorKEfiHxgGDk7UkQKuWiMOtxuH0Z/EuhF7sEhVKv1y4/wC3fSwQInDR2C9fUjbxxpICozXsaUvlgm7Vba7RmcEo+SKX5Uwo0uIvUGlm7Y0ZqxKTQQK2gO2KsoAcNygxGWF02PhZQUQVGhvAdJQJ0+cTbQSUWaSEt49T+F97rF2KBh0aPA0ooIHiqL0X9HQp6P2As98+iScsQcPFMcY5qyEtiJzMNhUwf2YhEZI13IFDSjfJm3p9NRWBsgQmFlEDM9zFO1GUG3lCAFAKILT+k90jFxQolEu2iqH5ZAfKB8rS+0OlQmkilEHJH9VpDTYyjoeme8QSDm4V87dO/2cdNDVw1ZmjEG6y54M/H7CwXHThQbjsxejfDUBckKZpYyAdwFwPzqA8EfVU+enVsa5SkUKbV+kIb80z9ab0Z8AgYqAJ0NKSN+/2eTopeIGOqpA7rb0igZMTSBl/JyV4edWBE/07GO8TM6bNFm6ITF9+iW6FAikW7KaJi7dUvdjWCQUvXEnlt7qqYB14toaX/STLALO4fpzh9SahAoWqEFE848y3QdUJoHojBEcO0Vtv08Cw5HwkoFNqF+JJnZrvnOJa0S1OFpl7M8ygpi6U//yD33XGL+29vyjWWcYfzw/34yUczZOTIkfLII48E9Ye68847TbsGHsMtzxErWNhUW0PEC9KNNHuDJM3+4hM545hDZeLEmm2NBPbplptukMnP/U+mv/umaVHBa0t8q7/r92iTM22V0C6zYYkCx4lz0RBoNeRDQZXGlD8cLM9cuLecF+je2dwBm73puF1jak4WCqeM6GtuLGRBbXcdDuTQUY/wKGiFCyWGDPhMenQhpmSAwIlyQe6VtRkO/9dHpo2z9h5hafFQ3gqqGHidWTvSY0NCW+tru2dUgL++8UPQOit0PtTmP17lA8KspmC/0hRKWYCsRAOfefoox7tzoictEStOHtHHbVsdqreGH5wbjj0kKtoqr/UBSob6n8Apvg6SfpA2oVEf1y1VYUpOUS3iOSaoqaeN6msUEFXi40m7NDWQTgFZaanG/xUJjz36iLzy3FPO+9NTTUmoF9EIAyoJP7RsOP3004N+N378eLn22mtNqwZ+Lr74YqkP6DflJTd+RNpW7pn2WenG63L4mDFy1PEnu+QgEo444ggzMfv9n2+RcWedL78+Y7xZ4f3SSy8N+z2o0Hh9nN5G6WEN+/UlY6GgvbrCrUCfaLQ68qHB+qCh0Vv2thZAOiZftp9MuergqP4XmLl2V9XVW1X16NY+M6nyKedLgx9lqSu3FJvmb1eOGWpmDcxgNRCHasA1pEfDGvi8yofpEFpUbsqQWWPl2Ps/NQZoXpu70tlmFAl/e2dtBoe0HyrPvKGgxKQLiJfD+8WmNmG+pNPtNYEKkHjAqrIQCarEtItvJKg3iPWEkg2WXOfaxE/gb18dCrrIGCXqmsrz+j1iAcGBNuasKnrxQQNNe/26qKmcW7r3NsaP97oixUDwQ9WJdq/QtTo/f6ssmP2F9OvUNuj9zOxffvnluI+D/q2/bxSKQX3AthKwQ31OPNuq/o/yKJ4n1Bpw9gUXmuPLuIhHZsSIEXLJJZdE/FtSLRx/fkKlsepzbCMBksf2NRRadZ8PixpQT+9fqCgcaBzGKqmkXuhxsia/2E25JBvk8R/9xBmcSKOxbgk3KwEY0yxlpP5WxG6ZbaBrZ0OC2T4VJizid8tbP7rrB6HeYICesWCDDOvTMaxygT9BWyNjdBvk8/RoygWjYqyr8jKzx8BbF/C3J+3VW/7z4WJDAFngKhJ0QbpkpVy8YPYNiSYuxGLWxDDK+h50JdUeK1rpEi8g7TceW2NIjReYuHf96xRpDMz/21FB3oJYfAYEcdQKZsnT3n1Dxp94TNDvaTJZV/mez0Yh8IJ/8111CY7ebaXbtn/9sXi2Vc390arX6Pr96KOPevweqS45Q9WpD+pzbJsSWqXyYVE/qO+DrrDIj67fowFSGri1P7vucPn6hrFy6SE1iy0dE1iXgVJcv/GU5cAbw++hGB5IvWiAu/5XO8tzF+1jViNFvaH5VTjywcyafikgVJWPa+ZsAGXBW2Gl26PnPhQYoFnK29m+5JhNQ3kJYq0Sgay8+fsDjGIBwQM7J7n7bUuBEgFSCP5ZOMF+1qxZMnXq1CB/A3/j9XGE8j1ESin4V0tvjG3V5mmR0i68l31AsXGrVjzpE8jPoMAaaHy/fo96UnhNPTDqEVHCEm57w33O4MGDzfv4aWqExSofFnGDCg78E4UlFSadwGxeiUFDIFQeFC8P24TCgBrg7eiqK5NGW7AsmamXDwIpCsqFMSkS+Ghs9/vn57pm0r0CKRo/qDCisyzB/oIDatp5AxSoWP0eiQLHkfQLHURvf/cneeDXe4V8H/0v6B3DeYlk/mxMkOZCsTj/gIEyb+XWhJaHxwP8EigQjfXd9ZHqCYwEOlUUdOkNAp+mGAiSBEWCpoJgOH369JgXHa2vzyER29oup4NLrOlKGqm6h99TthxuzFoS+J7Zs2e75AoCgdeFbeL7dV00HiFEkbY33OfwOp4Xv5rU2LDKh0WdSkjdKo4VW2VdIO1Ck6TGAiV7GjjeDaxSCUhvLAuYOWNZITSZplNw6cGD3FI3At//Lhgt13iawoWCro/z1ZLg5m5U8eiqlw2pfIC/BhYbfOu7Na73x4svFm+SC5+aaZ6PHtjZXDNNGfhYfrVHr0Yr+USSR8VrjJ94fVAE78WLF7szambx0RYPJfj5Uyb8XSjvAmTEr3Lw77qsjJ7obcVYzH/VEZqOqaqx8JfFhoBw7Wd51DhVRiYGCAHbqF6UmTOde4aut6NHj454TLzbG+5z+DuISlNcZ80qHxZ1AlUZpF1QGbS7Zs8kVjPEAspASW2Qernp2F2MP4HeC5RQ0lWRJlyNgeH9OhrFgxmmtqj3pgl+f3jktv6s/EqVzrqCErMA28GBXiv096DfAAbLhu4tQbUIK79S2vrXN36U9648yJAq5Oh7p/0i//lokan+oPuodgO1aBlgBk7AUxD4qEbxvlYfxYLZeqjPGjVqVKNvq1nNPECkIR/hemagOjz6yES578AjzcTIS/DYpnEBIgDJ8XpQoplRw21vpM9RMtTUYJUPizpB+1HQn8L1fDRScPc2koNkkAaaHTBishKp+j0aq7oJyZV2++9ccaDpmBkvgpu71agMczwlto2xb7Txp7QaI+y4h78wDbtOm/ilPPihQzxYn+at/zswoc3mLJoeCKThKkm8hk//7wnCp512Wq1A6g+WKAUQj7ooH8nYVshHYUG+uyJuOFMo1jP6e3g7UHvJzekhvifeqp5w2+v9d128Msko5W0w5UNrhWFkKjM1ZBmPRXKh/SjoT6GSemOTD2YhLJJG1Qsrt9Kz5NVA2/hoi6clG9EaNkXD/kO6yEuzVrqtyoP6ewyo/6BcF1Bd889T9zBL17MoIUsXOK+nyR2n7CHHDYtcCWPRvEBAI6gSzJhl63hOOgNigO8AUyezbh55L79TgyX/xovAc9ICpD/4O2LFSy+9ZD5LP5ff8XmkHvS9iliJNp+VjG19+41XTVv5I48YK7869ICw3//MK2/Jv/91l9x5219kj112cj0XXtVjwoQJ7n7qNvuPB/FTFRy2J9z2+j9H0zD8Le/xV/mEOr/qc6Fah89KZqompTqeJvVxgAOkTV3YaT150VBQUCC5ubmSn58vHTpY53lTBk2+lmx0/BSMBwtu+1WDr0fhB8rAeU98Y/p/vHzZfjLmXx8bb8KX148xy3c3V6zNL5b97phhiN68m480KZyRf59qFp6jvNRrsG1osFw4xIgF50gP3T1+eJ0b3rUWlJSUyNKlS2XgwIFmtVCL5gOaAq7MKzIqq7/03b+YJSXU9I5pCZ20Y7l244nfSVM+cAfn5Tkzs0TIZRZND7TmVvLBKomNTTzAAYO7GOJB19VrJ88zrx04tFuzJh7aLwRTJOuqYPJlXSKIB/0D8JQ0JugPc/mhQ8yPhUVLR83qs+HTLszp9ffetItFDZJ6VCAdlni0XHjl/t6NnHLxGjh1/RFNS5wa6Ira3KGNuki9UE0C9hnUpUkvymVh0dLgdjmtrAq7mCUmdypdqIxpCpOypoikHRU8HjQ80aYn4RrKlJaWGqnG+2PRPOBdlKyhenzEAl0NFiCNHrlr4/o9EgVKVpV8fLZos3l+wJC6dSq1sLCo+wRHfW7h1I/SQEl8Rpqzfo1FA6ZdMPKo6oHZhUV2qLf2A2PLrbfemqzNsEgiKAHNzkg1jXSSuWhYvBjZv5NRYigBPnaPXnWqMGmK0EX/tGsoOGBIl0bcIguL1gnKZ1kXp6yiMuT4UpNyaRljT7NSPrxKB+SDf4dSP66//npjTtGflStXJmuTLJIwA9DW4Y1d6eIF/T3+eOROZln1Sw5pmjXudcGQbu2NcQ0TGz9d22fITo3UOM0iMaiqir46qkXTg674m1/stE8PRz5aYsqlOkE1KklRPijtGTNmjGs4VYRq75qZmWl+LJonLj9ssGH+xw5zfBZNBaeO7Gt+WhIgVaMGdJLpP28w/2ZxOLsyc/NERkaGtGnTRtasWSPdunUz/7bnsvmgfWq1bK4ok7zCMsnNqJZMX7OxouJiqa6okJTKNlJSktKiiMfGjRvNtZqent70yIfWHXvrh6kXtubTloeDhnYzPxYN5/tQ8nGg9Xs0W0A8KFVcu3atISAWzQ+F20qluLxKtm1KNV2GvaDxIqbT6pwM2drCUi8pKSnSt29fSU1NbXrkA5JBRzqatPAcr0e0fvoWFhbR4V2ansZjFs0XqB39+/eXiooKqaysWbPHonmgfH2hXPfsbNPj6H8X7C19O2W7ZtOLXvtUWABm0mX71yImzR3p6en1Jh5JNZzSvc12NLWwSCyG9e0oY3fpYfweOthZNF+ofF1fCdui4TFsQJbs3KeLUSL/+Mp8uWrsjmYZhOVbt8nqgkrT6bdX5xybTgsDu7CchUUzAj09Hjsv/gW2LCwsEo8/HLGjfLZok3y3Kl8u+N9M6duprWsCp/upJR7h0fKsuBYWFhYWFg20uvOUqw6WCw8cKB2y0mRVXrHryRpsF1SMCKt8WFhYWFhY1BE7dG0nfzluV7nmyJ1kxs8b5K3v1siPa/PllBEtq9quxZMPrSG2nU4tLCwsLJoTDtqhnRy0w1D3360tjhUE9jeWXiBNjnwUFhaax379+jX2plhYWFhYWFjUIY6zum0kpFQnql1ZAjv+Ufeek5N4lzCsDFJDF9Voy/02d7SmfW1t+2v3teWiNe2v3deWB+gExKN3796ml02zUj7YYBqYJBOc/JZ8AbTWfW1t+2v3teWiNe2v3deWhWiKh8JWu1hYWFhYWFg0KCz5sLCwsLCwsGhQtCrywQJ2N998c6tYyK417Wtr21+7ry0XrWl/7b62bjQ5w6mFhYWFhYVFy0arUj4sLCwsLCwsGh+WfFhYWFhYWFg0KCz5sLCwsLCwsGhQNLk+H8lsMmZhYWFhYWGRHDTrJmMQD9ta3cLCwsLConmCTq7RmoU2OfKB4gFaehtaCwsLC4sWhNlPi2xeKHLoDSIZ2dIaURBoI69xvFmRD021tIY2tBYWFhYWLQDz3xT5+EbneXWhyLgnCGbSWpESw75bw6lF/VBeLLL8S5J9jb0lrQdrvxPZ9Etjb4WFhQXIWy7y5u9r/v3jqyKf/bsxt6hZwJIPi/rhvWtFnjxa5Ke3GntLWge2bRB5/CiRJ38lUlne2FtjYdG6wT34ykUiJfkifUaJ/OpO5/XpfxNZ+kljb12ThiUfFnVHRZnIj6/XzMYtko+VX4tUFIts3yiyYX5jb42FRevGVw+JrPpGJDPXSbXsc6nIHuPJvYj88Gpjb12TRpPzfFg0Iyz7VKS0wHleuFZaGij7LisrkyaFNT+JtA9Ug62aJ9Jpp8beIosmgvT0dElNTW3szWg92LpC5KN/Os+PvkOk0wDn+YD9Rb6f1CLHxETCkg+LumPBuzXPC9ZISwKkY+nSpYaANCl02EfkgOHO8zbtRJYubewtsmhC6Nixo/Ts2dP2SEo28Li9+yeR8iKRAQeK7Hlmze9yerfIMbFJkY85c+bIxRdfLLNnzw56fcmSJTJ58mQZNGiQeX7JJZeYm8Kihd18C96r+XcLYvk0ylm7dq2ZRVI2Fq1ZToMe842ljG7Ov9tkiHQd2NhbZdFErtmioiLZsGGD+XevXr0ae5NaNn5+R2Th+yJt0kWOuye4sqVDrxY3JjYp8qHkAgLix/jx411CAvmAoEyaNKl+W2rRtLD2W5GC1TX/LmhiNxoGsLXzRHY4MO6St4qKCjOQ06UvO7sJ1euXFYmkVYukpIpUo8iUi6SniaRaAdNCpG3btuYRAtK9e3ebgkkmZj/pPO73O5FuvtSnKh/4svDFpWU0/PY1A9R5Sjdu3DgZMWJErdchG15AUKZNm1bXr7Foqvg5kHIZdJjzWJovUrpNmgzev17kqePqVIVTWVlpHjMymtigUb7decxoJ5KaGXitqFE3yaJpQclyebmthEoaSMWumuk83+2k2r/P7uIoImDb+obdtmaEhOvJEI3OnTsHvca/QykkFi3A7zHsdJGMnKYlM5KeWBQgvMs/r/PHNLm8OcoHSG/nEBDzWoCQWFg0xWu2JWLzIkdZTWsr0mP32r8nTZvTs2mNia2BfGzdujXk61u2bAn5emlpqWnJ6v2xaOIo3iqy/gfn+dAja3KcTcVghQtdZxzrAtvZEqBEA+Kh7ZtVDbGwsGgYUFoLeu8lkhpQOPzIaWJjYhNEgznpwpGSO+64Q3Jzc90fu6hcM8CWxc5j+x4i7brU3GhNheWvDAwOYN33LaP7amWFSGVpQPnIdtQPVUNC7B9K43XXXZcQJXPkyJHyyCOPBKVW77zzTuP74jHcvR0rkrmtkcD7+F4e2Rf+nuf+1HFTAMeIY80Pnrr6HnOLekBTLn1HhX+PNZ02PPmgqsWvcvDvcNUu119/veTn57s/LChn0cSxJVDe2Xmw89ihiZWW6cxEvSj5LeCaUm8HXg8MpulZzu1bXSlSUVLr7RMnTowYhGMNXmPHjpXTTz896DWC37XXXmt8X/xgKK8Pkrmt4XDEEUeYxwkTJphqPPaD9PCll14q9UUyiAHEiGPOz+jRo2XMmDGSNKyeLVIYh1chf5VjrIwX2zc5Kmpzw8oA+ei3d/j32HLbhicfDAChMGpUaJaYmZnpLiJnF5NrJtgcUD66DAomH01R+UhE6gVlgZRHXX9KCpwBne3askSkOD/490V5IkWbQ/+tqhplATOvej1S2tSkXshB8/ceBQSyTxAMZfZmZv/yyy/X6VAkw1CerG0NB9QDAOnwAgO9/7V4kYztRfVAIVZAlHgtKQrNxgUij44RmXiQSOG66O/HW/Xv3UVevyy+7ynaIvLgaJHHxjiqXnNBaWFNZ+G+oxOvfFRViqyfLzLnaZGf3paWjITU6DFwqLLBYOQFNwjEo0n1+aBGe+mnIoddL5KV29hb0/xAAAWdBzW9/CYBm1QL2OEgpwsr/pSdj6mf6vCPAMFqaNywxiEcXr+HIrevSN4yR/nA58Lss0MvE8RRAAhQlLj7JwTM9klPJNpQHqr6LZbPS9a2hgOB/NFHHw35O1Sd+iAZ28tx9W6vKiv+85AQLPvMaQ2OZ2ryb0TOfTN8KTdk96MJgVbir4gccKVIr0ADvGhY8qFI8RbnZ/EMkR2PlGYBJhHsb27/GlNpROVjbXwK0qNjRLZ5SN/lX4l030VaIuqsfDBoaJ6Wm5mcqYJBhN/xGpJqk+nxQYkUC/68eKbI1/8V+ezext6i5u35aMi0CzOlryc6M49IWDPXSUVAiHY82nlNyUhzBT09XPLRvub19LZOjwG8N6A4zzwoESCF4J+Fc9/OmjlTpr7zujzy3wfd2bN6CtTHEW5WHa+hPBqibuusWTJ16tQgL0as2xoKvJd9cCdJBNkty5yeNUWbZeyYw93f8f36PTrWeX0l6hFRwhJue8N9zuDBg837+IlGWFA7FC+99JIhaUmZ0HH/KKgUm35r+Peu+Co4xfnJXbF/z5KPap7Pe1GaX8olguoRpHzEMSYunOIQD6podFJsyGDLRJ2VDy5+fmD6fnDz6uvem6ZRQdB69ZLgluBznhI55LpA/tyi3spHMtMun98n8vm9Iht+Ejn+3sgLr2k+tufuiSEfGDxRIOoClVGlSqTLjs61BpGgARHr4qRx7aU4i8UxW2rfrfZ3G+JRLdImTSQt0N9DQfqlfXcniGJI9UjY3HsERgKdKgrmvj14Xxncu7NcctrRJnVGkCQoEjQVBMPp06fHHODq63Nwt/XdN2Ts0cebckUdYwjSmg5JxLa6qCitTZgheu26ud+jzRIhVxAIPBdsE9+vkyoeIURjDxwtYw89SAbvtGut7Q33ObzOBC1WFYPjDInxd5VOOPkY/muR714Q+eJ+Z6G0XsNqv5f7EQw82FGS6amz/keRHrtF/g4Uk8UfBSvRpCazmnDKnfs4yGwahXy4avBaZ39jKYFeHWhHsf/vRVIzRD68XWTFlyJ7189T1VTRRPpGNwAIAL984Bj2TvqvSG4/J0+OXNgS8fUjIo8cFlveNh5gEOO4ecmHKh8mACYpfwvpAJyv8uLav+c1BgidmfTdW6THHs7zvKXRFZNIYOAw5a11+EGFSc90ZjJUBmW2F8np4RAjtpFyPeRbVIxQ38Nrrt+jfehBDFISaDo2bco7snjxYndGzUSglvJYFThHHJPKChP8/CkT/i6UdyFeQ3kkQIqCtnWHATLp+adFtjstwkMhnm0NBVU1jCqhiyJy7DKdwLfkp3kmwCshYBvVizJzpnNtdenSxZg+g47J2hUOKaf/g2c9oEifw99BrOKZpCnxSorqQeWU3meH/0Vk5+Oc5z+9Wfu9vI/24hDnY/8tsuuJzusfB5aUjwSOU/4KpxEXYwhpw/lv1PaS1KFBYFJAp+QJO4j8rbPIL1Oc17h3I0HHRCYVJVvjSOmISJ+RIv33dZ4v/7JlVOuFQOvpy9x/H5ETHhTpOtQpkSJQTrtF5OuHnUWBmnNzHnL9m38R6baL0+CGIPzxPx2SMO9lkQOuSLzqgdRPIAXtugVaflc6gUNvvERCv5eAgRFrmCc3T8742VM9bccDyoeWAaPIQD65BhoCzOIgDByXQCpE2naqfY1pLh3ioQNVKHjJRzhgPi0ulTmzZ5mApyDwUY3ivsZAVlnT/XLruuVx7Rqzde/nRzOURwJqQc12VUnnNoVy8TW3ysT7tie1igTVge8dd3iAxGR3FmnbUWRDgdmmcSMOMS9DcrwelLBmVO4301eGVU2rXXKn2xvpc/weuUhAMYF88Df62QklIXijuIfbdXfu4V1OEPn5baeb8eE3Bb/3y/84j7scL9J1iMgh14rMf935WfqJo4ZE8nuAfvuIDDncSYXPe0lkxDmB7fhR5LnTnG357ZciPXaVRsWiqTVEFXQZItIzMLEJB+7prI4O8WACyP0fCaWFIht/dp73HiGSmeNMKkjb4OfSFXNbEFqP8gH2/HVNbfaI8xzJe928Gqk+HJjN/zLVSdvcO0zkx9elSSBvucj7N4jcs7PIf/cX+fTuGulU1QkGgqSkXAJ+D9AmtcZ8lYw1XhjcMVYqvn0u+PdfPuSQjqpyZ8DK7lpjfNMOhOsbyPfBtYLSQjBiMIGIAAaicNC0X3lJ7VmOVtr4zaa1PiNQ+eIreWRGHVRJUsnva75j2pR3jeHTX2lCED7ttNPcf2uwS5qhvKRAxh1zuGzNL5RpMzySfAhzaqzbGrK0c/MimfCPv5tj8MjjgfU5GOjTsmTr9sCxKykI+T0hq3ogcjR68543rsMI2+v9d5CKxLWD94TrwAdSLZAYJR4oPQlXP1T27zPCIcpDj3AI/YYfg+8/lB1NX2tKgFTLyPOd569e6ni0ovk9Bh0qskfgvGEM37QosFrstc59DKj6aCqtBTDU/nGhyOVfx7ZeSzxeuDXfBoys/RxllMlErz1rvDUtEK1H+fCD2Q65zLnPiDx/ushOxzgKyMCDar938gXB0uN71zqdPbXU0S9dMoAw62U2lUw8f1oNWwaznhA56I+OcUmx/AtngAzViY8S1FmPO8yadArVE6c8UttXEIp8aJmtAoWB/TYGq8S6/Y0LnAFd1RUGL15je5lVLJ7uvO+C9xwS0mmHmn0gvcHMpaE6naL8qPqi6Q1kfVU3QoHf493g7/AheD1IpJN4nX2P8BnTPv1GJtzxd9mytUDGnnCajAgYGElnEKSYMWPqvOSc8XLp2afKhIeelkeefUXGHrSPDBq+h/FoMbMmuJEWIFXD3xHYMTgCZu8EQDWUk3rQ98bb3pvPIvDqZ0KW2Z6OuTly3W3/kku3lMsll15mtpltYz94r/rJYt3WIJi0YJm5Zqa+/brceduNct3t98vgYftK5y5dTMAcd9xYkzrhb/ke3U/9TPc7qqtl7D67yZIF82XOvPkysbpaBg3d2Tm2j7xUa3v9n6NpGD6P9xhlhPuQvjSMISi0HoLnr8Jhf+tbFhzW70EqUMfIAfs7xIAVrPf9rfM6EzYmNyhx/QLpAXDUP0SWfe6osG/+n8jpz9ZW+5hI6IRo8GEiHfs560Ohhjx9osioC0SWY7Lk76odM+rYWxrXl6fEq/uuDjGIFYyJlOXG4oVbPTv42ANSL6tnOb6P4bH1r4kISMzUm0WO/Ht0w2wDIKWatZibEGivTqdTGo4lvecHjPap42uaUDHAX/W9SG6fmvcgAaIq8LvRF4oseN/JV3IC9/+/4N4Xz55Sc6HiWD7hfpFhNTOyhIIZ9T8D3WBPe0bkrSscif/sVx0Zk1VnFb+ZUpND1G1l4TXNX3rBgIGU6gUzMmRHBiNmNQwIY/7qEB3FS+c4BO1Xd4rsdrIz8+m+c2L2dfGHIs+cJNJ1R0cSZnAiJ33wNY4RdepfnUHwwhD7g0eEkkH8H7+NzTleUlIiS5culYEDB0pWVhyDHmSD9A4EqeMAhzgUbRLp0NdJAUXrr0BJL8TJK9Fu2+CQOjwJXQZH+O4qJygwYDNIhiOQzMIIwix+xfbxnQySkB+ID88bepVcCAH3mReUFxozbqK+o8KjfqU4x5gyz6xOIp13cF5GYdq00DkWXC+kMM3fljvknMkEJJ7t3bjQVTiM6sSMlfQY5wp/j/qhYgWfj2Km6L5bnVZDrXXtMryTWub62eusyH/84N4imxaInPmyyI5H1aiKU653ytbPD/Sd+PRfzhjDhO3XL9SewT821jk2x99Xo4YoVs1yentk5opct9RRTZlIPH2SQ1oUFALMfU6kYJXIqY+L7NGIhQv0MSFG/OaD+FK3b/xOZO6zIofdJHLInyK/96XA+Dn2VpEDr3JeI7380llOOv139VQ/uA4ePsi5BxgfLvvMOfaNGL9bV9rFj84DRa74VuS8t0W67ewEDW81DJj5uPO4y3Eix9wlcmigDfRn/w42MZKzVOLBTJb8/asXi7z35+SYMLXRTYc+IrueILL7qc6/CcZKPAYcUDv1QufCp05wiAeDLEThxIdqDGPMcPx48/ci/9rJKfvyl9n6JUbSUw+MEnloX+e5YtXsYOnWC8gQvw93nLzVNahT4JtHnZnity/UpNRCYQdyzynOTZe/WpKKbRuda4igSXCDxPYcFp14AFU1/JJ7LH4PQKB00zcRVrrV3/F9qswxMzOlppucc9TQ8xGV6GkZD2kHEKFEIshPU+0QD5AVWBTRfH+2Y4I0pc2BexszJISEIAhBZOVmJi0EVwhel6EOKUYFVbIUIm0SEagBBGCDgFKg2xfv50BWSS9tD6Rdv3tR5P0/i7xxucgGj0rqB2MZ++mffe/0qxoFVc/TohnO4+DDa39O7z2diQlg7IOkeaFjAgqzBj8UTFRL7hXQsb/IgX8Q2ets59+z/+cYySddUHO/NxRIY+q5IV7EA+31EUu57Zq5NWZThU4YN/4UOY0VCxZNryHfxA68gI2M1k0+ALM8bgRKy/zBlxsSUgFGXeg8DjvDCbzIjswo/HnMY+8RuXGtyMEBpks/ka8eSvx268JuWtam27/04xrTkhISJR/MdF/8tTOQsg+/myky/n/OjGh0IHeLg13LyvTmw4nObO/dP9V0N/XP7LS0zJiz8p0B/rVLnZk2RO2xw0X+d1zwZzPbe/tqkQdGOr+/a5DIKxfVDJwKnRHynZAlBnvq4ZlhcWMy6PN6KFC6qmVxxp2fJLBflM8C/C8qN8dqZNbA5Q2SHHv1jKi5NxK8672EAqRCK4UItMz6NdgR9CGjBN14ehPUF2yTDqyoMarYJJp8uO3pfWpCoMrFPVfaXwHvEim9Tb8EfDIBLwezcz4LJZR7iPOi51jJHyXPmnqLBZA/PpttU9UVFTMeEggpIgULgWT73rk6oHB61sxhYhIOa79z7llUOkq3FQRcZsqQaogDY+LKwCx8SJgW7/v93vFzcC2/cmHNuWR/tLpQK2m89ynKCqmbc153yLEhHylO2ufxsSI/BlTdhgQTHI4L9xap9HigvT62rhT56mFHCYEY+lG4PqC+pzjkTdGuqzPWgWi+xGj47B7nEYUOUMYbL0lOMCz5UCAhaqDWAR92yMyT2Y26tyErh93gPP/iQWcw5/3IiQCTFowed/jRgR4oMx8NDrqJgMrUSj5gzLiwFXhSGAD0wiXQo8SQW2RWftYkx6XuZdmYIiFVWssOeL8O3DBmnZH5yYe3woUUCG5wPotyX6qKADcY+UvAoP6fvR3PCTc3QYAyxe8n1TaUquGr00BnhsngxOxIV65lIIvUqVZnb8kkHyZYVDqqVyRzaVTlw0M+TK642lE91FAaCe5Kt2HIBwFOfSiQDWR9mpSh+pEi04GJ2XNDrbnB/UWwhvigxCSLfJQV1xAcVZE4Bn4vlKa8CJyGFFQ47yMN5BKVFOf696e2UE3Yj3i2n5SOBiSOf9vOgb4vJZEVLC94Ly32IUkpac42YBJ9+EDnniIFCL5/2QmEET0HnuCn2PlY5/HjCU5PDo4J6cFwqSVUuJMedvaFVOCMv9d4RSBvEG39TC+4h/f7XU16ET8I4ynQ4woxrq8KEA9UrWV/462IVOWDCRkkkBQMqXmNL4o1AaMv9yHmZy/67+c8fnJ33dsFrPjaaRjH9XnuG852MRbPfEwaE5Z8KLrt6ARvBmgMjLB0DJxg1G+CLzxm2QwUlFGRpuHEEni4GQmKipHnOYEI9kzdelLIR6Cag+0bfkbN72lXzPaQlmFQYq0G6ua5AE9/rrZ/gEEYwgK8qSdmHYAcrcJbZqugiojAS6rn7Mki459yBnltFQxxAD++VjOQQR6YPZ73lsi1Sx03uXcgDNfUjNkhbZ9VbeE4R4KSjyUf11SOJBpaXUSKpS5l25pu4FxBVCEhSvQgdrF8phIUgpaSDC+U2DD4q58B0qPEB0+Pzu5UxUk2NJAQ9CHtLvlI8KzMTTfhz+jrHG/vDF/Bdc1kg2uLe5cACknnmOn9zTgRSoniHLkKVozbb44zM+vsQHllag151TLtaDDvC8zOMYJzDttkOPuMmvLrF53JE9dEKBUWdfKLB5znXm+YYt/LnfGOlOubgbL9wWOiz/pP/E9NWS4pKyYWgM7DsTYUwzdCGud33zgEAPj9QcmEqq763fHAOyHj+ob4ojC9cEbNvci9rmq7N+XiVZG4HjCeUn4c7/gF2Zz6F+c58YFxn2VFANWRkNNGgiUfoYIUFwMlXqQ2GKT8fgIGCE1zfPt8cOmYF6506PGOJAKYC03XTI/yoSkhBiACeq+9nMFQFRsIEATirJdFdgh4QcLtP3X9Ck3ZHH6jw8xD+T3Ma4NErl0icv47ziDKRX7Ko45kyyB0TKAMmBQOg52WK4973NlGFCUd0LTkT/fVXUXXk3Pl+aWfilzwfuSeAoDtZvbHDBvzaoyI2YuNfKnBzcxc6wD2H2KoErqW5zEbjFRi64UhFQHPAsoSs29mSwxASLt8Loikomjg01RDMkEwVIWFgRm4wTuBygcDPOfeS7ZQeiBboWAawfV0rjH6K9BvAXA/sZ2RUmDxkA+TqttUQ+iVYOp2xZp60WPYrotUMaRD4I68zSEMGMDpk3HAVTX+CZNK8CgveCkgQUxkNL3sBdtz2lMOkdHjGC7l4gXrKe10rDMxm3KDyA+vOq/HYx4lgGNsp/rHLZv/seGVj3j9Hjo2U1E5+iKR388WOec1Rz1jsvqvnUVeu0xk4sFOp20wyOkvU2tSrH+34gun3UMs4LxOuVHkgRGO8s3EUK+B4Wc6ispB17jNCRsDrbfUNlzqhRkACsH3gbVquPBDNYiBkHxyp9PgSokAJWN+oJp8+aDTXZULuS4M2g+qbcjNMxh4Uy3IlLiijXGuTQ2hoE0y5ODXLzkXczgwoBC8kEYJXgxeukIs+0Yq5eVzRXY/JfTf+wdlBh9d0I2bgcDGIIcXBIWJJkNec5tKvuwf5k3ywCgnSODk2L2qEuD3/nbkocCgzrnFf7PwPcc87AcEkhbRB1wp6entTMnoxo0bpVu3bqHLR8tLA7PNLEfBqeB5jkg5qkUdU2zV6Y7PY2PAVwPSu1DCEPtnZPdxJFWO2Zowg3RVWvjPrKx29oXgX4y3oU1yVY+KQKqqso2zTfr9UiZStD0xjnxmi3wmKYn6nJ9YUJXqfNf2IpH0KOcNb1N5haNSSGbNOTHXAce9XKRwq0hGW4dQ4udIbx9c4s91WFIs1dUpUlaaIhs3r5E2bdpIBvf97p7UBuZQet8w8/7PviIH/9Hxd1BhgYeD4Hba06HbB+isHCLz9lXOuEP1SyyABDH2qfLLBGhIIJVSl2BO07OG6tkTlPKtw7jNtXuqJ7WBKkolEa0bCtc647JOMPAIQlRCgb4rZ78i8viRzv7T3yla0zHSNMQdwLk64taaNDsTHQy+jdxY05IPL2iZy8xV5W7UDco5Q4Fg3n9/h40agx4qQ4gbEgVA69iZdVCzXl8o8ydf789Z+wM0XQopEWP2488n+sFNsMOBzrYikfKcmU77ns7MI2VHkWt+qdtFy3ZSwktfFVVT9r6k9vdjsMJ1Tx6Ucj9NubBfoXqVxIqdjg6Qjw8cNUXJmc5AKSGG6Mx/Q1LPeF769u0rq1atkmXLltVu+MWPzgCRj/k3n4FAsdVTLhkvUCmMhJ7iDFyQue11MH9WpYhszw94AKiCyXbIhJaGtmd27Ms7e5G/ydnXgrT6HfNowNDJNkLuCzzHOX+zE2wLUmsbROtzXDkO2+pxfmIBcjoEOzVfJC+CesTxVU8JY06hrxKM88dnbSl3iAHeGMgakwM1MgL8A6R/UVyK1kt2drb079/fEJAgcM+Oe9KZbbMYnN+4yZITkUq5AWWzpkqqc+xpEz6T+/yrQApm1+Pr3rNDVd7GUD40bVxfDNhP5A8/Oj03SG8zJnN8wqlwCjo2Mx6TBid1reW4oUCKi3JocMIDInudU3vMbgIdvS358AJGyEwdYxBS/vH3Rz5JlH1CPgAz+HAtdOkPQkDHwDrm5vqfeG2YpWuXRALfFU9tOoSLbeXiNV33AmVx8VZvhAJeGcgHgNBoea8XVOlAPlb7yEe8fRP8gCgy66IJGLMw7xLeDATqTUH1efRwaX/aUzJ06KFSXl7uyZ3+1TPrYnD3VDSg6pz/bp16MwShKM9Js9T3c8p6O+cPNYnPgxxRbkc6YGgIedeL5/4skrfYuf5pMlVXUG3x4T+cZlKaflRQgvnO/4mkpItc8K5ItufemfQ35zgf9U+RgTVtyesMGisteEdk70tFdk/yIl1cJ8+e66gZl33qlHeTUmF9Hy/mPCPyxX1OxRGeJ39AnvuFyOf/dq5b+gW9dVWg+ZaInPpEzUJvL53tVLkcdoOkDtlf0tLSwjd6gwjQ8wfjKWZ57aLJmOdPGYeC31cWK+hxwSyfSd2wejTL0rQL68pwPSehT0Utgug1nCYKbPcOB4RPf4cDirMhH6+GJx9MrN660plo4K0JRTyaCCz58OOI25wbnsAYLQDsdpLT7ZR8f6Sbd8hYR1qmlwKBFcXC7xnAsEhulFlOtM6o/jLbRIKmaDBy1mjQJmSxSqzRAKEzzZ3ynHRUqFk1EiNNzNQBHsrvURdwLlk7AimSlTq95IN9BaRmMGCRk33xTEk9+xVJ5VqY+7STP2X2CYFBDWMQpvcBzd34mz1OFGmfgKZ4WZ5Zbb0+J0ukgy8vP+yE2P42O1tk5UqRgiUiWSF6OcQCgsM7v3P6Fyx6W6RorVMBpgPhD8+JbFvpKHOdffvcPldk8UqRvJ9FskKkyOLFyk+c7+ox1DkuyUT3QSLFGxxl7OXTnWDBJIEyUr2vuaZn/MVJjR1+rUhOiPt9h9EiU1aKLHpHRO4S+fnVGrXtRwykezuBcelUR93a+UiR9BhUKhQRrt26kIi6gnue/aciJ5o/KxIgAKhXjLdMSjxdYJMCFCxa56NE+hXlxsAuJ4q8c42TOqMVvbdaEdAniTW9qCjE+4fProkSD2DJhx/IX9E6ASqQzGg5TMOrSJ1MkSqR2/AVYHj0kg8MZ3RQ1bJRzG0XflDjfIZ98x4kWmRYXveX2SYSXKzMtLjA1eldnwHDC8gG5cf4Lva5NPR7dL+peGHfE6V8AM4VvVkICARF1CqCpK6oOfICh0S+fI5TlkvbfY6x1thTyXPywzUDEeSTKh/O6+6N2IEx0dBZnhK/uuCbR5xjTDoAtQVnPSkGcs+kgLR/zohza/+tyv/aU6Y+oOeJLkGg6/0kE8xqSR2i3GilGM+5ljAOMha8/QeHeEDqmZmGm+UrUf/0Hod4GMNnmdMr4+g7HLO7Xpf0hGjK4D6q73jFsaXkmbGBCViyyYde/6Y6KgHpv/qiXRdnfKIaE/WDa4T+HZigUShJx2izMiqE8AA2Ydhql/qCk3z9SuemiATtBohB1YtP7nKIB7MXTJUM0F8/UsNkHz9C5O4hTqnsE0eK3L9XTUBWGTLRwHuBux32zICdSMmRNQpobBZO3WGfIGAoQbjyE0k+GER2C5hltbTQpFzWO/vMjc0gQ5kwhAulA+LBbOvI2x153D8D4jNJKTTm2hOJhp7vcB1po4GOkNrbgSD5q7uc55/f61RSYZojqFIGHqpLppqomSnXF5w//COk+XTxw2RDy1UhF1xLXFuYOrmH/7OPk9ZECaWMNNzMFIWCHD/46r815Jj9wOPxwV8cUyHwp7RaMhrS95GMlEt9sfupNeMXDSPpycREiZQwxANllusq3OSuCcEqHw0FrYShRTkVDQQ5mLWW4JpZUTunkx8z8WPudDoKasMv1jRh9kMliP47lkqPugLSwTo3zNQaUrojiENAaBH/7jWB9UoC5tpE4IArnJw3pb44zLXvCI3KdHbDNpzxgrM4FmC23hRk14aCmutw1dcFDIQQN5rNjTjfCaR01aXDJrN+derjmQqVt1fyQYrSbw6OFzTFAqTZGuo6hnDh86LEm++kZwiLpnnJFMbzaAZPlgag8k7TLTTm4hol8Hwz0Xltz7Pq56NobmjIctv69PhIFnY+VuTtDGetLUBnasYmUsD0raEBZkOR7HrCko+GvGlY6p1yOQgFZiNa3GIMYvbHrJs0AwMWMjHSqjY5O/QGZ00Z0i4Yt+ZNciT/ZCOWNUmSAXwfkA9K9ADrPCRC+QCUC2v10UP71fhOdvUdTypNxgeWXG9tcJWPpc41GU/QpiJjfmAF6F9NqCEOh17vqB4YetXcS+AMha47Of11mOFzL1CpVRew7Uo+/O28kwmuKa8SiuGbEnjK1kmPROoO6oW3eo4ZLdI6EruqdlTnHffvJp3XT57ykeBVqrlWSPPhLVNCXJ8eH8lC245O1RHFC8f+q6ZnCpOqZgabdmkoMAjj+tfUy/Ivazr+afktg4hKqNNvE1mH8tBOZO+AQx8VAqPmbyJ4JloCvJ3+WN2SCqFEggHbmGirnRw6lSqxuP1bC4zKkxIo7/Sts6PAu8SKpygTXtAfB0LNImHeVt1cuyfSdyAQKElrhRvUmd1rhRbm37oCGZoyeO6hgVEqfJINCAe+MCYasRJpJiLacZY245Canrs70jvKJCtQh1u9uKWCpoWAlGyiunOS3mbpiQdHOmZ0hS6015SUD8ACp3SEbsyVfhMASz4aI/VCKS8yLKCxjNcIR5dSPA/aa4TW4dFqwFsa6AdC5QleAWTERM/sCHq471nRmOomlgVvCoaypgLSTtoaOpTvg06pLAHOUusY37z47vnwqgZeCJr2QUD2D7TSD4cBB9akKesKvCVg6Njm6cnhutcFE7WjMhj3hMiln4jk9JBWB8ZCTYFixK0vSIFPPr9mIkiaS3vDaKsBXZiyKaFN8w/dzX8PmhNU+UB2Jo9LHTbSmRf4OHgdQEJYaKm1AYMehGCfGFsJ14eEIFfWp5dFS0WkipcfJtcsOf/ZvTUtwOm/gNrAdRtuVjbmLyI3rnMIQSRoDwSzblIcq7t64aZcjpdmC4zOV86LfrxaE1QpxsCsLdv94FqkFTldiyPh9d86hEOb2XH90q4eZZrWB9wHrcnv1YCw5KMhwWzSsOgUx8eBqTHUaqwsJsQATlMkqiksLJpSxcssjxeGMlJtna2ln5DnSKWfsagQpN4o06XXgsrf8YA+CPhFuI90ZdTmCBS5aK20WxtIO+0f8DiwTL3ffLpwishjRzjl3CzlwNIOoUAjQ4g0VYZMdlhQkMoo1LalHye2zYBFLVjy0dA4+1WRK+Y6BtJw0hk9Qf68UuSo2xt66ywsfBUvS2sP2JiBmSlqagX5G3/Sdy/WThHUFXgZVO6OJ/Xy7Qsijx/lLNgF8PZEa9pn0TzVD9LYNBx7++oadWz2U05PFVXmaOyofXz80BbkpL5pBKkLu0E8dAmIxvYKtWBY8tHQYE2EWNzTtD5uTS52i+ahfMwOqB50AD78Lw4JYYmBhw90WtfTu2Oop3tsfaB9LmI1nbISMOXR9NSgM2VGoAmgRcsDFSmsR0NVFOebFNuGn53yfIzkNG87+FrnvVQH+VN3qCXGE5QictDVzmtqOqcqCzKdyO7OFrVgyYeFhUV08sHgzWxQV3um6ooFzlyVI8WRwzHyJsq8S+dOsCxG3wfNuKi06TNK5PKvRf683FkfyKJlgutvv8ud59NuEXn9Mqd6DfLLgmr7XOak7lDq6IMRSvWARGsPIchuSqAnDQSGaqPWaOptINg+HxYWFrWh6hyy9cRDnM672luBXin993OeH/UP59/MELvvnNhtoHU9ygoG7U2/iHTbMfx7KbtULwrN4xK9LRZNEwdc6Zx3+scAPHS6ICh9iiDHqHUzbnMIM+RkwXs1ZmTvquW0s6fyUFuUW79HUmGVDwsLi9qgmRUrDANmjhAPJG46Kp41uSYlSDM2+tAkI9ibNZEClUhvXxXeOAgIQOT5u+2SuLSPRdMHZINeQArK81FEFFotyGJr9PLAoGrSLdVOsy6Isxfefj825ZJUWOXDwsKiNiAXF051WoJvWeysxRKtiiUZIJg8erjj+2BlYZYd8IOF6nT9E0qnW0APBIs4gKLBKtjte9Re4JPF5058yKnIomEe1wrGUlZTDrXQHQbTz/7tpBHVc2SRFKRUV9e1iD4ylixZIpMnT5ZBgwaZ55dccol07BjddV5QUCC5ubmSn58vHTokYIlyCwuL5g0k8hfPrCEj3v4vDF9vXSEy52mRnN4iV35nG8ZZ1B2oa5TnUu1FTxqLuBBP/E6a8jF+/HiZPXu2eQ75uPjii2XSpEAXOQsLC4t4FtNCWv94gsh7f3LUGMrQaTfOYnUQD4yCtM23xMOiPuCaooOsRdKRFPIB2fAC9WPatEAjIgsLC4t4wcJ0NAxjMUZWdF3wrtNqe+13zu+PukNkp0BnYAsLiyaPpCRHIRqdOwevR8K/58yZk4yvs7CwaA0elEOudRZTY6G4/JU1xGPvS0T2vayxt9DCwqKxlY+tW7eGfH3LlsBiaR6UlpaaH2/OyMLCwiLsooNX7ec0iaoocaod+gVWwLWwsGg2aNBql1Ck5I477pBbb7211uuWhFhYWIRGhkjXvWr+WRhopW1hYdGo0LgdSx1LUsgHVS1+lYN/h6p2uf766+Xqq6+uWTpi9WrZddddpV+/fsnYNAsLCwsLC4skorCw0FS9NHipLYZTb7UL6NSpkyxdujRquW1VVZWsWbNGcnJyJCXBa5vAyiA1K1eubPFlvK1pX1vb/tp9bbloTftr97XlAToB8ejdu7e0idJvJynKB9UtfjIyatSomPp8sMF9+yZ3GXlOfku+AFrrvra2/bX72nLRmvbX7mvLQjTFI+meD3p6XHfddTJ69GiZOXOm7fFhYWFhYWFhkVzygfoxYcIE83zcuHHJ+hoLCwsLCwuLZoZWtQhCZmam3HzzzeaxpaM17Wtr21+7ry0XrWl/7b62biRtbRcLCwsLCwsLC2ntyoeFhYWFhYVF48OSDwsLCwsLC4uW2+E0FiSzz4eFhYWFhYVFC+3zUR9APGx3UwsLCwsLi+YJmqlF69fV5MgHigdo6Z3gLCwsGgcVVRXy5ZovZVi3YZKbGVtDJAsLi9g7uWocb1bkQ1MtraETnIWFRcPj7SVvy/Uzr5dTh54qt+x/S2NvjkUzxLrt62TGihly0pCTJDs9u7E3p8khFstEkyMfFhYWFsnEgi0LzOPS/KWNvSkWzRT/+fY/8vqi1yUjNUPG7WibaNYFttrFwsKiVWFl4UrzuLF4Y2NvikUzxeptq83jxiJ7DdUVlnxYWFi0KqwqXGUeNxVvMu58C4t4wbUDCssLG3tTmi2abdqlsrJSysvLG3szLCxiQnp6uqSmpjb2ZrR6QDZU+SiuKJZt5dskJyO6Oc7CwovNxZvN47aybY29Kc0Wac1x8Fi3bp1s3bq1sTfFwiIudOzYUXr27Gn71zQi8krzpKiiyP03qRdLPiziQVllmRSUFZjnkFeLVkI+lHh0795dsrOz7UBu0SwIc1FRkWzYsMH8u1evXo29Sa0WqnooyNkPyh3UaNtj0XxVD1BYZtMurYJ8kGpR4tGlS5fG3hwLi5jRtm1b8wgB4fq1KZjG9XsoNhQ5hNDCIlZsLqkhHzbt0koMp+rxQPGwsGiqKK0sDTkj0uvWepWajvKhxkELi1jhvWZs2qWVkA+FTbVYNFUUlRfJkq1LZEXBCimpKAn6nb1um47ykZbiiL5W+QidJvxk1SdywfsXyPi3xkt+aX5jb1KTJR+JSLt8tPIjOe+982RlQTAxbuloluTDonmA4MtM0x+EWzLxWF6wXKqqq1xjmkXTVD526bKLebTKR+1r+Mx3zpTfTf+dzFo/S37e8rMhIhahPR+JUD5e+PkFmbNhjkxbMU1aEyz5aATMmTNHrrvuunp/zrRp02TkyJHyyCOP1Pp8Xm/sbc0ryZOC0gLZUrIl7LaGA+/je3mcPHmy+XueL1myRJoivpn1jYweNdolHsD73KJpYNU2R/nYq/te5tEqH8H4cfOP8sPmHySjTYYM6TjEvPbthm8be7OaFLyElRRrfScZywuW1yI1rQFt4g1Ed955p/kZP358xHJX3ssPIGDocwuRiRMnRgzCoY4r6sGabWukvKrGLzB27Fg5/fTTg95HoAaJOt512VZFWVWZ208h1LaGwxFHHGEeJ0yYIJdccomMGzdOOnfuLJdeemnc2x/P9tYVHHPOy/x58yWtTZpbullZXZnw77KoO7iHlGyM6D7CPFrlIxhMFMDuXXeXy/e83Dz/dqMlH+EMp/VNvZRWlppxPdTntnTERT6YfV577bXmZ/To0TJmzJiIQYuZLnlugsagQbaczdvvgSDI8fQDovbyyy/Xep1BEiWBn0ggUI8YMaJRt1WhRIkbLFYVAGILIB1esE/+1+JFtO2tKzjmewzfwzxPT003BARY8tG0oIN8+/T2MrTTULfPh+1yWgMdXzpldZLh3Yab54u2LrJVHR74FYpQqZdYU80rC1ZKtTjXn1U+woCZ9B133BE04PJaOBkc4pGXl2d+pk6daoJY0noolBc1yk9dBi2COAoASsCkSZNq/Z7ZfrhlwEFD+ifquq2AY1NeWe4+j1Wa5BoLp3CgttUHkba3vlCikZqSKm1SnNvKpl2apt+jb05f6dq2q6vKbS/f3shb1jTJR/fs7tK7XW9zHX+/6fvG3rQmA79a5idmby1+S0Y/N9o8xppyaY3KR8x9Pph5Pvroo7Xka+TwcEgW4fCCwWOf5/eRxsDXZ34d93LKEDaUIwLsxRdfbBQib7CfNWuWbNniSJ8EfRQj/ubFt16UXv16yZoVa+S35/62QZSkum4rvxuwwwD55sdv5Ijjj5B+O/SLiTRBZLmuwu0b3+H9fr6L986cOdMQC17DJ6JKG58H8YU4hdvecJ/DZ6jX5aGHH5JJ0ydJ/w79JTM1Myr54Mf7WqKv99PfPl26ZHWRJ456wlbQ1MHv0S+nn7lvc9JzzNocG4o3GJ/D0z8+LX874G8uMWnNaZdOmZ3M4/Duw2XN0jXy3cbvZL/e+zXy1jUNKEnAF0Nq2bu+CxOtJ354wjz/eu3Xcvzg412FAwL3q4G/CrpnlxUsc5+3thRgXE3GUDsUL730khnAwxEMgoj6DxjUw6VeSktLzY+ioMBpW9vSwbFkJk+g06DKIz+DBw92UwwEUILgAy8+4AazcUeNkxnTZzQIuavLthLwi8uLZffDd5fTxpwmj736mHRpm7imcPo9s2fPNv+GUJCugSixTUo4AI+Qi0jbG+5zeB3CVZ5VbpQbZjiZbcOQj6ra5CMZysfc9XPNUvD8rN2+Vnq3753w72jxykf7vuaxa3ZXKcwvlE1Fm+Te2fcas+Wbi9+U3+z+mwbdrgVbFsgPm36QU4aeUicyCSG9aMpFMqrnKPnDyD/Ua1u2lgYmlVnOpJLUy3tL37O+jwBQvFUpYzLiT0lxDfGaf9XkW768Rb5Z940ZB/fpVTNZ9iofHHvGkdQ2raMBYZ06nCqx0EE7FBjgNThCOjARLl68OKTMfuutt0pd0TatrVEgGgLrtq8zsiTfuUPuDuYxHhC8OQZq4OS4EBy9M3o/CH577bVX0CwaVQHvQn09EMnYVvWbqNm074C+MuWNKXL+hedH/U4lp5CCUL4VXkdp43t49PpQILiAzrfe7rdcg6p2hNrecJ/D3+nnHHn8kYZ8RFIyXOWjTaq0adMmiJAkEpQ/KphJtQTygTw9f/N8+dPoP7kpq2T2+CDtArq37W5I3E9bfjJBw/uehsTNX9xsvn9g7kAZ0SN+v9aPm36UeZvmycK8hXLFXleYa5Brj8/cufPOkpGaEXfapWOWM3bv2X1P8zhv4zxDppN5fpqT6pGVmiU92/U0RMNrOH190evuc28l1bJ8R+FYUbgiLPmoqq4yaw+1FuWtTuRDZ7eRZt7eAKISOD9+9eP666+Xq6++Okj56NevX8zbwkwh3tRHXcGNl5WWZQxCyO/xzlKYgXtTFwQ+fzrDC01t+WfQDWFkrOu2+s2mOlgxO4vFI4PqwHd4VTbvNunrXFteIhQvEdPt1c/B7DVk9BC58KIL3ffotap+m0hkQs8R+5vMtEsQ+dj4vRy1w1HS3HHnzDvNrO+4QcfJbl13S+rkAShhQ/nwB4yGJh/cEyq9kxaqC/nQVElJZYksL1xu1qp5a8lb8pfP/2JUHL8awnX88sKXZd9e+xrCE/RZpc5ndc50lI8dO+1oJlkEWIja4I6DpTVDTaEoGKTtvIZTjPXvLn3Xfa8qH4yF+hyVzYtlnrSLfn5rIR9x01hkacgHAzMDeKjSRYJEqEqYUP6QzMxM6dChQ9BPUwUXl4JgWl8QSMNVkngNn9OnTw96fd7ceXLaaadFLR9NZFlprNuqv1eD6U/f/yRHn3S0Cc4E42jbpKZQf3mv9++83+P9/njg315mNMip70x5x30PigkDtRKLWJSPbfnbkpZ24ZrzGv9aggmQoKZSv5KDZIFZpTelgPIBVCb3+kIaCvgFVMZnkbu6QMkHWLhloXn8cs2Xzr/znH97MXXFVPnH1/+Qaz6+ptaEwGs4Belt0mW3Lrsltd/Ha7+8Jme9c1ad97+xyEf7jPbmuaZdPlzxobme1S9DZ1hiBn+jFS34ixQFZU4PJNCnfZ+gz28NiIt8kGphpqjEA+lf1Q9v5Qu/91YWMMATvBrKo5AMEIR0Bgy8y3JHA/tP2gmfjLf/BgGWY6LNtADeGNJZ/Jtjzc8tf79FnnjgCfngzQ/knr/dI/f97z7zd3wWn+n9XDVdakpLfTcApSaWn/psK+cdgvrGq2+YbX3yuSelW+duMv+7+eZ68X9uKKCqcX35m4x5VQ++h9/zO35GjRpV63jwuio4XJvhthe15Z3X3jHHd/hew8138UOaacrUKTXXQBjywXv/8Zd/mOf33n2vvP7q60lRPpC+uQbV9EqqwntNNkes3rbafe4dmBMNguzWEofkaHAINcNcu21txGNKiiiRQZjvq6/h0Es+6EjqJaahAjrXkRKT+Vvmhz5GAfLhbch235z7TCvwROPp+U+btBHekqYOPUdds7q65EMNp68vdu77cTuOc+9RUi9eUu1VPlYUrHA+q21XY4JubRUvMaddGLz9pY4EI5W7CXT0/mAg53WCAUGI53gHQpVqNid4m3up8ShWqNnRD46dP10AcfOnNg46/CAZsvcQk/I58oQjJUVSzKya4On33eh3hSorrU8/g1i3Vb9/Ud4iOfiYg2VAhwGSX5Yvuw7fVT747ANTvhcLuI7iPab+48G//embUNt78GEHyy95v5h/t2vXzjWbAmalmq8NF5R4/4CRA+SKv1xhvEC44BnYq6qqzDFPVEWKplwO73e4fLb6MzPoMWsnr99csbqwhnwkc+aLaqQ+pNzMXPPovRY7ZnY09zTvWV+03p2JerEkf4nc8NkN0qtdL/lg3AcJ7T1Sn26rXvKxIG+BIRBqrg31mZBWxeu/vO4qG1xPFdUVtcjHWbucZVqs89n/N+P/5LLhl8nv9vydJAIopKRzgPpumjKUHASlXcq2mftcSSmpUIgUKhrXtNd46n2+LJByYYxUQ75VPkKAQMMB9v7Qw0MBufAGDAZ+/k3ASmZ/hYZOuagTGeWjofo4aNAj94qkj4TnTQE1NZi+HoGBnqZbmLM0kCNLJiJllSxi6ScY3n9H8nyE6vPBeUrkNTJrnUM+Rvca7XojdBbbXOFNcxD0k51yYUaqRvFu2d3c3x/Y50DXC+Jf+VaxdKsTJJnJJkpxomIpkcoHlTPedBz77e2xw/Wo6gjAo6C/15RLdlp2UEk5gfH5Y5+Xc3c91/z7kXmPJKzfEIRO7x0vKYqmlum90GjKR9sa5QPPhzd9RhWMElvUvPXb14ckH8sDZtMdOuxglBTv57cGtG7rchzQGxS2CwEhwDZUwy8d6OicifoBEvHd7ANMm7LYRILBRFUWcsa6zcwskRpZ9bUpdUz0Ds7+VEkQ+QiTRmFfvaW23oqARJEPyKYSjVE9RskeXfdoEb4Pr8EzmcqHphNQOFSJ6ta2hnwc1OcgtwomnOlUiRKksq4zVPo9TPhmgivFe8mHNzDVlXzwGR+v+jjo997PhVgRJCEXBEh8Bx+u/DCk38MLKmauGXWNGf+4phNlzPV6UlACYhkXrphxhVww5QJXMWlI6Hk35CM9kHYpK3TPJ9cX5FaJLdf0uqJ1QX+vY8Xy/OW1lY9WlHax5CPOAMVNyMwgXt9HQshHSmLJB4MQN82a7TXSLzcGRqlYy0QZsJhJeQmMHivIEoGY44XUzbZDRuoz0CZb+fDvt/d3DLqhyIT3NYgpwU0VMiViyOt+p3s8oLIFNYnmYsyUhnUbZl6nP0RzAJJ0qNmqV/lI5iJvqnx4AyvBt116O6PM7d97fzfvHi6wehWRus5Qn5r/lDz707PyzPxnaqVd+Ewl7RyLWL/DSz7AO0tqTNP6WYqfNv9kHnfqtJOcOPjEoGof/Rw15PrBdd2vg3OMqKpJBNQg627fFmf7wgHVVFOk+tiQ2FTinBPuww4ZHWqRD1JyQJUPyIdX+WA80GtxmU27WJhyt/xlxqcQbqZaWlVaQz4Cpb3x+D7qA83DGuUjkMKgrK6+0NQNZEEHPQYgBt9YGTgzJwL21rKttQK29hdg0GJWSZkepX38W1vU6yzKOwg3NLQNvPdYu//2yeuhSJkqIsawK86s2ttineNh1uUpzauzXE/pJKCRFN/Dwl9g8dbFTUpF0kqLv3/1d/f+4Bq5+IOL5ZKpl9QaXBvKcOr2r8isMb1Dhh894lHTKZa+Ftp8LFzFi/f1upIP0gxAUx9eM6K2eufx5DdOltPfOj2m60VJw+DcwUGlnxArP/nQ1MYuXXaRE4c45OOLNV8YZSiS8qEYkDPAVXASqXwwsfJuXzigdmjlSENXJoWtdinf5hqHe7TrEVRJZdIuvnSikszlIdIuVvlo4kj0QlDMKLnpCcbhCIXO5pErXeWjjuu7JCrtUt/vVpKgZbBeUhOrsqKf4VU+9DVVObzAA6IBAPUD4oHSwsDXWJUb6k8JRS5qkY8QqRev30MlfW+vD/czquumWKEavPrLq+b5mTuf6cq+rLvBQNzUjHr07XhpwUsyaaFjMv901afmuuK6oE23guvOSzrVD8T7Lpt2mdw98+6EbZOW82qli2KPbnuYHxAt7RJkjq2jcqdSO+ZNo4h5VEf9XCZCEDYClzctEwocK+4f4G1/zr23T899apOPQHXLLp13MTNu1B7Owy9bf6lRh3zHyIuEKx8B8nFQ34PchmmRANkOdT4aApqmdsmHN+1SFKx8eNMuSj50TOB8bCjaYJRzXuO6U+XDej6aKNLTnWBWVJRYxcFLOEItMkXw0KDEbB4CwMyWwJJs46fXTwD54PsJcDqjTpTXQWf/+lqsn61/R1BV1Ug/A6IRCnqjMWP3dges7/4kRPmIYDgN9W9AVYt3cPE+5xrR/aouqzazJL2OYwHfh4oAThpyUlATKk29eAN6Y4PzqQFiyjKnTNlbnundVgZa7h+OlSp6DNYEoM9Xfy7P/fxcwjwz/s6doeCSjxAzau5Br0pTF/LB2KLqDoQBkqPBRgk5//Z2vdRyzGheFsYjb+dMKqD65PQJ8tIwlmjaBeUD0JAMcM5iUj46DIhpu2IB+8pMH7VQVRhv6W8k5Qh4z0dDgG2FRLO9+IVyMmqqXZQk0vXUm3bhdT3+QzoOcfd7cb5zj0D+GNN1TNQW660Bdepw2lhITU01pbsbNjg3cHZ2dkLKGPO350tVuTPIFVYXSm6qU4qnYFbP75EGy0oD3o+qDMNct27fGiTlJqW/SJkT8MpLy6WqTZWkVqaaAF+4vVDaZTjSqh/8noEddh7uGJWUlEhVpbPf24q3SUplipQUl0iVVElJeYmUZJXEvG1g67atJiVVXOIcLyl3viMUslOy3XQBwYcgDalMyQje1rIKp6152/T4WtnHCoKbd20h9r2ouMhNm5SVlJnXdBvZt7Sq4NumuMzZX2NCDuxvdXm1eY3jaQjktkrJ25wn0zZMkz3K9oi5i+ELP79gZsl4Zq4eWdMJWFtfv7/sfZm7YW5c+8zs7bmfnjNriWjATRQwwKosznNkcsqCFd4eGRo8GLAh1gRdZoQafCFebKu3KiXRyocXmnaBGKA8aE4fsF1echzKv0Pw5rrRUl4/vKQCfLL6E/MI8RraaajMXDfTfI/XW4Iv4IA+B8S0EJy35BpDskr/OvNGZWG/ONZDOw41rw3qOMgYVAnqej9GIh/9c/q7bcLrC/VsQGhGdh/pHiMIrAb2SMpHQ6dddHupZmECqmkXlFNNQ7nKR8DMrOeS8YPzw70MGdkemORqx1hjhA60UGgtLdabFfkAPXs6zFIJSCKAIcjN20uKlLUrCwrYKCMMXqb8LFBdzA1iftIKI96s9QUDMAMS25O2Nc0d5JCnizOKw96kDNqQD7Yt3Bo05Jt1ZlmSUWKIQ1CXybwa70KkbVPo9vCaUYvaVsqW1NDrqvB7Bnm+s6CiwCgnpZmlbp5awcCJssBMIhkLLrnHN+DVIHCmbHEMo5AGndFw7jmeobZRrw8GpIosh4zxb17nmHCM+fcnmz+Rtze+LcNXDJfTdqrpUBsJkARw5Ygra11nuu4GakI86268vOBlefT7R802/XW/v0oi4Vdhbv/6dqP26PEjRUQQJy2g6Q16arD9BB4UBW/HUY5/IslHJOWDaxGzpfqedu2ya9hA51c+uN9OefMUs1/vnPJOyNWPtV+MQqtMIF8abPzKh5+w+OGaRNt2lh7ZPUwQY1/xBKn6ptuqfgqIh6qSqnxQgZaWmhaVoBF4AeME9yz7CXmB7MSyeCQq49frvpaRPUa6KReIF+eF6wBCijqzd6+9o5IPUnYNud6MXpeqYLRLa1frd37lQ8E1rH4QzkfF9oog8gEh5P7mfLaWFuvNjnwQhHv16iXdu3eX8vL6y/QYhf7x7T9MsEElICDefuDtbh4YPPPjMzJp0SSzHPJvd/2tO4Ob8PkEsz4EhrVkAQl6wrwJpgfBw0c8bF6bs3COPPXzU6Y3wbV7XxvyBr/m7WvMIH9Iv0Pkj6P+WOs9BaUFcuW7V7r/pjHOETscIRO+q+nJcs+h98jATsFrP3jx3YbvzLYpGFDoBXD7t7eb8/TkUU+aQTEaHv72YdNvYPyO4+WcHc8JGlz+MdXpHPqX/f4io3uOlkRj3oZ57vFVEnHfYffJwI4DDSmd8MEEE1AO63+YfLDsA/n1Lr+WXw/8ddBnvLrwVfnfov/Jof0Olat3cdSJx75/TN5c9KacvOPJZpb85rI3pX1me0NuZqyYERP54FpUdeDoHY6u9XsqFnTdDYLHkE7OoBgNSwuWJkw6D0c+2DZmeSwrDo4ddKxMXzHd7BO9KAiOGtBRX7T3C0TQG2AIcppeqg/clEKEwKrbEpJ8BIiSKmD+3PzD3z3sEoHZ62bL/n32r/XZWt1AsCRo8j7AtaczZWbF8aRdXPKR2dnccxfsfoHx2HAtqqlVJwiacvHul5pUUT6U5IWrdtHjR7ktfS04JvzdHz/+o/EfPf2rp90AGw6Tf5lsWrtzTiFLun6MbhfXO6u/QkgI6NwrXK837H2DCeheEsj4xr5pwE82lGCwbYCYwUQEFUMrH1X5gMgST9T8y76qEsU5zgv4a/T4A8ibko/WgGbl+fCnYLKysur9MzdvrqwtWyvdO3SXgV0GmuezNs8Kes9PhT+Z17t26Oq+NqzXMNlYvlG+3/q9bKnYEvbzWbumPtu3qWKT+e7qtGr3tQFdBpjXZm+ZHfJvlhcvlxUlK8x73lv1nqRnpNd6z4byDeb3+rNw20JZXbI66DV+Im3b+vL15j0lKSXm8ZP1n8jTvzxtnu/Raw/p3al3TPvYvl178zfLipcFvT6/YL67HcuLlkc8xgsKFwQdI/3JyMyQt1a8ZfYt1N+uLnX2OTMrU8pTy83zrVVbze/yKvPMvytSKyQ9M908X1+2vtZnbKzYaH6Xkp7ivpaakWpe21C2QZYWLZWSqhLTdhkw8/N6XcJBZ4bMCEMpXMyWtN/H3I2xp15UIk50zpyASkkwYDEzrWDQrqzDugZ7VNQwyP5pIPKTj2iGy0QqHyBcxYvK5xoo/c2iJi+sWcbg09WfhvxsJR+je4wOqqwiYLnkA8OpZ7Ex/8JjfvjLY1lI7smjnzTXi/eYouKpMRmzqUIXluN7dR8jHSMIjqofmE4hlJrSwSSs5tdwUAJEz5qpy6cGHVPttDpx3kQ5+KWD5TdTfmPKkvH/oNRxnLnGSIe556kBFwLUtIsqH0BNp0oqvYqFV7Ez6lZgIUOvujfYs1Af5butqeKl2ZKPRIE8q5Yw8uNfORRoMxs1WymzVdPW7PXBLc4Vby95Ww59+dCwv4+3o55Cb1YGplCGV2/XSwYD1k3wQ29aApgGIn9nx2hucq1fZ5bHDJx8MvsMzt/t/Jj3UQdJf0maBrJoOWaMjWe/e7Y8MPeBWr/7eOXH8rcv/ybnvHtOUGdHhVYbMPvUtIYGKj32DCLq69EZtF9FAh0yazwC3h4AOvPcu+feZrAn1fPv2f+OaqbU7UVFCAdNvcSz3sjKbStdVSGR5jauR64BpHhk8316OwZIrg3MkMO7DQ/aVlf5aN/XDb4Y8bwlt4labC4e5SNUUNNt1XVOvD057p9zvyESSgBoRR4KmnY5cocjg17n2tPABOH0ElPIl9cYHint4ocGP1Qlzosed71mAL4Fvf/0e3VF22i+D/bn8zWfu+eYgEr79UjXVKjusTqeHTngSPPZLE8A8M4c3Pdg83z68ulu2ojgr2bahjKdcq/6lQ/gnRSgzOh4av4dUDoAx1ivcT6nsKzQkBWWY1DoGI/ywdg3bfm0BqmmbCy0avLBiVXygaRP50idmXlbDutMzCtXghHdncqDORvmuAOBN6C8v/R985oy/LrAW9ql4CImGPJd3lmiQrteai401GCog6nORklxqNyrJbLRDF1KFpBcte8E4Dh6/x0NKpt6m/F49yOa/PzV2q/MY6gmVjrLRia+dOqltXLoWurJ7FsDkw7oOrvlePuJiRcM7MBrUPSW4Sn5YAC6fM/Ljb+EMlRIUSQCouQj0tote3aLj3ywrTo7JWAmsrEXaTidwXINUZ0DDu9/uPHDeD0q3sBBINEc+Zz1wYsOJoJ8mAXTVPmIYg7XGXU4Iq4ESj1LpEU/WP6BOaek6wg+EGW/v8Pb14H7w5va8CofGuC4pyjpj9ZNNFJjMAiBBkfUGFIDXJfembvX96GI5mFT5YNUKceANAwpFz4b87MSklDQ43rxHhebFBb3hK6jQxkvfpnZ58yWuefMlU9O/0QeOPwB8x7uXxagM9vbcZB7nhqKfPA9kDiIkZIvv/KhKZdQyodJuwSucU0x9svpF9zGPqB8oCad+9658oeP/mAM5S0VrZp8MEgQQBkwGFSYlXITqzEOkLMmTw/b9ZuAtOyRoMeKj4e8dIj885t/1pJMQy1rXR/lA+lTZwtIgbyHWb8O1Kp8HDvwWPPob7cMdEDDp8EgQP5UqyZ0dhftxlbyAXnQIBiv6uFXPpTpQ/68SkUk5QMPgSpU/mCuHROpKGCgHv/WeNPA6coZV5qmcrqPDPY66OosWUvkOPYatCKRD2+Vgw76zFx1sOFz8G7gKYIYvvLLKyHVGoVeNzt1Dq98DO8+3AQ+jk+4HgEQWO0v4g+qiawYUIVNAzT7+uwxz8pf9v2L+TcpIvabY8L1p2ST4OMfmDVlkwjyQeBSQ3m0tIumIfykXo8TgU/PM+RU0w6oGZAr7qdQqRfeq30dCDp6/7rkw2eqZUasSqs/9ULpNUSae2RLceSupHpvTVnqlD2zjX7jtlf6hzT6DdXhyIden/QXgSAr2Xxl4Ssh/45rUMeMs3c9W1494VV55lfPhKzG0+7I/OC1A26qInewq1A1FPlgrNDz71U3tOIF9MzuGZ58tOvhkgvFYI/fwzvB/Hbjt25Kjnii5dSJAmMsE9LG7inSaskHgZaui4DAySyBm0AHDy0P/HLtl+Zxv141DXz8ygeDAwZD8/41X7qmTw3w3KR++QwJkSBId8F4yQfQwQtT358//bNZ7ImZNBeqBmpWn+TmhaB4l+72DqYMcKo8aGDat9e+sZGPQPBggNMGR8yqtGFQrPAGHg3kEA8IkUqwKBSh+oAwA6VBEqAG35sq4pirVPuvQ/9lto3vMEa2lTPMAI5R0592ccmHKh+etEuogcBNu3iUDyUfqtgwO9TOuMcPPl5u3u9m8/yNRW+ElFa5fnSwjaR88J0aPFR58AJCdvQrRxtTYCjykcjOsqpoKPnQ5xrM2H+9bpHnIfXcdwzK/uC7V4+9Eub50HPmXzAtFNg+7hnOvZJPDIWqMECUvP4M7UuhPo6D+xwcUm1UJYS/p9LEm0rzGk4V3Jd0vvSrfmwLDdwYN1Bco7VE18/9bM1nQWNWKMIFuAeitS/wzvyB3u+nDj3VneyECmw6nnA9oDISyHu1D1YLQkHJh4K/U7WkPp4P7juI3BGTj5BT3zxVLpt6mTuR0Ukl6VGM6DrG+FUjb9qlZ/ueIYmfPue8e8/TYA/p86vbnCfICef37lnRm+3hi9HYEw0cs99N/50cNfmoRuut1GrJx1uL35Lz3z/fDGzMQm7c50b3d2P7j3WDArlLPaHe7oEKZlHKXjVIEvhh+AzyOttCmvTL2xjUCC4qJcZLPjTvSOdLrShgtvXaotfMcwYuZigaCGjP7c3FapBmBqESpkLJB4EpUs7RTSe062HSVhPHTpSHxz4cd+kbkrwGd50ZacoF7wCqBcfST6B0YPb6XrxlmsyaUSqYReM5mHT8JHnthNfMdiI14y1Q17k37aKvedMurucj8Dsv8svya5EPfa7XgL/0juoPAiHf4W2cpOA1iBWDm1/O9UPTGe8te6+W4Q9pHFL2xeovDPHyD9aJmjkSFHV2GKk65ZC+hwSdJ65Tgp3/+BzQ+wDXfBfJ81DXdV3CAYI0sMPAINVMjxnXAOfDWxY7f9P8oJSsBmJ8Y97mhd51PLxqFvcKxAv5Xhut6fsG5NZWPrzrmeAlU3NiOPKhx1Wb43mb1IUKgtE8Md59UFB1B6i2Yrzhmtf1YrxQ4suYG09/JgyySsRcz4eSj3ood28uftMQOcYJJoiki5768Sn393d8c4c88cMTZmKp17bX76GTirDKh4dQ6gTPO44P6hic7lJCyr7ef/j9csv+txhV843Fb8g3a7+JSK5/P+P3hlBEM/wCVfUh2qG6UDcUWiX54IJCnv/VDr8yAclbojhmwBgjqxIE6bEAQeEEqSLix2/3/K0ZKJGX1YfBbFPLGRX+1IumFOaunxuxrXgozwfQGaQ2q9Hg+ODcB4MCgBq2kPcPn3S4PPTtQ4bt6owS4qHmLcAguHOXnc2gSFAPJ80xM9eBTwc4jKfRSu2ipl4CaoqmjtgPt6VziJ4HfhOpdg4ErkGt0xAT6JFLec52/mfMf9wBG+LI8dV/q/KhjaSM8hGQ6wngfpNvSM+HR47Vz/CC7dFZqHpWQu0XA1K0gVpn3RhvD3v5MDOb0/STpgWQcak00ACgvV/85AMyd/xrx5teIPEA7wNKBoNspL4cv9vzd/LicS+a1NNvh/9Wbt7/Zvd4eNNW3G8ajP1eoHihA3KszQDVSK7Xj5IPXXhOgwqmQIgN5HbHzju6gYP3cU97VU0lEGow5LomsECCGV84x97AZCYPAYXBe917xxFm5nqtRiMfgO8J5cXyej5iIWiGhAWCLqTLu92qfjAp8qdAveQjHnBsjhl4jHnO93L8Ne2COlWXLtNMrCAXWiHEir3eSQ/jqhI9Km60msyvfHjvc/8kQY89Y6mO3957Y4jvsyCkTI5eOu4lcy8wqaARIICAREp3cr35ly8IB72ud+vqVBc1Flod+eBm1VnX9ftcXyu/ySB4wuATzPP7597veiDCNeqiPwb9Nxiw9GJCovMbzkiPKLhQdBAhDxyqCsMf4HXhIe9sRRtjEaAwZnnXKdESTHpnHD/oeHPTIuH997v/ygs/vWBmJwRdbgadRejAwCClZCDczFgrEnhvLLOlaFDS4lc+MMRG6qqox1UbKnmVD+86Fn4weDG7gGyhrjBAKMGolXahlXJ6jvsd3tQLA6xWCXirXfylsf6ZPdB22JHIR6SUiwK/wbWjrzWElAGI2RwNrCip9c6UIXQaANRc7T+/zFgJlNrcLFb8sPmHoOsuUiDBkMo9hvlWyyv9M0Wub50tepckT1ZrdS/0etGyUG9VDtBgq6kVJbe6f5QV+1eX9S4ipurB/47+n3vf+gNTuLSLl3wQaLS/RCzkA+IRKu0E4dC/j4V8eMttD+pzUK3xkDGV60zN/Aq99urSVffkoSeb6hFSMHw/Yw5jMoQ33tQh9+xNn99kCAYp9yv2usJd4ZdrX43E2qmXCYd6j7xenVppF1+/EZQNxhfuCVUY9BpPkZQgNUfBtaTpWTCm/5iohnKvMT+WbseqfHjvvcZAqyMfWvYKUQh3o40b6vRjUEYdKuUSCirJIdFpea7OELyDBsTEy9ZDVWkoo4UkMDD4gxc3HqSIwQR5DpZMKadCm6TBoP9x0D/k4zM+Ng3AAOZYzTUTdL3kQweGaLKm1++RiBb3XtMpwUIHKgZMJR+hyvQ0R6vnyGsUVIbvr1JSIBFPHz/dqCDAm3bRlWg12LCPOjP3mk4ZwHSG5692UXIYjnzs29tJbzFI+9UvJVWRzKYKFJ1zdj1HXjnhFdNkCjz+/eOu6uG9njSQKfHxD9xaZk7aJxYJV/HDph/qPaDpNcCxYlDXwby+vo9YWqt7odeLklcd+FW1UPKhZdr+6+uEIc7k5aNVH5lriNSleou8AYcUiDcQ6+cSqJhFa4CH6GsKx0sm3dWj22SENYl6CY0ayUNBfR+RGox58eudf22CqiodCgKnNsTzV/nVVfkAXAvTxk8zzQYB96OOUfGmDkmlc88xhv7jQKfBJMRUtwvioeZp79jIWO71cUSrdmE8mDJuimm2qFDy0Tenr7tIaCSogs3EK1zzMS/58FeL+cFYFW1cbCi0WvIRLo2ijNVrzAplNg2FIOUjILPSGdM/aGguWTFzffAMQaFeDlanDBXg/zv2v/LeKe+5UiryIeCm8jN0BjQkby5+VUf8RAPoDaivhZtVqN8jVFCtb9pF2TsDNQFf0y6hym1VIcBDASB9eFu8ZlOV0UOBwVI9KjrwEqwWblloZj6YFJWkavDykg9NuRAAvIMJn+kNCKGO086ddjb7B4HR4A3Y9niUDy8gmBBSBqQnf3zS7Z+gA5OeN/X1QPY0iBHgvANZPAvW6Wqk8ZRYhwuUeh+5ysf2BCkfMaZd9JjzvahHqnBQMuzdToWfcHHvMbBDKPHcYG6GxHONRCKTGpgg2wRErg29JlFOuC50EuMlMfT4CDcB8AbLSGPe7l2c8+b3f4UDC8E9f+zzIQ2jh/U7zDXtez1j/vRVvPDvo1vxEufqtlpMQCpHxxavasc9oPfjGTud4d4rqBL+bdC0CynCUGv6QEC8C2zquLpThN49XvCZej9QBeMHx9c7dvA8kkcKAqjLHfg9Jw2NVkc+dGansnM4nLrjqe7JjzUAeMtflXzowE9Q1ItCA4uaQQkKoRrzKPkIt84BgdM7EO7fe3+zVsfdh9wd0kjE+/9vr/9z/60DjXf25ZKPKE18ND1SV49HpLSLztjZHzAgZ0DItIuuikmgZ8DT9UMY6AmypJlIlcR6o6ssz+xAm6Ux8Cg5cdMyHtOpVrqEGniCGhB5Gg4pCDCqVnlTLwwgpHJQNPzleNHA7FlLHrUS4vd7/d7sA8dKCRUqHceLfdXgDtnwKjCx9g5hRhZOBYgH6j1QAqMzyXiUD4jCM/OfCfIbuMpHjGswEVDUVPnAtw8Yss626XXkN3+H2meV8Smn/tesf5nn5+12XthF57wE1Wvo1Od4mTgOBA6uC+2WG02tUALH+fdWIflx6fBL5a5D7gr63LoC8znjD2OHjoOMb6qi1pV8+KHjV7QusH5oEYGOL6HIhzY4REH+895/NuQMtccPVTs5zrEowKSNWKfpyhE1S1tEg563UNVsjIkolBBbJkdcqzrpUjw7/1m5/avbzSRDJwlcy41pNm115EPXlQDazTTSRUIjnNv2vy3mBc3UNU4AVcmaG5ELlPSJVjUo+SBIaP9/rydEZ6Eq/aF8xAIufjweajINN2PRnLZKrZQ6qrlPBwa3iU+YWYUGLL/Du67wlvuynoPmj4HKz2wLwRGlgEc9lwzQqAy6P/g+VF3itVjkTcDNqGkyZqzAWzasM+f8kvyIZtNQ5COcCVNnVQyIeHxoKnThBxe6BNk7a4oV9FlRfwqDJsdAVzHV40kw0uCuBFNz9Opv8nbKjSWHzPeEW+gwFjC433/Y/XLh7hfWSfngnvvjR3+UO2fe6Z6/uigfYNfODqF4b+l77ixZg4vXm4LZ1F8Boe/nemIiwjXN31y0x0URvxP1jpSFps68gYdul6p6QEj1uolGPiBKmClv2e+WiMSH88Z3x3qvRAKTHFVZKAHVMZF7FuKUqDGDHjdg2oppMXfq5VqCyHH9a+rRn6pmbRlSXdxDEEvG9ReOe6FWya/eo/gyLhl2SczHhutgB09n02jQdFkoP4cqlRQJ6DHXppeqJN816y55ccGLZm2qppJyaXXkg5PHzA/JMtqqgQwcV4y4wk2bxAJvnhowuHt7G2i/Dw2MyLV6Yfl9H8w6uVn5jEQue85Nh9GS5dkxcQEGVQY+ZnfK/lUeZFYRqgunt8w2EVB5WGVBlAItIWVGyCydig3KpA9/+XDTu4IuoUBnpEr+8H3U9SbT2bGqBlpGCEKV27rkw2M2Ddd6ORQ0pceAMeLZEfKnj/9kDG4El7sOvkvqAq4XTUPpgOktf/WrW5paU1VQZ7/qoo8GlX1Vuq8rCHzcb2q4i5d8vPbLa6asWKu+VGmMV/kIlarzBh7v2KEKkh+oZCzupmCm6zUShgL7i/rgbX9OTxjtnUFQBIwnSPF6fUXzaaC46L3eUND7RlMc6vdgXEnU6tSonZB+rg9ViWNVPVDX/GQMhRtypI3uOLfhCg0UnNN7D7vXPU/JwJ6B6wGS76/sUYUGY75LUtbXkBQUXB2/UQTVGN7YlS5xk48lS5bInXfeKZMnTzaPW7duTch7Gwoa4CPlPusL7wxT87Iu+diy0MjTKqkzgIRbT4bFxwDsPBGGTv8gx+zKe2NhWn3jpDfcAVJvPGYslM2FS7sk2vOhGDtgrJvu4FED5l+/+Ktx+HvTM5pH19woAzUVH3UxQHoDFOfNSyZDdTlVhSuk8hFQUTCehltuHKLg9RQx28K7Q7+UWKszQoGuog+NeUjO2uWsWuTD9fq0q2nU5PV7kOdGkWMQ9nqVoppNEzygxUM+mPkyu9PrBTVHyamSxXiUDy/5gJCr+gZQ2fTeiURudeVi1Iu6BieuQZRKSOBLP7/kvkYAV19aIqrNkkU+UNO4jupT6RIOkL7jBh1nnmt/Izx9rLUTriuolj/7Uy76ed4UbbTKrYZC/5z+hmCSNqECC6LFKsreexYypT1cKAuGcDDR9ZboQl5UPWkKykdNn9gYMH78eJk9e7ZLLi6++GKZNGlSvd/blMym9QWmJG2trNKakg9mkntu3tMNlEjq2qOBnD+mMs3xalMZbwVLQ4JZ1e/3/L2R7O6ZfY+ZxXlnfK7nw0ca6gpID9+pZauaclFAPrSMFlUAckQuEyVLBwn1R2i6gEFby6ZjhXcg95cRhlrfJZa0C8QjXH4VYjnxiIlmgEbZQcaPNkOOVUXwpox0DZ+Qysf2Na7fg4DP7yErDNSY3CIZdr2Gt/qYTUNB5XmUMK6LSCkd7jkIB+eBzr6kXiZ+N9F4LzQQxROkveXZfrlde3IQUCMN4lynk4+fbAJuvI33vOAaRi1Vo7iOJ2fsfIbZZ4h6UwMqKqotPhUmfW6lS/vE+D0UKDrP//y8mYh8tPIjuebja4w6wHo7/x3z3yBDqWkaGehYHYp8AMYSTSM2FfKRkpJiSoIxLlOpiEoKufh01aduCp/7mw6rkGImRHgMSU/zSEodlYgmhPwd//av59MYiPmOgEB4MWjQIJk2bVq939tQ4ERougMfRkMoH+pBoFU0s19Ypza2URMrs0UuLILPFTOuMIMsAU3L/BqLfIAzdznTDMJsE63b6QEBEWHRI52NJop8eD/Lm3LxBwNmeyzgRV8L8rB/P+Dv7jHyNu0heD521GO1mn3Fo3z428TrzBnTFt1WCbzq4I+UdvG3zg41uEA4CJyJIB6hABHW7dHSZUqtAWWg2pMCMqyDXSymU4iLNtqKtzInGjgWKo37TacEEjxUeArw/tAIClD6SVBGdWS7rvnkGrcDbTxKEt+L1wo/VKhcP2Sc9/gJqh+octHWSomGYwYd4651A7ShGerCaye+VuteaQrgGjqgzwFuJ1HtmZIos6mCa46xAVWAlv0QD9RDJnJnvXuWSTVg6Ccgk4rlUXtvhIL6PpoS+QB6jlHIIRAo50xm2W/GJQguExydZNz21W1m3wHkFEOxP73U2Ih5CyAPnTsH5xb595w5c2TEiBF1fm9DgWCpnQf9zWASCa/5TNMusEzSGrd8cYvrldCBmhnRvw/7t5z+9ulmML3og4sMEeEC4+8T5amoC7hA6UB55jtnmqZV/HhBjjFSN8t4wb6ibnhTLt68NceMfh5qiiOl4k2rcAPSUI0bkuNdl0FfyQcpE391AKSVmQU+mJPfPNlcTzrzCJV+0mCfSIJWV3A8r9/7eqMKaaWXmooh5X5irmY+JF56hjDr5h6CdGk1CIOe/l0470N9weyZgMG6G5AAggvfSTpIc/PefTx959PNIHzDPjeYYKSGRxDJcBkKKFJcS6FMmJBfjJz1UTRiBZI7RJj7j+f+BcqaKiBHLCPhXZk10eRDjfs/feNchwTffx70T7OWEdcJCphCCRyp7HDBlzHNNBzM7Bi05k1jYy9PjxZS5icMOsGsTYUxFpKkqXka9/0w/QdX5dciA/xwkEHuh0QrlEknH+E8G1u2bKnXe0tLS82PoqDAkbETDQ7+Wye/FbTeQjLABUvZE4O1d80E2uQyON/42Y2m8sXLqpFwcfmf9/55rlGSGwXlobFBcMcsh++DQEDQ4TVSV/Gu0RAN5+5yrlGIQq2Kyyw4mvmXbaGhWn2gqsDB/Q6uNUChFNAa/K+f/9WkKSAekJHTdzrd+CT8UHm8KZi7AL4Dr/cAUsy1R6ksM3SInWtQ7TrMzCApz713zr1RPztZs2+uhQnfTDDdZv3rICEfY2DEHIzKcfKQk12jNPvy3DHPmSDELJhgEm9pIb6KSObIhiAeXv8I5APimGgPWLJA1R2eI9Qz5H/IeKRGZ3UF5mrWX4FcPjjmQTOBoHss6RjKU1GRmfTpSrHa/iAUGNOM3yqzY8KMsYnA8G7DDbFgDNZS+qePedqsRcN1r8D3wXUP8SbVxURblWF8YKgh8a46niykVEdaOcwDTKNTp041P4rBgwfLhAkTZNy4cXV+7y233CK33nprre/Lz8+XDh1qS9nNAdOXTzfLeOtF4gUSIDciZMQ/iLD4F7lKZp/MGuKdqVnUH5S7khtlAbRwxx/J/9VFr5qgTVCIVG1AJQkDQEMGqniAksBPKM/Ku0veNTlyhgiIGMoUgx9pOAI66cHcjFxDYKiQCWeqTcQ5wURM8GXWD1FCaocIa4DgPaHKkreVbZNHvn/EEEE1JzZXQHYhwKHOVVOHhplkESdtlBeOYKKSQUC4TszSFM2EwNUVqIWsYUYcSabNwA/Eg9zc3Jjid8zk45FHHpGJEye6JlLQqVMnYyIdO3Zsnd/rVz7Y6P79+8vKlSubLfmwsLCwsLBobSgoKJB+/fqZ7AckJCKqY8TixYurR4wYEfRax44dq/Py8ur1Xj9WrlwJGbI/9sf+2B/7Y3/sjzS/H+J4NMTs+aBixV/RMmrUKOnY0XGQYyblOe+L9t5I6N27t1E9cnJyEi6NKStrDapKa9rX1ra/dl9bLlrT/tp9bXkgkVJYWGjieDTEVW9D2uS6666T0aNHy8yZM4P6dtxxxx3m9WuvvTbqeyOhTZs20rdv4hrRhAInvyVfAK11X1vb/tp9bbloTftr97VlIWq6JV7PR0tAPGaY5o7WtK+tbX/tvrZctKb9tfvautE0LfgWFhYWFhYWLRatinxkZmbKzTffbB5bOlrTvra2/bX72nLRmvbX7mvrRqtKu1hYWFhYWFg0PlqV8mFhYWFhYWHR+LDkw8LCwsLCwqJBYcmHhYWFhYWFRYOi8dfV9aGqqkrWrFmTlCZjFhYWFhYWFslvMkbPrmZFPiAedIKzsLCwsLCwaH6gk2u0ZqFNjnygeICW3obWwsLCwqJ5o3zDBll+5lmSc/RR0uOaa6S1oyDQRl7jeLMiH5pqaQ1taC0sLCwsmi/yP/1U2hYUSNWUDyTn1lutVSCAWI6DNZxaWFhYWFjUAeVr1pjHqvx8KV+xorE3p1nBkg8LCwsLC4s6oHz1avd58bzvG3Vbmhss+bCwsLCwsKiH8gFKfrDkIx40Oc+HhUVTQWVlpZSXlzf2ZlhYxITU1FRJS0uzvoNGIh9W+YgPlnxYWITAtm3bZNWqVaZu3cKiuSA7O1t69eolGRkZjb0pLR6MDeVr1rr/LvnpJ6kuL5eU9PRG3S5p7eRjzpw55nHEiBGyZMkS2bp1q3luYdEcFA+IBwN5t27d7EzSolkEwrKyMtm4caMsXbpUhg4dGrXJk0X9ULl1q1QXFZnnbdq1k6rt26V00SLJ2mWXxt601k0+Jk6cKI888oh5PnbsWJk0aVKyvsrCIqEg1cJgDvFo27atNFWoKmPJkQXgWk1PT5fly5cbIpKVldXYm9QqUi6p3bpK5pAhUvTlV1L8/feWfMSIpFHjkSNHSl5envmZOnWqdOzYMVlfZWGRFDSVoB4u9VOxbr2UzJ8vVSUlDb5NFk0TVu1o+EqX9N69pe0ew8zzku+t7yNWJNXzYQmHhUX9ULZ6tVQVFEpazx6S2rGjS4iqysqkYstmmIlUFhRIGzvLtbBoFOUD8pG1x+7mefH3PzTyVjUfJI0m4/GYPHmy+bnuuuuM7yMUSktLTUtW74+FRX2x9fXXZcnxJ0jp4sXSnFFVUCDVlRVmlkUTo+qKCvN65WaHeJj3BPLOfs8V9119MW3aNKNiagrV+/m8nggke1vDgffxvTwyTvH3PA83VjUmOEZ33nmn+Rk/frwZXy2aDvloO8xRPkp/+UWqiosbectaOfm45JJLZNy4cebn9NNPlyOOOCLk++644w7Jzc11f+yichaJQN7Tz5iBYPMjj0pzRXVlpfkxSEmRysJCKV26VKpKS6UyL6/mfcXFtVIzXs9VKMQavPBrcf96QaD2msrri2RuazjoeDRhwgR3rOrcubNceumlUl8kgxhAjK699lrzM3r0aBkzZkzCv8Oi7uQjvUcPSeveHbe68X1YNCL58M4eBg0aZP4dakZx/fXXS35+vvvDgnIWFvUBM4+SBQvM84IpU0zQbo6oLiszjympqZI5eLCkpKVLdWmpUXOqq6qkTWamISWGpATe6015EgQJWn5wH7788st13i4CdSIr15K5raGAegAgHV6wT/7X4kUytheSxyTNe/x5rSkqNK2SfPTpYx7bjnTuieLZsxt1u1o1+eDGCMXMmVn4kZmZ6S4iZxeTa74oX79Blo4/TTY//nhjb4qU/PijmYGA6pISKXjnnXp9HqoCqY36/FRs2SIVeVvj+hu8HHx3SkaG8XRkDNxBUlLTRKqqzHaldusmbQLVON7UC0EcBSBclRmz/aaCxthWAnk4hYOURn2QjO2FFD366KO1lJVQ46lFw6F8dY3yAbJHjTKPRbMs+Wg0wylKh/cmZICBrVsDastF3rPPGqd3xaZN0uXCCxP++VR0cFO323cfSUmLfNkWf/ed84RmP+XlsnXyK9LpjDPq/N2kNRaMSIy/IV70f/YZScl17huUjowdBkjZsmUiaWmS2qGDVBeXOGSFPHOnTi75R54nwF588cUmreG9F2fNmiVbtmwx/yboc7/yN/xOVUruV54nGw29rdpzKNz7+Q7v9/NdvHfmzJlmTOM1fCJsr34/1XwQp3DbG+5z+Az1urDfsyPMmNlHxUsvvWQ+246nDdhDZckSyejXz0wEQOW27WYxOZDeu08Q+SieO9d4s6KNU60dSTk63BSjRo0y8ibPFy9ebPt8tGAg+W999VXzvGLtWqnMz5fU3NyEfseWZ56Rjf+6Rzqfd670uP76iO8t/m6eeex8zjnm70p++EFKfv5ZsnbeWZojUjJqOiaidGTuuKNJt6S0aSNtstuK4D0NYTolYDGTJ9BpUOWRn8GDB7spBgIoQZAgqsC4OX369AYLcE1tW/V7lBBAKBjPIEpskxIOwCPkItL2hvscXod4+FUM9fqQcgtl5I9EVCwSi+2ffSYrL75EOp11lvT8y03mtfI1Tpltm9xcSW3fzjzPpLFbhw7GJF7y08/SNlABYxEaSaNmSIW2o2nrQOGMD53qiwBKFy6U7NGjE/odmEdB3gsvSuff/MYYvKIpHzmHHWqqRAqnTDHqR8+bbqzTd6e0bSs7zan7YE/6pGzVKjc/nOYjZgQajKTq26BbYuaAAVK2cqUpqdXZlrs9noCUkp1tHqtKSs3nTP/wQ0P21cDJbJvg6J3R+0Hw89+r/B3ehfp6ICIBotHQ26qKB6Qg1PjE6xABJQReHwqqBejSpYv5UUB6VO0Itb3hPoe/08/xKhv4eeiUKW3amOZV3n4zSrys6tHAaVxTRvt9SLOpgslA9ogRsu2jj6Ro1ixLPqLA6kIW9cZWn8GuZEHiyUflpk3mkQC9eeIj0vOvfwn5vvJ166Ri/XpW2ZKs3XaTDsceY8hHcT0qMxj8NcjXBaRFtA8HYaSN77MgGY6KkW0CT0qA8PCa+e4Ia0W0SU93jKgV5SY1xQzcm7og8PnTGV40ZslmY20rqgPf4Q343m3S1yEnXiIULxHT7Y30OaHSP1XFJWaNEIDBOCVw7aCYQD74G/1sS0KSD8YUb1OxcOQDZI8e5ZCP2bOkywXnN/CWNi/YdngW9QKBc/sXX5g0QIfjjzevlQYqTRKJio0O+QBbJ02S8rU1Czp5Ufyto3qQmiCYqxO9YuNGaSxoIAH+bqSQDdJUIL1/f+c1qlcqKqQq8Hd+5cMPk3qR8KmXcJUkXsOn//cE4dNOOy1q4E8keUn2tirUj+Yv7/X+XajvCbdd4RBue73/DqWYVJfU9IlQIzGpFkiMEg+UnoYmHlyX6277u2z673+lNYFOwgB1V3t4VLiVLj7yEeh9Uzxrtrm3FQXvvSer/3hNyJ48rRVW+UjQTZn/+huS98IL0unss6TjSSdJawHpDNDugAMkZ8zhUvDWW1KyMBnkwyEPab16GV/JpokTpdctt9R6X/E8x+/RdrjT9CetWzfn7zdvNufJn0NvCFSX1ZAPqm9MBUtASmdmC6hiSW3fXlIyMqW6rNQsUqVVLdFWycQHMnXKFLnn6adla1GRmWVrSoEAS5BSkySzbh4JwPxOTZH8m5m1miJJf/B3BHYMjkA/l+CpngsqR+g7oWpBrC3p+SwCb7K3NRzYflUS8Gio58KrevA9/J7908/0fwdpGlVw2J5w2+v/HI6h14jqVUa8Tap4znf4q3DY32SmxEKh6JtvJO+558xz/A8YnlsDylFS9fnq1SYVVraqprW6F1m77mpUSxadw6TKe5l8rLv1b+a19gcfJLknntjg+9AUkVLdxNYMp8Mpzcbo+dEcym6Lf/xR1t54k5T+/LP5d9uRI2WH556VpgKCLrOVjuPHSfsDDkj451NeS5VL7zsnSNbue8iSY45xPBKzZ5m0QSJAquXnYcPN8z73/ltWX/UHo2rs+M3XtRzly84629TZ97rjDul48klGQfiZdReqq2XoZ59KWteuUb+vpKTErAw6cODAqItz8fl4OjDYhiM25O+9iodRZQJqRkVenhnQjM9j4EApW7FSKgvyJbVDrnkkpZK1804Rt6Fy+3YpW7rUHIvMnXZqMmvSWNQNpktmgJRS4YSR0R8MuSfS+/atda7juXbjxZobb5T8Vxxjef+nnpJ2++wtrQEL9z9AKgMKVb+JD0v7Qw6RJSecaLxt+m8vlp9/gRR99ZX0vPmv0unXv5bCDz+UVb+93Pyu8wUXSI/rrq3TdpQsXCipuR0lvUd3aaqIJ37btEs9sfFf/3KIRyAINqa8HwpUexS+/76s+9vfwi5QVlcQUEt++sk8bztipGQM6C8pmZmmNLU8xmZxSJMrfnOhrLjwoiCZ0gt6ZBikpUnO2LHSpn17I1+qCVVB+RuVLWZ7hjtkhYCcGjD1JePcUFpM/heSFzXtEiBjqB/u7zxBxmxvlvNYta2wVqVLOJheHzQbq6io1WzMonkBdU6JB+C52+U28HuuY1J13uso2WA7Cqd8UMuE2dJhugl7UmOstcQ5MOXuIpIRwrPTbr/9zGPeSy+bMQ01WFG6wJmkxguq9ZaecqosPfHEZr9khMKSj3qibKVTxdDzL44BkoGhKYlJ26bPMI/ly1fUy3QZCmYAqqgwS0qT+zSdOAOzNO0wGg2YQ/GMbP/8c/eGDuf3SOvSxZAJJRZFvv3Z9J//mGCePqC/6YehcFMvSSAfSh4gXNFapJNWAV4VRAONmgrVmKpELJrfw7wHs2qIZmMWsYPjbQJ9I9+7em1wnWu6LSgN4yWuSSCaKHGLjztO1t3+j6DXt338sVRt2+b+m9WUWwMqNmwI+rdZY2nNGnPsuTf9aRfQ6fTTzASJSWn+a69JYWAMBiU/L6jTNbbpof+asZbUDZM1r/m1ucKSj3oOWBUBJ3T2iL2c14qLnXx9EzGDetUB7cURK/JefNEMOuGg5k7IgMq/mTvtaB5LFyyM6Tu8N5H25/CjYlPA7xFImbQNHOviOXODKmy2PP20ed7zxhuDUj76d17TaqKgqka4xaT09xAzrXKhMZj7ew02rvIRLJVH83so9LMt+agbIMEm3dHIrfiVxEImXULpuba8JNfrJUoUuN/LFi2W/DfeCHq94G2nS3BmoFdOUyAfbMOyM8+SokDpcjKg47uifNVq4+UAGTvsEDLVyurTnc87zzxfd8utzoQIM3mbNkZFiXcSVPrLL1L4gaM6pffrZ65VCAhKb3OGJR/1AO5nE1zatDEXogaAig1NI/VSOH26eUSZMP9+7/2YgxMyHzfO6j9c7a6k6kfxt9+ax+w993Rfy6IBlun1sSB+8jEv0Jk0RGrDSyKy9wqQj7kO+WAmQVqJluo5Rxwh7Q8+OOjvk6p8aEkkKQ9PVUut9VkoidVgEqhmMKpI4G/ctAvv8xCnWJQP8/eWfNQLOmFo7OPnKh+GfChZ9RpQPapZeeKVDw3kNMrCywRYG4nyUdD9mmvMIx6jhphkce8zqfBXienK1ai5WwM+lGSgPFDpQlrT/Hv1aildsjRsykXR+fzzTAMyvb87nnKyiRF1qQbc9LBTep5z5JEy4JmnJa1HDylbvly2zXDG9+YKSz7qAS33ZDVDgkYyg5yCQJv/9jtOE6IYUy5dL7rIpCIYWAs8edtIUGJhvBWB7+K7MdgSUM3zwHvaesgHhkdVImKBNt8yfxNG+dAeH2ndneObhfm0TRsjf2K+K3jnXWMypRdHjxtqdz+t63mJJo8GrToboozWvMdTLuumVMrLHbKiKRck9oBnyPT18KgfKenxkQ8+MxxZjHWfK7cXBe1XslGxdavppdBYKQ9NuZjnjeyZUZUD1SMlUELtJURBKkiIba3vMaQ5ln9iUDhtuvmujCGDpd0B+5vgh4E71tSq+dw5cyTvxZfi3j7M8uv/cYfxrvmhaVrtuZEMVKxfFzSucUzKljiei8wI5CM1J0e6XHCB++8Oxx3nGseZ2MV6XW7/8ktTpgu6/vYySe/ZUzocfbT5t46/zRWWfNQD5Wsc8sEFARqCfOCPWHPNNbLiootDzrS9uduiQAvm9mPGSseTTzbP819xSmOjwZsC0eeFU6fKslPHyaqrrzZ17mY/09JMMy+Faf3NsVmxosYoGsPiTOrmDhXA9XimBpQP2hlnBm5kBku8HqDrxRdJeq9etf7eTbsESEw0pAak1LIogch//L2zUv97jKKRmuoqGeyn3++hCCIfMRhOXQKjn+2bvZtF6rZtM31DIg3+EA6MwmVLlyR1QA/6zupq51ratEmqtjeO6mCCeOC4eM2eDb4dkFk1IGdlBdIujpHYnDuzenFpRPJRFDj36TGm6/yLQ+IN85MPNZe2P+hgQ44pJzWv/xBsOmUiULai5u/d19euNePVultuiStFgrKiios3xaooW5p88qHKh6bVK/PypDiw35GUD9D5nLOl3YEHmiUhMvr2lcydnJRV6c/RSduWp56SXw4+RFZc8BtTct/+8MMla5ddzO/a7uVM9oriJB9cL1TeMBY0Bdg+H/VA+boA+ejdK2hmngjyoUHCX0q37cOP3FxkwftTJPf440L+vfFqVFWZHG1G3z6mtnzjffebYF2+YYOkd49crlX8vYd8fD/PmKgKP3B6O2ybNl02BGbaWTvt5OamQVrnzkZeZFay7Ne/ln4PPmheh8Fn7bGHmzJRBBmnKiqkZP5P7o1ey3DqKZPN3nMvKZ3/k2y8/34zYCJxdjrnnJD7Ei8pTEtLk+zsbNm4caMZxNuEKRmmxLXcU6FTvq1QKjvkBL2nDA8QjcR4f0mJlGVkGOJRvmmTSa9UVlVJaps2QZULFSkpUsHncu7pTRJjVUNZZqb57Ir8fEn3kJzggJDi/J+aKqmdO0taoFEVbdzVSGfehexeXJz0sl2+tyyg1FQWFkhaWsP3YSGt4J5H+rA0wH6H3I6iIrMdhqiiPEEG09Ociou8PEMwzXZyPfJIS/3AtjJeQDzWr14tWWvXSZs6rGNUNGtmyHsTiR9kDBpoHiEf2z78MMj3QfXN0pNPMeRpyIzpQWs7rbv9drcBHuSj3d6xlehu++QTl4zR2tzbH8dcr4HtM6pZknr4qPKRMXiwGWNYTK40UOGXGTge4UD5fP/HalYjdpWPKBUv27/8Utbf8U/3M9ofcrB0//Of3d+r0gyJgaDxnliw4V/3GFJDiXaff93tGvcbC5Z81AM0u9LGV4lUPpDllp12unS59BLp9rvfBf1u26efuM+3PPmkdDju2JADpZKUnMMPN48oAjBnBoyir7+W3EA30lCAGZctXlKzPd/NcyVARcGbb9VKuSj6/PseWfW73xtSQD28zirxngz95JOg7S0PpF0IhJix8H3UIh+u58M5vuZ7R4yQvOefd2dqzC60msSPtIDnJdbzwvb16tXL9EtYHhh4Q4Eb33QnZX/Yxy1bJN03czbVT+XlklpRIW22bjXB3ezPxo0mmDCrTS0rkzae/Lm+h9+nhakACrk9KBxbt0pKfr6kBWY3BFZjotRt9GLtWidIpKaa4GZ+T2Djsbpa0hjQ6zCDjge6zSBl2zZJa4R273gbvJUcDIoce1Ic5tzl5Lg5/7hQXW3UnJTMjJiOo54rlK8037alcF7btjVeDH6vZDUNIunpdVP17rtS8tTTUvTkE9Ju333rlnIJXCuUlXrTG5kBz0LWbgHlw0M+Nj/2uFuSSvm9fje+MyYrCtKjoeAlFgomV+6x2bTJTLhU2URZ1SZ8TFq4z1SBTobywWdT0Vca6EYM1MMRK9Ssi2JTVVrq+ry84Jpb+9ebzXN6M1FF6fd9sS3abLH4+x/MSt/RwJiS//rrzj6tWmX6IXW78gqzAnmi+jHFi1ZDPmDJG+67T6oKCqXfw/9NbNqlV++Eko/CGTOclWJfelm6Xn65e1MyAzHBFok9NdXc/MWzZoVcR4XGX6DdfjUDUPZ++5q/2f7lVxHJh+mVUV1dw/QXLTL5RQy2+CoI8lqCFop8QHJ2eGWyaQYG0eHmYX8qN24yAxQls4DAq+sm5Bx1pGx94UUpCXQoDUk+AiTC7IuHoLTJyZHOZ58ddn/c87JpU8hBLhQyMjJk6NChEVMvm//3lGx96SVpf+ihrjzc/+WXnGAVwNKbbpKqLXnS5777JGugM1Na/cSTQfvZm1lI4HeKwjVrJKNXL9N4LJ6y75XX/MkEugGTJ5lGZquvv15Kvv1Ouvzucsk98kipKCgUqayQgnfeka2TJrt/y5yR9BmemQ3/vtdcV50vvSTp3XrpVEt3YHXy938k9LouycTaW/9mmkIpetx2m2QPHyZLTzvdKCHZhx4q3f90TdyDdOFHH8mGCXeaoAMhj4bVV//RBO6unKtAm25SlyvOv8CQoLQ+vaVi9RpTSYF8TgDucfvfpZ12cs3Lk6X/e8o8LZ73ffzkI5ASYczY/sWXJiXqVRg02GrahX4TKGsQJK8ng+ZbfDeBdN3fbzevtT/sMKOWFH37Xa3l5jc+8KDpnMo9oo3LIKUoH0BXimWflHywEKMXqHbJIB9a7ZLWo6dk9Olr1Fbz7969aq3RFA14A6mEgWyXLlokbT3pasXG+x8wqc+0nj2l+3XXhTWct91zuBRCPr79NibyUfjxx2aixDZkjxopBe++Zwgjing0FTxZaDXkg9mCma2npJgSJV0GORGG0/ReifV8lAUMngT40oW/SFagfHXbp5+ZR1ZOzBg40AQ+AqCffDAj1zxoxpAh7uvt9t1Ptjz+hGz/6suIQZib3Lx///1MOS0Me/Mjj7oLJ+Uef4LxnXjzj36kdeok/Z943OSLMwcPNgqIMWstXeqSD7MAXGB2nTNmrCEf/nJb4wnwVbsA6uu5QRkcOp9zTsRWz/p3WgYdTiHxg3RLxC6RSxZLm7VrpX2f3lKOAZZBevESyQoMBsY/8ON8Y6xq36+vpAU+q8e4cbJySs2srsPQoZLq+56sX/1K4kXmkMGSQROqtWulctZsyTpgfymf8aG0KS2VTnvtJZkco8Bxav/b30ratu2y5Ykn3HbZdF5ksCsZOlRK33pLyj/7TLLOOEOSiYqZM80xBJXr1pntj1VGThQqA9uggSGFwNYhxzxyhxS98IIUZKQb6TuedMyWTz81n1uelyeZGRkRyQt+i7IZM8y10vmggyVdr4fevaXTAfube6Nq7Vrz+5zBg6Xiq6+kkn+vWCFZ++9v3lrg8QCU/BRfKSwkhxJb0OGEEwLkY7XTLLCqypwT9VxhOFWlkuUVaJzlTRvi3QIopVyLvL/P3XfJL4ceZpQd73LzKKqU9HPcV195pewweZLxR2z75FNzv5IiaLf//mbxypLv50mHo440f+fvCWS8YwleRR3Cp2NPes8e7jpRIHNgZL9HKHDtYFxlQlb684Ja5APiSVoE9Lzl5ojjFOlrqhe14i8atHQ694Tjpdsf/2iWw0jt1KnRiEerMpwS8AhWzOjr2mXOD521KxuvmWHXj3yUBgYBsP0zh3B4Uy6sD0Cawbw2Y4Zs+/zz4L8P1KEzWEACFNkjR+BEk4o1ayN2INWS17Z7DJO2e+zhfE9gZk/3PlaK7XLxxdLlskvNQBEOqDNthw0zA5eas3TbgMq6EAmzFktKihnwvN1Cka211NDfGr3Hn/8suaeeIp1/U+MqDwVmKBrQ/GXQrAWj6zTEC46j2S5SWmrCC+SDgRJAoxZ5FgFrd+ABkhkwj/G3XqWkPmBwyzn6KPO84N13DXEkZ066y2+O473M5mmL3/fh/0rPv9zkzrLa7e2Q2eKZs8J2nU0EyNPj8TEgLUEFRYyVAIkCExFN/bUfO8YNbNrAzlR2GAPg05L/miNbxwLjwfjSUVMIzPod4VA4fZqrJPrbZ3f5zW/c7rgga/fdjEpkttVzHxfNrmm6V/rTz3VKuWQOHSJtd3eIgZksaCdPeloEiBePbQPerfV//7uroHU680znuxc6vYV0IsH1zv1X059ndpBKgqIKICCrLv+dFM2ZK1snT3YVUV2niRSD32yqCLfQZH1giAcpyPR0Q7a85COa2TQc1PdR7PHUKTbc829D9HKOPlpyDj004ueo4lz83XdRK4goPtj28ScuseT8dTz1VDcl31hoNeQDuAFCB7wwiKUczJjAdEZey/NR92ZWSJKoA4rtn3/mfl/R19+Y5+0OOtiUeeUiiVdXy6r/uyKo7Kr0F0c5YVEjfxDWG5nUSziUBJQP3qvvVzALMYHrj1dL96uuinm/1JxVFqiR14Y9gJuaAKw3tFf9qAwQOQYvv8zZ4eijpPftt8ekZIQihhChZaefYdaj2fzEk2HLS00zOTwRYZWv3iHz4DXLbvcKmjHznLI5VZISidxjjnFTd9ogrt3e+4ScsfNa7gkn1BroSL9AmJBp/S3sEwkCG0ZEvAyobKDkx4ZtXlW2yNk/CJqaobn/tLqCgNo14LvKezb6mk1K1iD33iqMaMdxW2Cl25wjahaYU2T06ycdAkoY9woTCl4z37PCQz48QZ0UbTx9ONSL0XbUKLdrJyqFqqB+f0OvW2+RLpde6o597ceMkU5nBcjHokXmOBAYzWcGjI3ZI51rvWhWzXZu//wL85g1bJg5B5CR5Wee6U66KCvFqK7pYL1HXVI0wOlkXL4m8R0/3cklrRTatAlWPqKYTcNBVeqtL08KauC4/etvZPunn5qUever/xD1c7J23tk0JjQL2EXxhTERkfJyE/+0D1NTQCslH/Pd9AiLAG15/nn3PZsff0J+2f8AczHEkgsknaOzWg1w+CTiKdmjJFb7YlCZoI3LzO9mzTa506JvZpoZFDOxzB2dFuY9/3arkc8YwFdccqnb8790cYB8DB5c67tIvQBSL+FuOOPnSE013g298XX//ItcxYqMgExZurRG+dBcst7UbXd3ZEivMhUq5VIXhEqJmZu9utr4UTbceacpayPH7QezO64Jbw8EU5YaWO0ScuFeWwGvTTD5qN2CucORR8rAN96QngFzWaKQNXy4OZ5cE7oCaXacC4CRBtNAzHWXLGgJJ9cZKlsiO2eiaGx55lm3UVbYbQikCLKG7ljTBGrZUimaO8f1FrFSNUGBbdP3e8H9yorWlEYuPXWcuff95D4S+SCA6HjD2kWhAAGiS2bH004z/07vH6x8sL9awmlIepx9OJTwk9Ll73U9JJY9CEU+uB+7/+EqGTJ9mgx88w3pc8+/DBEw/i6qdlascH1NNeTDSYugKukET03sHY75lfR74AGjThslcfgwo65m7b67Gccgw5ApnZjpI+NfssptTVqYfQ14SdL7epSPOqRdlKTlnnKKUThW/eFqp29SdbVsvMfxBHU6bbxk0A01CjjOHBtQPPfbWtcjZt2Vl/1Wlhx/vGy4+1/m9dyTmtZquq2MfOwSNMDRGQ+j2fq/3WZybXkvvywb7rrLOP8NW4yAmllvzawWg6ZK1371I1xPDljr8nPPkxXnnWeCoKoWBDNMTbzGUtbkPEG7gw6s+b6MDOn7wP1GAsWQhXkPaFMwJFQ/1IBa9NXXQZI6N2/+m28a8uX87VBHKSEvGSBCzE7rWoKYEUr5UPIRSN1kDHLIUqmn0sbt8eExm9YFoSpetn/1tavmsK8c522BrrAKUjIsEMVgnv+O02LaJUWUiKamGmJjZNC0NHM+tbRVZ8/h8sN4eRLhPfKC89MhoH5omWK8xkPvDI1jkghQ3q0zSUVxYBFAlBaXvCVowbLNEx+W9bff7t4T4aApAvrT4KPSdBrmaOR2yDdKg65c6m87vv2rr2TJ8SeYJdONR+unn4wXS8m9lpzq94RCIZVplZXONgRm8n4w0x7ywRTpeukl5t8aoFBYTMO/7741AY17qW1ATfOmACOBMUbHRE2z6oRAz0e4yg4UAWbTVG5gIqUkFRS873RThjSoAsuxZHwkzVKOMoOaGyD03IPcQ0M/+lCGfjhDBr70klFXTdM90reB6wMlBrJmqrMCY1KyyIerfARSbxkcE11GYnDdyIeppLv1FrPdkLRl40+TxUcfbVQiFMAulzmKaCzAdApoN7D58cfNMV97662y6PAxsvqqq0yqnHhC2poJMo3OmhJaGfnYtWaJ89JS100NqKted/Mt7r91ddRwKF8b7PfQC6tmHZGaBYkIRpitlp3x61oDsAlolZXmhiqa+22NajFkiLQ/4EDzfM1NN5kGXwS6jqecGvT3BM1uV15pnmMSYyAqC5N20cHFSOp5ee5sDGK0/OxzZM2110lewLWusxWz1Hugu5/OMuoCrdog962qkF/50Bta105wjmPtMtv6KB+aKiO9pe7+bldfLbmBJmzkm73Y8r//mfNjfvfFl7VVjR49nJ4ZHTpI9qhRNdVK5eXmEbQf07C5VTw5CmaR6g+IB9mBXgwco0i+D9JROPQj+WZQiJYef4IJ0l4/j6ZYULw0bWUqKMKskxMP9Dz6G2EpdOaNzA8I/BjwqKzwTla0K63OGjGto3pRjr725ltMJQqEE08As3ewaeIjhtwDVSoidSQ297ZJuRwR8/6ZeyYlxSn3pvFVwO+BuqDNqGIlHyULfzEEhMlTeoD8UFYaOFBxlZVmBVRZjKjueBPov8FkSZVU1F7MkkbNjUFRJS1jtvWH7900A4qEkh0qDxPdIbdiXbDywVjY4y83Sfc/X+eOJ3UBymKf++6TtqNGGsLotgs499y4DKC5xx1nSAUq/Ia77jbVhRiTmWDh9+vy28uM6X/gG68bhYoeTE0JrYp8qEubYFI0c5brk9DAw41G2aQOSpFaLZevdYIP6kQ0eX/zk08ats/3wXQxOSq0dS4gz6mVLlQu0B0PmFkYedbb/16rBwbAyAVrJrDyHW6lS4i0CzMPSq28383gx99QssoAyICJ5KmAqXe76ip3Rl0XcDPw+aZ/wDKnd0bZ6lVBA52rfCxd6ga8ZKVdmOnRP4Fgk7XLzq6BzusepwJAjW9uqXOAMLk9XjznXw1ctLUnaJN+43rLDpRNNhQgi3ruaehUF7UKQsDKnJBiL0n3Y+O998mmhx6SFRf+xu3X4YVZd+fWvxn/CB4CKhtcs2kgOKJ8mDJEpP6qKpNqZBmAuvpNHCPr/Jr72BeUkPoXjBwlC/bZ1zWWQj44Tt4gm71XTfVEziGHGBWD62fjAw8YIoXCATqecboMnvK+9J4wwRA97nXTFCw7W3JPObnmmg6hfhozIOm/wNodsQKlQc2wpDh0P9qOGClZuwSInM/bxr1U8MEHtY4HVSQuUQhcK2aW74F3lehIcDscBwy2GM69UI/Txgf/Y3wPsSqqbYcFjO+ffCrFgXPLudLJHypCqOuvruAaUpJDpYui85lnSpfzz6/356fm5MgOzz4rQz75WPo+9B/pedvfpNvvLo/rMyCZQz6cYeICqhH3faezz5a+/3lQhs6YLt2vvNIoSqYRZANXkMWCVkU+vK2BNz/2mBnoGKR7/eN26fHXv0jX//u99H3wAXdBoJLA4Lf9m29k85P/Cxo8NPik9/SRD1+XU24I7WNgGsPgMznnXOPxIH+s5W1g2+efuWkXSmRNiiTQnKj7tdeG7bnAjEJn3XnPPBuy0sWLjuPGOe99+hkTYLc8/YzLvEnj9PrbraYrqoIBpOtllwbV5scLM7Br6iUwEOvMQpWPDPLY6elGJtTjmyjyoWWCel405ZK992gzM1NSR0DU9uR5zz5nZmbkVlUJQmb3m00VtEB217GY5AysOWPGJKXzYiQYQ+tllxri0/H00+r2GRkZ7qyd8uxQQMFSAsvsbdVVf6gVYAvff99UZCnynn/B/B1VLcZsmp1t0h3ee3PlxRebssvlv/lNnaptUM60QgoSoGqX+fe27bLmxhvNd0MOSZ1BQCH7/iCr1Rl6PDoce6x5vvnhieb6JMXR/39PSq9bbjHBhBltt9/XNAWE5JNGMR6M8nK3U6gXBW+9XWMGDJTUxwo1nZoF1gLmTq5jTS9D3rznA2Vz9RVXmv5BofweGuCB11zJvRNrRZaSD39qQEFZPMZyjp+mtgmQ0YDqygQCUqMehoyBOxhlSv0pOmbUF3gAFx1xhFvhF8qzlSikd+9uJi2dxo+PeRFJL+guTeXKDi++IIPeeF163nSjM+bU4bMaGq2KfAAd4LSpUPuDDjIDH4yWbqIEWNcbghmostI0/9kwYYJpmKOzhpoGY5GVD2bODIQ0Ghr01luSve++Jhe/9qab3GWq3Xa5839ym+dkDhlqpPx+D/3HNKHqEqWclAWfQEGgf0SolIsCdYPZJkF2zTV/chSg9HTpdMbpkkyo98GsHYKZi1bSzOACx8zkjAf0DyrJ1eoUb4OxusBfiaTnXw242jcEVYy8MtK/Gja7XHSRe3xJbYU7/xA2k6KqrDQ1+PHOZhMJmsjt+MXnxkBYV3Q+9xxzXaDiaHDzgqZReI0Y/I1n5quvZM11f3avfdbAYGEwQFk2xxdVgHti7Y03mdfb7bOPS878/WpQ/OqifujaGwqvSXTjvfcaTwfBlUZ4/SY+LANffslNr3ibuvmPHWXdmvNnhslg7/fTkFfXqq12++1vPBEZAe+VIQOU+kOOAuPI1tdecz4bE2KcYLFI8xks2EZePzfXTKYgRahWEA+9j0iLsS4U4Lr2qh+0Lgdec3lQWWmMqkdI8uFTPmh5MODpp4LSLNn7OfdgJEB+MLWSetZW7dpxVclBInwfqNJ4ALlGIKW0NGh30EH1/lyL2mi15ENBzww/tM6dnDQyvM6ckFnznn462IwUIe3Czb/l2edcVQFzIdIs6QeqIjZrg6ezz3b7PjATYzaonws5yg3MuCLBnT0E/AmhKl0UkK1uV6lPxBmQco/5Vb3ymLGgptfHUleWZeDwSq6Zrul0sa+7aWI8H5wXKlpUpvZ2B9SGacXfzpX8t982qQJkdMof6W+ikj2zcVf58J3/9ocf5j7nPGvHxuYIOkaSVwZqRPamIrXvBUpa77vvMoGZ2eyisUfI0nHjZdm4caYRFcbnbpdfLp2pGjHVQ7dL6c8/G9LS8+a/up/HQN/n/vtk0Lvvutcz6dF44a048po98YEooex5663GTI2R1Jtq0SoGKkv8ahvvJ3AOfO1VM8MMJWVDpFAP6UysZF4DLaom+77kmGONCkGlAwZVFJPc46Lf4350PudcUz1BqjjnqKOk599vM2THqEiBVt7aViD/zRqjLCRIS2tp6a4eKy9RCCYfsbcRJ32GcuwS+hD3Lce1/9NPma6nnPNYfQ6QUx23zHYFiGIiyYe2dOeYDv30E+lx/fUh26Bb1B+tj3wEjG2AIE9de+337OaaTtUMxk0F1v9zgpnNuWbJCMoH+VXMQAyyagKkgRCdJJ03VZhS3ZzDDpX2B9aYOenhEW8rZwY4740eqtLFC/wkbT1ehE5nh16ULZFAJgUMdlrr7x3kzHvUdLrYmR1qakal1XobTrdulYJ33jXpFORkry9Gc/wmbfL8C+Z5pzPOcNz2w4c7vpotW8zg7S4q6Dv/OYc7japA+8MObRbyZySo4sZ9sPjoX8nPw/eUZWefbQLntkAvBlo0Ix33f/IJo+Kh7BnDdlqadDjheOk3caKTxkFaZhFCZt0E6Xv/HdQSm0GeEmQqO4wZzxgT4ycfxT/+EBSc1FS64e67zXfj8fLeb17kHH6Y6e0BuQgXANXQGQ4Q/25X/J+74GJWgHxQTabkp+Ctt2TVZb81zyEQ3iZ0sYI0Tb//PGiWi+h7373SwWNYzQyot9u//MLcR1qlo+bJvBdeDFpKwfQP8dxj3lSDKgyxwBCfwP5SLhsOpIT7/fchE9zjAWuRsOYJk0j8Ld5t9a6QXRdwnEgTAq4RSzqSi1ZHPowkGchfIvnilwhHPhi0CgIrufb861/M4MmNamRLXdjJt56ABjmC5/p//tMNYN4LOffUU036BTDzYgbVLlDZEi1lEumm9+ZOo32GNgojQJgyt0C742QCUqUy+Kb/Ouvr5BwZ7PB3lY+lS0ylAsGegKV/W1eYwT3gn1kbGPCM5O9RXVisTlMrZkaamSkdkdrVqBswy5GqKg30ZUnzeX4gt3pNdDjK6TbanAGpNSZsYxReZh6LZ802Cx+ishFgtOESKYgBLzxvfBBUBQyZNlX63HmnGxxIC5DzBwSdUGsSKdTDxHfFU8VgUg2B7p567riPUSqLUbuM6he+OR7nmXu9/cEHS6KgSxy4JsyAuVnTUx0DptREguUKtDpnwz//aTw5TLZoc25eZ2KEQT3QRCzL4/cAECf1SSmJixV0NDXbcFiNCpgoMCnrddttMvDVV9wy9UQpHxAxPoPxJpQibpFYtJq1XRSmNfDw4aayRCtbQhKUwKJqmJhQJzA8YShsf+ghplUt/Q+YnWmu2E8+VBlBgehy0YW1toFBYMuzzxqjkRrFGBzIZ0ZTLcIBX4LOcEJVuvhBTpsA4V3+OpkwBjny+wETHB1aDaHzvkdNqYuXSOGU92sIWmAWWVcYX88550jB2287y29nZtQyYzKTZOBRsyIGw6C26PvtL9s/+dT1IbBQn7/en8GRWSjKgBpQmztw0xe8977x42BiXfvn691j4DdBGxK8775he4sgmyO1e2fZoWBSACwFsHGj6WURS+Mlt7smZaM5OUZRwJzIa/RAMJ87YkSt9uXJhtffYEyqjz0qW199zfQhoVqqPiXs4UC6j4q1zY8+alrDA1QlSB3jHx4ePGzaLFGbvHnR8ZRTZNuHM1wiGI86ga+sri3I44WmPutLPgoDfjnG+PqONxaNSD6WLFkikydPlkGDBpnnl1xyiXSsg7SYDLCOBeuhdBwX3DND4Tjvd3HXZsB3oRcjTmJ+wsGb+jAzjXvvDXkhmw6BnhkYMy68HVtffTUm93coYIzSNQjCVbr4kYyVIMOBfYSAMINmAOx56y21SuzU8EeVwtZAlRBt1BOBHtf+yfyE3b70dBP0WPgJdPr1r4N+T68Hmkeld+8hHU8/3e3I6gf7ptUxLQEQBfVrAJz1BC6qNzpEWB05FCBn0YgHgNTjvcJzhe8jVvLhmid33838jS4/vyXg1ergU9oaAowJ3JMEx15//7tROjufc7YZY0jnJqsaiiXTOR5qrjbLMZgU61mGfGiKAfiXUQC0+Y6l1Xeo+yiS5yzRUOUDnxiKDiQLtQzVlN4tsaSweb/6PVqCYtmqycf48eNldsDUBPm4+OKLZVKg/LCxQflb5zCdBL3mMiUfodZbCAeCP85/Kkl63XprXDchcm+3q/8QM3Hwg78b/N67Tdpn0PX3v5fCadOk5403hMypcuwYTBioMfoSPBIpgUcD5ZWQD5oa+VNRZqXeKB0zWwMInr3v+EfSv4dSVUM+Zs92UyjRoE3FIC4Ede4/qtZ0EcB4GnklChBsUlG0eveuZJrs/i9Uj/X5192mg3Jqp46mrBxoyfD2zz43HUZJE3orXZobUJa4X2nnTinx5mHD3PGDarM+/74nKsGjLwxpsYYeb1ozkkI+IBteoH5MCyyc1Fygvg88EdpaORYYt/t/HpTKgkJ3+eeY/zY9vc7EQ9FQKZS6Ald/NGc/KSOVUE3KxbegXDJBVVLlljx3hU6LxoMxRD/6WMymUyo3VLXK2n0Pt/TTXUNmjz2S2rMhlp4cDQ1UpkFvvxW8sGGbNqYUm5+WAEjWgGeeNj6yzY897q4pAwo/+MB0r+5x4w1hG5nRc2bNH69plPGmNSMp5AOi0dnXypV/z5kzR0bUo+9AQ4JqENg0udN4A7qWZVrUDZhLzaJvCUy5xArIHx1dLRofps9GSooxS9LMLGuPYY7JkCDCj5HTU8xTFlhbfeVVJhVE8NAuvt6+E35zc2tBXddjak5ARSWNTeq6aPYcs/gmvrs1f7rWrEacktrGrVijNw1VbxWsEbNpk+S/8abxCaEAUaVk0YzJx9YwbW63bNlS67XS0lLzoyiIsgplQ4GmNjQfsmh4aLmtkUDjUJ0sWhZospe5y86m+d7qP1wd099g4Ox7/wOur0RXgAZ4ASxaNkjBuAbfESOkYsNGs1iomm7DgXGm1z/vqLfybNFEq11CkZI77rhDbr311obcDIsmDnKurFuRe8IJVgJt5ej1t9vMzJW296bxHCsJh0G7gw+S3v/8Z9ACWtmseTF0iGQMHhJ2xViLlovOv7lA2rTLlm2ffmaqF+lcnJrbwVSxpXbsZB4hqHhD4u2tZFE/pFQneilAEXnkkUdk4sSJruEUdOrUyRhOx44dG1H5yM/Pl/79+8vKlSulg2eFSQsLi9YNs84LHXyrq8UMWgxd+pOSUqvs3cLComFB5qJfv35GaMiNYldIivIBwYB8+DEqRL14Zmam+fGnXdgBCwsLCwsLi+aFwsLCxiEfVLf4q18gHrH0+ejdu7dRPXJYJTLBRillZa1BVWlN+9ra9tfua8tFa9pfu68tD6ZFfWGhieON5vkgxXLdddfJ6NGjZebMmTH3+GhDh8i+fSWZ4OS35Augte5ra9tfu68tF61pf+2+tixEUzySTj5QPyZMmGCejxs3LllfY2FhYWFhYdHMYO29FhYWFhYWFg2KVkU+MLbefPPNQQbXlorWtK+tbX/tvrZctKb9tfvaupGUUlsLCwsLCwsLi3BoVcqHhYWFhYWFReMjaYZT1nHRxeSodnn00UdjKrW1sLCwsLCwaNlIGvmAeFx77bXm+Z133iljxowJ6nhqYWFhYWFh0TqRFM8HqgdkIy8vz20yNnjwYFm8eHGtBmR+VFVVyZo1a5LSZMzCwsLCwsIi+U3G6NnV4MrHiBEjTJrFv6BcZ8+CT+EA8bCt1S0sLCwsLJon6OQarVlo0tIu3sZiL730klnvJZTnw7+wnAoxLb0NbUOhZHu5zH5vuQwd1V2672CPp4WFhYVFctvIk7mIhqSRD6/qMXny5LB+jzvuuENuvfXWVtmGtiGw6vs1suSbrVJVkiZDhiW3bb2FhYWFhUVKDJaJpJfasr7L1KlTw1a6XH/99ZKfn+/+oHhYJA6l2yvMY1FBWWNvioWFhYWFRfKVD6pcIB+YTNX34SchdHyzXd+Sh7LSCjf9YmFhYWFh0RSQNOWDVAvGUyUeL7/8su3z0QgoL6k0jyXbkkM+tuWVyA8fr5LyMud7LCwsLCwsGkX5oLR2/PjxQa9BPC655JKEfUdlZaWUl9vZfDRUVpVJVi4cs0q2by+S1NTE8s1ZUxbL4rkbRdKrZMiI7gn97JaE9PR0SU1NbezNsLCwaAQUbCqWDcsLZfBe3SSljW0h0STXdsEtm5uba/wfoQynbO66devcNI5FZBQXlklFWZV53q5TprRJ8IWPl6SyvEoy2qZJZnbS/cvNGhDwnj172v41FhatDK/ePVvWLsqXk67eS/rs2ElaKqLFby+aXbRQ4tG9e3fJzs62A3kUFGwudlMvud3aSlpGYmff+RuLDLnJyk435MZCQhLmoqIi2bBhg/l3r169GnuTLCwsGgiVFVWyflmBeb4tr6atRGtHsyIfpFqUeHTp0qWxN6dZoDi1UiTNIR8ZGZmSkZXYU749tUJS0qokLS1NsrKyEvrZLQlt27Y1jxAQrl+bgrGwaB3Ysma7VFU4CYbyEqcAwKKZrWqrHg8UD4vY4E2qVVUlPsNW7WR0pKqySWXvmiT0urVeJQuL1oMNyx3VA5QFVGiLZkY+FDbVEjuqPYSjOgkEQT8/GcSmpSHR1+3PX62VV+6cZaVcC4smDIymitJiq3w0a/JhUTfykWiCgJdB/cpW+Wh4zJuxStYtKZCVP21p7E1pkZj13jKZ8ugPllhbJEz5KLfkw4UlH40AVv2l+Vp9MW3aNBk5cqQ88sgjQZ9Nczd+KHfO81QF1YUgRNpWb0oHkhOpcCrUtkYC7+N7eaRnDH/Pc8q4myI4TuxfQ4Hjnbduu3leWmTTOMnAnPeXy6LZG0zO3sKiLqgor5Qtq2uuH5t2qYElH42AiRMnRgzCsZYRs1jf6aefHvQaQfraa681P6NGjZJxZx4fUgVJxLbyefn5W2P6/FDbGg5HHHGEeZwwYYLpDcMihayIfOmll0p9kYwSbciREpCGQmFeiVtCbaXcxIPy8fJSJ1BYcmdRV2xetT1IObP3agsiH8y2GSQa46euLVLo90AQhCj4wcyebrB1AcGPhfoUp55yqsz74TtZtmKp+Xdd5ONI27p40WJ5453X3H8nIvWCYgP8DenollvfJnX1ObaRADli++oLBqbFczeY2VI05K0rqvm7IjugJRre5Qjs8bWod8olYPey1S7NtNQ2FJj9PXLlx43y3Zfcd4ikZ8ZXMkkQRwGAKEyaNMkoAl4w26+rfE8AfPTRR91/5+U5s/xOuZ3qRA6ibetdd98pOw3e3f13InLjkCfvPnjh75obL+pzbBsCc95fJnOmrJCDTt9Rhh0WeQXivLUeKdcGx4SjeFvjkA8Ul9T0Zj8ntAhgwwrHbNq9f44xntq0SwsiH80NBHJSIqQQLr74YpPW8Ab7WbNmyZYtjoGQYM/aOPwNv+M5s3dm2jwPBX6nePnll+TgAw+V3NyOdUq7RNvW2bNny/q1G82/+Z5hXXeNa1v94P2oLOHe7yU/fAffxXtnzpxpiAWv4RNhe/X7WVEZ4hTu2Ib7HD5DvS7sN/taV6CQFW4ukfKKyCsL528sCTzWqBoxKR9Wyk2q8lHWQMd31YI8eev+b2X/U4bI8DH9GuQ7LeoHxtRvp62U3kM7So+BtTt6bgwoH3126mTIh71XWxD5SMtoYxSIxvruuoKgzEyeQKdBlUd+Bg8e7KYYCKAEQYKogtn79OnTIy7URxB/9dVX5f3XP6y3MhFuWw877HDp1a2fnHvmBc62Ll5cp22NF3pMlBBAKEjXQJTYLiUcgEfIRaRjG+5zeB3igd+kPkBxIpiVV5RHTNWpt6C4MLrHQM2m3r+zSBy8CzE21PFdu2iruVZW/bzFko9mgtUL8+SLVxdJ9wE5Mv760UG/27611DUr992pk8z9YIVNu7Qk8kHvhHhTH40FgvfixYtdAyez7VDpDC8Ifn4/AX+HdyGSB4Kg+s7b70luu47SJjXFDGpakRJLv4mYttUXRx97/LE6bav3vUoKQnkoeB0ioITA60NBtQB0vvV2v4X0qNrhR6TP4e/0c7xqUl1QVVkVskIo3Gyb9XiiIW+t9Xy0NM+HEh7WS7JoHijc4vTYKdziqJaKlT9vkalPzDf3e8ce2dKpVzvzelmxTbu0GPLRnMAM3Ju6IPD50xmJqMxg9g756N2zn6xctNas59KubY6rfqSmpiRkW72BlKqXRKxRiOrAd4QK+GyTvg458RKheM2oemwjfU6s6aJo8HptIqW+XPLhmXWHAuSkMdICrVb5aKDjq+fUko/mg6KCUvd6YWxl4c4V8zfLWw98ZyZnnXu3k6Mv2V0yslLddV7i8fVUVVUbRaznwNwW5wVqWXvTzEAgDVdJ4jV8+n9PED7ttNNCkhTKPgmoBM68LXmmGqVTp07uMs517XIacls9H/XJ5x/JSSeeGte2hgKeC+Av7/X+XahjEu4YhkO4Y+v9dzjFJBJC7V8Q+YiofDhBriSK8qEpFxQt836rfCQ57dJQ5KPCJR91KYu3aHgoUeS+VsVy6bebzNg4YI8uMu7Po6RTz3aS7llTqyyO1MunLy6U1++ZK/M+XCUtDVb5aAAQ0AiqBDNm2ZpSIMAi76tJklk3j7yX36kpkn+jZqgpkvQHf0dgf+mll8xn8V5e81eE5HbIlYsvusQw8q79Iy9xrOCzYtnW88+7UO6++0559sX/yYH7HyJDdxwa87ZGKk3Fs6HqDR4N9Vx4VQ++h9+PHj3a/Uz/d5CmUQWH7Ql3bP2fw/nyGlEjpcX0/KrPhWodPsur3Hi9NuHUIWZDFYG+EigfkdJjWwIpl279c2T90gLzd5WVVZKaaucSyUm7lDfodxqPUFG5tG2f0SDfa1F3eFUqnrfLzZTt+Y4assPuXSQ9sIo44y/2AFo0QD7a5kQ/txtXFMoPn642zzesqOmS2lKQUp0IrTyBKCgokNzcXMnPz5cOHYKDZUlJiSxdulQGDhwY9wqqTitwZ+bf0uSrcOAmwPSU1S5dKghuZZWS262tZGanJ+TzCzYXmxmi3lRp6W2kc+/20hSAvEk6gn1X1aexQD6YWRHVLpsK1spOuwytdf1yrv533efuvy+656Cw5+n/27sO8Diqq/tky5IsyZIlucq994JsY3pzoZgSgo2BkEZiO4WEVBOS8BNCgmMHCCGkGCeUEIqx6d2mGzDGBdx7t+Umq1m9WP937sydfTs7szuz2r7vfJ++Xa1Wu1Pee/fcc8tb8dwOaq0++pKe9Ajc8ufzHC1oCs4A2fzA5pP0vKBHlrjhzolh/84n71wpKk/U0vMb7jxTFPSIjbmkYI+XHlgnDu/Q1M4rfzRG9BlRIJbMW02VLVd8f5ToN6az8d7Hb/9YVFc0iOt/PYEch0D26sX714kjuyrod6uE1liEP/ttRnJYYd0YlRw8JUql/giJDpZuYXxZonfa6wODv6qsTtRWNQT8fCZzsbQHBjZbg9GPhWRMJ2EX2dOWK15ASo7u0RYgc5ltQWG2aKfHkmPhPBMJ0Ug4rZe+M17yPjDnd645RmuFSHblo0J7DocPyOqY7vXetPapjnO0dq05rhEP3W+qLEm865s05KONLknDqMaSkQwneLt7Ih+69+/03BEGwMSqKq23DRXw57dN1ckHKmpiREjD8dNjk6fSJFrwqnaxuf71eryfwfHjtxZuFM8vWOu1vwg3GMvrlinS9QVN9Q8ILeok0h0J8oExIn9PvJCP/ZtOimX/3iw+enaHSEZ4h13q6T7ya7bkw0HOx+evaV2pi6b2Nshwos3xpCEfCJ9zDJ2NAQwlPHuEJBIRTARw2m1cJpw26++jcJWNwWQiw+SD3h8jxA45ELGy264X4XOqfOh5HyWHquj3E3rMFwsXVB0A5XscmlG9PsKT/AkgpCgTyHDAbFg4byDWwcnPctO7UAIN91a9usdnfsSKg2MmjFAssezC4TOHQbniJZDy0VDXJMqPadfzjKl9RPsO2hznkFyiIInIh2/oAYMAnSdDIRnCUGCCxIKnbSYCIB4pfO4OycFp6TzsDDiTG1xXg9idbqGFtMZBr4pwAcfA53769OkYC7u0OAy7aOW0vHlc+XFt4eFFCQsS8lnSM3XlQ4VdQkpczQYi3F6nXF0TT8pHtU6EsYaGQ/Vc8+Z+seb1fWLrJ0dErMG8xtVCKdZDLpk5aYbD56t8+O/1UaHPdZ7jOZ3a0++VJYp8RB3BGhQz+QilNI94LQYHe6WxAF4LiHi5DLvIBpNVENuwjkTsmptaiKFXldaJxoboNNSR72e0lQ9ZOWoR9iE/n7BLVSMRY0b58RpTyCXLdRxZwRmMe5Hi6WIcbnInKy1y/kCsg/MbQJLNYzgUKNeVlVMnY8/wmu8RCKNdvgeQluEs7FKuOxgdu2TSI5OPigQjH3FVapuWBjbZRhQXF4vOnTvT7066dTKaTqPioFnUYk1v2yxqa+up5XVTc4qoq2vdpThVUUuf3VzbKNLroltdwairr9OqPhq140G1xem6JlFXF5hz1tZiLxJtktTWCNGS4ltJ0dCg5YPUN7QVjc0N9F2VZfg+vV9BVUrIKmvcoKEWrcy1haFZ4N5GrwMurkljU71oOt0kKk6VivrqZhq3ZqC00qx8eJEPfUEq1eVt7piY0QrlA6To3f9uFR3yM8TEq0PTUC0RwEnWUJVQKlnVUB92cmdWvuJF+WBPHzhVVicyskM73yv0REtUicS68uFFPnLT7MlHgLFUrjsa6IwKoEIxEZNO44p8gHigzPbIkSNEQNyC9teoaxZp5am0sGCBN2TtunRXRMa3MqRei+enCFFe7a4MOFzARIDn3746jZKmMTkQfimr9mXlZuC9rAylVaQaiY0GWjwthXHtoPzwtWRY/l8EAM9C9l7LazKiSj6wcMLQlx+qF8c2N4lzJ7WxNT6IC0OWRexYbtmMsAvGmZxsSu9vBfkoO1Yjtn92lHKCxk/rm9R9QrZ8XCw+f3WPmHbrGGP/DUjeKB/H3A6HV28VdkH+FMZMTZzkfMhKL5537uW/hNQNkGuDUIaZ5MQK+B7ldG5Paq9MPrKtlI/2nPPhXxHm/BkmHzmdMhIy7BJX5AOA19i7d2/R1NQkmpvdyfobPzgkNr5/SAws6iwmXtNPLPvPZmrkAlx562iR21m72W5xeGeZWPnKduP3Gb8eJNLSo39pX3xgHUmDaO+LctjXn9pAE2DGr4YG/N/X/r7eiD0OHNdFTLy6n4+BX/LEGno+87cTKC67+wtth1tG3zEF4tyvev9fJLBu2X6x9ROtRwNw/W8GG81+Ig2MjVWvbqfxUHlcW0iRvMjVV+YySyw46BGAagtZ+UAjMdxLXpjy9bCLUe0SRMIpQmMcnsOimVOgeVjJCJSLgiTu+eKE6NRL66/RPtvTIybsOR/6/c/rnilKDlbFhfIhV3bI4ylUkI1tLJIxPvfOPbOJfMAB4GPOtCQfzsIuFSblw8j5SLCE0+hbyGA3k2vXjn7cIDOrvairOC2qSpqoyVN5cT39DjRUC5HRKzgP+dCmSuNzgObaFJGRG3lvG971B09tE7ldMkXRpX1E1Ykm0VB7ms4b4Q8cI37S2qX5GD8zyg/Xi/oa7ZxOHW/0aYrVWFNHn4Vcj6zsTJGenu51DYDSA/Wum8HZnltLC1UlOSERlUcbvY6lpaGNyMiJjvrRWCXoWAqGZBnkA/F9JKRZxfyRywHygZyPVNNijnLbCn0BgpECjGqXIIyjrKygpDqZyQcTvZOHq0R2XrqhfJAsFIFqIiafuP8gHzBkbvYAiQZqKhu9qttC3euDxzoAYsh7p8Qa+ejYLVO0SU0Rp5taxImDVfbKh4OwSwvUTZucD4xRK8clXpEYZ+EQmbnpnr0TWlq8ytlYLnMLfM6+jSVer0VLIkRZ5pZPjohVL++hjH2WjzHoM7JSeR0NuGU7EkVlGd8qiZbZO9g8yGCG1Aq6/9jOBoMPVQb8js+PiUd+/CF5qIFg3mEyml6kp+Y/zahMsSob5NewkAGQm/k8uJQZPRWw2KOxGCe08Wc2BBF2ke+r+ZolE3BN+fxBPvheIH8hUtVE/J25XdobydvRrBhzgqryOssdXsOhfOAeOdntOZLgkFBmTrrI1MtqOV8DbdbNcFLtUlPZQKkBWKs51wNEhsjNaT28nyBILvKhDxDcYEx2MNXWko+Th6vJa0RsuPvAXO2zojRAuHsrBim8ZLb7MFZgyx0KMnw8CiuYj9/q2nDckmvXuRYdGHd5H2PBDlV9/r4NGsHbvupowPeyIcE9CXflAPoQfPjMdluCwwsmxh550hZllV6ery61ytUuPK72bjhhvIfzkwxCE4RxlMM6yUw+yKvWq6KQ1FepXxcqZY5QEzeeJwj1sCoW670+zOtEqJUPc4JlsGt0uMBzHvfLUDL1Nde62qVtwLBLua56YK1m1QuhP1YlEynvI7nIh56BLCcGMYIlDKx69ByaZ8hk0WKn3PAHOLFfy2UBOFTBTBoG0x9YuWFCofWbaLZVPgA+d8TLu/TJEdn52uQrPxaaycIeBVoO+ysXbmr0JKl17tMh7B7k2jf3i00fHhZfLNtv+Xf+7vY5aUYlgKXyoZMHjvPCGLK33WtYvtdizJUuXspHq8MuyUs+zMSrWN+rIxrKBwiPodDGYIWH1TrBhhZOWChhdpJijXxUM/nITTPuGSNLD93JcFIWX84hl66eOQ54en0kzjxNSuUDCzsUi1CESg5t1bZd7zOqkzHgohV2KdN3OwWO79c6YmLTN06ay9ETajmR1A48ybFJHKsHZi+MJxDHMbv1zxVX/GC0uPx7o7zICE+m1oAqRfTPwfeWFmtxVSvwApia3tYw0sEkq1EZ6uNbAraNZrUJeRr+pVmJfJiUD3lHWyzkuGeM9KxUIwGSwZUuQFr74Ducyp5qqCXzeIK5hwSPNa2Jm3Z9G8Kc81FX5amwYS861pNO2WHr1j/HU10Xwg7H7OWzYhBr5bbG3O4gKR9Ye9LaGMdsnfNhH3bxkA/v/KtcveIlkXp9JBX5gIzFngxXubBhDoZVw0Dx58D4cpJRdZQ2WZI3zWNjyBuPeSkfAQYwGyUk3hmEqsyGfEiltP1GdzLkQYN86IpFawDiI5fxFu/UPFN/oQT0rjAW8QA5LlbAcW/77ChVSNkZAUoO06tPMA6sWssjKY8XqPZZ1soH9/hAJAUyvxzCwnnwtWRwgzFA9szd5NeY48fJujGYv5ATtrRPi1DYhckjCKqs0MYy2MmC0omxizEVKrUGcwm7ZgPdBnSMOeUDyi9KgQ3lQyIfcCCs2jYYpbZ19nOVyQeHXxko5020ipekIh8ADxImDdguO1hWjcmB5CEkBKL6wJAfozBJ0BtAlimROCezbS/yEVD58GyMxITKh3zoSVNWDF8OH3DZWGtgVk+Kd3rv8mplSGC0s5h8BKF88J4q8rU0A8aBSRgWIiuiZYRdOqSJdF35QD6HDFZC4GWDDMvJuyBz2fkZXvvn5FuEXaDmudmjCF6b3P0VpC1WNgWMNDjHg3OiGBnZWj+giIRdpDFgkOZYz/nQ1zlcN2PtCxGJxRqKnDxUt8jKSqyAc7mgckCp9CIfFsmmABNZzLtmm7nK2yjkmslHArZYTz7yoXsVJw5q5KNL3xzDkLiVDE8c0IxSfmEWNWjKzsuIWs4HDJ/sebNhkSV8ZNIDICn+DI2hfHT0KB/miW/O+TCDvysUOR+GDK4b7+Jd5bbHb5CPggzKswCCyZKXCYcd+TBvpmUOveB+1HHCaU4aJRNaKR+y1wuYlQ8swHw9kfXOTYfMYTU3jbD4OvF3gTwla4v2Kp18QLmTkZGVFhHygXwqJo4YAwZpjnXlQ1onQr32sZHNLsgwPjuWyIehaOZoXbbZrtglmxq5d7og0mBR8YIKRVY2zMoHz3+o28hrSwQkH/nI0QYGypkAdOTD4k2lXC4ne4lOYDrrMXnuDwAvJtIDhPM9QIRkyMpErs6eYWT8GSp5fwJD+Sj3n/PhT/lo7U63TGDQ7AwKAO6TnXrjCbukG/c6mEVczgk6KakgMrjbqDnPhgGSwRwpQ98kil43Kx/6vWBDxyRF9sZZtUIIRq7zx8LnqchodE0+cJ+YgCRrxQsrH71HFBhEzifhNIzEjMkoSCbma2vGbaRAXZ2ldQLzLZRjiMkHch1Qph5r1T81lZ4N5OixQ2DygbGVpjuDDRbj6VRJHTnAUFPM6gmaCsK+IPx8cIuWZxjvSELy4d3cCTeUX3MbLmH1pHNvraoCC5WRoBlhls75HlBymAQB7SRykJrm6Q9R7qfiha8D5Xx0tPY6jLCLHsc0I6dA89jh0bU2DMXhjIIe2aJL3w6G+hFI+cjMaefV18UNZMJRYqd86IoM7+PAoTwGGw+QDihjdgmncqUDIG/FDeVDJnNysikjLYheH3yd4FWyZ5mMSacYFzIR4+vMyb5GE7eaxrCFpfj+4/tkLzqWq10whrlVQZaX8hEq8lFnhBuiGc62A98bJoqy8mHVYMxJl9M9X+ql9N2yvEgwgN+5fxK68CYCkp58YGDz4HZLGLibXSd9PwMsHHYJmpEqswVDlhdQc05GboDEJUh/nsZYvjkfCEFA1WkMoHzAO+ckqdbmfbCRhxRZOLCj36RTj/LR3jDi8BY4OcwJ4OXKHhyIHToL+hyXTvgGndnNIB9y6M6T76EZMEP50I0NerHguHzIh5TzwcrHkIndROGgjmLkBT18jsPTYt05+eCqIJAbJjjJWG6LhnsUf0/RyDbngMFIgDDytYWhtYvTtxZMRvn+G30+KutbrRo6xd71J8STd64UR2xIvW05fk4aqZFcWh+qclvOX8MawioA1NpYCTnwGsmh3fYOlA9/5baVJbVi9Wt76fmoi3znODCgSCMfezeU0Dod70g+8mHabZDilUGQD0iAkP+R1FzQ01MKmR0t8sEbjnX39t5k5cO710etPaNv0SRgSIlyzseG9w+JZ+/5XHzwv+0Bcz6Ajpz3ESDBNVAi7SldgsV5wQADh7eX+SzMWJh4UYRBBTFCya1xXg7BOR5U9prRlgyPVe4K56L0G9OJci9AcuReK0aDMX2BkpUP9Id55verxDuPbTFCYPB8rXI+WPW59udFoudQreeHjGBCA7JCxIYjGcMuXFGBNQBGFNdZvleUU6M7oeEKvXDYjb8Tcy5NH3dH99gnV4cSa97YRw4JHt2U2fLaGXrlg8Mu7U2KckPMNRgDsNZwfp3Vjra+jcaaaU3FWgOHBY0KoRL3GNxRDD27u+X/ouoHawOcDKx/rUEsJJcntfKBNsbwNniwuJH1WGKHQZT3G8m2CVOEE/DKWR1AJYRXHwgp4dQr6dSGEPBxZ3ZMI6mPFxdk3q98cRc93/H5UVGq55jYVbvIJaF713u3n3e7CGGeUEZ5bhqRDxAekLvDJvUDDb9ASHA/+Z56ym0bXIdc0F+joDDbMukU5IsJJq459+KQQy+swrB3ZCgfNY1i3dtaU7I960+IEwcqvf7ORgjEiQmJPwSTFCmXU5uVj2N7KwNufhVKfLxkp3jx/nVh3z8lUGk20FVPQOffKU7P1zdMO9ualS8oLn315FfzZo3hAOYYJ0sf2FrqiECYG4zx9ToVAqcLhtFQPjq110JRQarT4UoQhvoAyGvt0HO6Uwi+kx6GtwI7a6dO1oln7llFztyin3woDmwupWTyC28aYru7ehsp9NKacQHVZMm8NbSLcyTnuRlJSD48khjkPCwudhUd/oDNn+SQi/GZUWg0hvgovCR4B9QXwkv5MIddMv0qH2xQmUTBcFJCbosWvpB3QfUXdgGGn1dIBO/A5pP0Ewzk7aUxKZG3MmhCV3pt66fFXqWx697SDPp51w82YqZGS/0glA94waxqmfM+WPWAJwKjgV4HAC/iIITYph3gUBGTCihL6NTKzw9uLfMyPvheHD8Mod1CJCOYnW3lkmQ552PbyiNi6fw1Ytm/N4tIAPdt/bsHKYy26aPDImrkQw9voVPxlO8MFxffPMR4T7hbrHtyPjyK14Azuhjx/XB7qV6GrMXZFgbG1vH6esePUINbGxpBh1mog+jLxM6SoU5HMOl01St7xJO//dQnlwtzBOcJxbD/GRoZAC6YOVhc/+sJfje/5PXyy3cOGGSW19Xxl/f16uFjBf6+vV+eCLqh287Vx+icMN+iuVFf2MjHnj17xIIFC8TSpUvpsbzcWSwx3DA3g5Ef3ZAPc7Ipw9NorD7iyabo6Amj5Z3zYRd2qaEJDtkfkwwLKxa5kkOnvK4JBierCCA3YOYy/IZdumaKURf3pOcfL91lmTfhNNlUPqdhuiy5e90JOm5Mwvef3EqPCIFwbFQOs7kpt+VKl049skUnPQfArHwYYS59seiit3KHEYX6smvtcSKFIBzwiNijlZUicwiQVQ4Qgq//4Wwx7YejHR2v251t4e3wwkc5H7znT0mtWPXqHmMTO3/N3EIFuS39+vcORTymL5MwAGRv8IRuBkkH5KTTSCgfQK8R+VT1gOMzG79QY/e64/TYtZ9GoLd+esSH8EANkV+TlTM69mxPNde2lYHJiz98sfwAPSL8wOsXr0GRUj4w39e+uY/m8Bv/3GCEWbCG8fGdMaU3zWk34PWySrcPk741TMz87Zniqh+NIfIRCD2G5JHSiVwlEJBAwD1b88Ze8e4TWyi/DGsTO2ljJ/cmZy7hyMeMGTPE3LlzxfTp0+ln1qxZIhaAScJeMZdwBUM+zGW2vjkfdWL/5pNi2b83hXXxwIBiD5slwA55GUaM1Kx8cBIoBu9bizaSl4M4Lxj+0j+todAFwB4Hfa7e1GriNf3FiPMLvXJc7KpdGBOu6EuLEow1Jq1btl5hbC/tOR5UvKCkGAmAO1YdFR8+tY0UB0zsC2/0li3dtqrG5Dypt2/P75El8vUcAHO5LSsyfM0LB+WRbIr3ffribiOsMuaSnl6ekKF+YOH55jCv/I4M3cixMfTnQclIM4VdcA7wahDK2LzisE9yGi98uF74YcMLb05OGAQpDafXjXyLnWs0w0cLamWD2P5Z6wxXa5UPK4S710e9kXDqIfK4931GdvIiBwDux5ZPisXat/ZRPlRrAXKDMBsSbid/eziF+hCSPbq7wvi+FYt3iCfu+FS8tXCT0cwQ5FS+bphz46dpxvOzl3aL2qrgcjMw9+izU4QYO6mX8XqwRQHB4tMXdhtl8pgvb/5rI4Vb2KnAvB12bqHrz5Wdjw75GaTiduqZ7VPmbQeQHU46x9YPgTbu3LyiWKx6ZS8Rwo+e2U4hcKxdmPdWyetxTz6gesjo37+/eOedd0QsAJ48L/g8oO16WVgBCzkMC5eCmcMuLGFDpn/94fW0uL5w/zpjA7pQAYsC2Pnzf15LkxXhjWG6h41BzB3yzMqH3L778PZykjZhQOEJw4Djd6gVRVN7G/9z8c1Dad+WMZN60SIDxs/wF3ah78tsJyZe3Y+ef/bSHvHY3I/Fu//dSjFTTGZezA5tK6Uwyob3DxpJmzCirOrwVvN0fimec/34uZ1iyydHKCnwwpsG+2SauyUfWIzRAwZEAmoLJyBiAZInuod8ZBmkc9I3htHzL5cfIPUEeSojL9SUHwZ7hyBP2DCOz8NMTNwgQzeOMBggHS8/+IX48OntpFx88NR28fRdn5H3g3EC2drs7aOviNxBtejS3nT++P9DrUxs8weEW3CPEeqYME0bI18sc09QWwM58dYO6aYKBahoa97cJ95/ahuNWzNBw/HD+DpV+qyUD4AVPCh8+A6oQu8+vlW8/+Q2mku4z63tBcLEBqFB9JAZqH8nzg/zcMXinZRozqWgby/aJF57eD05L8hz6jfGozKOurAHzReQtM9e3E2vNTY0u7qfmDt07mM7e6mdkSQfB7eWUpgYtgLqIww1En8X/vhD8c7jW+k9oy/u5dg5sFOKx0zu5Vo5AUDysGbj3iNfyg5welc859mbCttFvP+/bca98qdaRwJh+XYQjfx876x8/L5u3TpRVFTk9Xp9fT39MCorvRs1hQMwSMgB4BIuHtgwOs8vWEPtre1iYZiQbHgGT+zqs2DwZ3ENPOKC8Cbf+McG0WekNbu1dS6lP8hvaWlGeKTKU+7VoZ24fM4o0V3PLQAmTOsrdq4+LnoN962OQBIXFg8ASsGQiV3Fjs+PkVoz/LwePuXIcjkmMHB8F7EZ8UI9YTcQkPsBgrF15REK9Wz79Aj9wMBRJ1aL88fkwjHywmze32Twmd3Eyhd208KGz5l6ywgxoEiLk8vgc9m/sYS8FzOwqOM6otEUVCQ25EgixcLQtr2WRwMj9dYjmwxDdHhHmU/CGY4JuSCrX9cqBkZc0MPn+mBBBckbfXFPjUSdWyjWvX2gVeSD1Sx8N0gHAMke4ald6zRPDd4PA38DuDEUJRbnpdM9wuOZV/YXjQ2nxcb3D4n3/7vNJ7ToBri+cvdUEDJIvcjs50qOM6b2Ft0HdBSr39hLx/D8grU0puU56DNH9BeMl1vM72uxevD8X4t37g7vSeRPWQKxA4E7tK3MUB22rCgmIom+Ns3NLWQcoRzQ31M8G8WhFNMqORtVD9ycznz/sV6AFOKavPLXL+mzsfbgfuEeIm/ouXtXk8FnooO/YVxhbvpLF8L5Nzc2G+0CeO4MP7eQvGQkQD69eZX25hQhRl/UU2xacdhIHsecuPLWMV4GGOX1F9w4WLx43zpyCJBLAiLCDg7+J1AOEztpYyXnR15XkR/1+t/X0/FjXMGBwefDCZIJdGvA92PkhT1E31GdxGWzRopl/9msNQ083UJj064cNhDYWUvPSqVrHQxS27UVl3xjmHjhz2tJKcRxWZGYY3sryA4heRn5Y1Ay6b3t2ojRl3hUpYQiH3b5HaWlvp3Z5s2bJ+6++24RScAAIGGUwwkYEFhA0Hfh6J7A5AcD59zrBomhZ2v9HWTAi8TghOE86yv9xdgpvcWHT22nOOq+jcElXdoBRrfnkHxx0deGeJEDTljjpDUzYEwgtQ4/t7vheduVd1kBA/3aXxQ5Soak42zbRpw7fZA4+9oBonhXBXlQiFey/I9FA54njCEWFSScMcFD2GhgURfqRCsDC/qoi3qKXWuPicm3jBA9h+RZfjd7T9i7h5v4+EOV3g+kW79c47Wu/XOIfJjL22Ac5RAUMOHKflQ6eWR3uZdCxMB1gNQKw0LH1yVTnD9zMC0K/gygP0BBufonY8XhbWXi6N5KGn9nXTOA8nvO/upASpA7sruCQoWoiuIENw4pATgPGDkoEFicxl3WR2z9pJjOO5wluMiVwfFjLI25pJf4/NW94vi+8Dsg5rAKlxtbge8L1gf88HHjmiF5T37dCy1aWbXWx8Pi7xKoZF+vrGJgXYLhgDoBwsPHeunskaTWvv6PDUR0WqsGIETLKgscmGk/GE1EC500T7e0iEu+PlQMO6eQHJk3F24kwgHiYbWHCRQUrClY7zhMhfAo1ltO0g8EVLTJ80/ezwjzJNTrqBWgCnAYCef97T+fJ+qrG2lfJqw9nAfkFn1GFVAotOiyPl5bX7gFNjIdM7k3KUX7/VwP2AWEd+E0YU0CqUTo3OxgRgMpLWEI6iLBdPny5fTDGDBggJg/fz7lfwRSPnr16iUqKipETo6WABVqwNM9tq9S9JWUCLBoTU2op8XC7qq0TU2hBUFuBGUG9d9vaDYqIHCJcdPlRdyf3fYy6jbvg9FC7gNYsFsgcQ7GqPfwfK9W3ZEEldMdr6VJDmMpnzMWGCy2SMhEEpw/aRKf448E4e/7NpT43TgQ3in2S8FijxwAfH/vEfnGAgOZHWEieSM2AISVK1niBRjnCNeB+OEc2RPDnMDrCIHw9YRsi3nSWmCRxX3GpzbUNxH5oQ250tqS4sEeP7x3kFNcbxwnX2/z7TXut8/rnheN/zG/1fRh+BVk3F+VAY4FxJUb1SHcwJVImEsYX1A9WAmEoYSnDuOLc8G1xaPVfh64NnBYQJJ58zAZ+PwDW0rpmmEsY85yaBcJxvhuXDeex3gPvHNcO3kNs5oiUKDw/TheOcTBwDqI5GT5uEB04Cz4U+mg+sC5gZMGkgSDjZwvJ5t3gtBjfbUyjuhqjLJgHhfUx6ddGwrtyOMlFOg+INcIucYqTjefprC+XQNFXMt+Yz22CtcJRKXv6IKg7IYTwH7n5uY6st9hIR+PPPKIWLhwoVi7dq3xWl5enliyZImYPHmy3//FQXfs2FEcPHgwbORDQUFBQUFBIbRg8QDRD5CQiIddQDBAPswYP358wP89dUqrDMEJKCgoKCgoKMQXYMejQj5Q3WKufgHxgKIRCIWFhaR6dOjQwXFOgVtWlgyqSjKda7KdrzrXxEUyna861wTdqPHUKbLjgRC2WhuEWG6//XYxYcIEsXr1avrdCdq0aSN69vQuTww1cPMTeQAk67km2/mqc01cJNP5qnNNLARSPMJOPqB+IMEUMCeZKigoKCgoKCQvkm5vFwUFBQUFBYXoIqnIR3p6urjrrrvoMdGRTOeabOerzjVxkUznq841uRGWUlsFBQUFBQUFBTsklfKhoKCgoKCgEH0o8qGgoKCgoKAQUUR3WzsLnD59WhQXF4elz4eCgoKCgoJC+Pt8oG1GXJEPEA/V3VRBQUFBQSE+gWZqgfp1xRz5gOIBJHonOAWFUHobx/bsEvmFPURae98NwhQUFBQi2cmV7XjIyMe6devEO++8Q8/RtXTRokW2LdPxXqCoqIjaq2OjGTwPBA61JEMnOAWFUGD/xi/Fq3+6Swy/4BJx+Q9/Fu3DUVBQSHKkOEiZcJVwCuIxd+5c+kHb9EmTJtm+FxvLjRs3jg5izpw5Pvu9KCgohAalhw9qj8WHon0oCgoKCo7gmHxAyZg3b57xO1qm4zWoGlYA8SgrK6Of5cuXO9pUTkFBwT3qqqrosfZUZbQPRUFBQSG05AMhE4RZGAijAPn5+bb/A8KhSIeCjJ2ffyre/PsDorG+LtqHkjCordJIR92pU9E+FAUFBQVHcJXzIW8Qt3jxYjF58mRbcgFysnTpUiM/xC70Ul9fTz9ywooTNDc3i8bGRjeHrxADWPPmq6L86BGxZ8OXos+osSJZ0K5dO9G2bduwfDaTjvqaatHc1CTapsZcHrmCgoKCF4JapZhYrF271vY9s2fPNogJSMeUKVPE7t27fd6HUM7dd9/tKrP/6NGjhvKiED/Avet/yWVCtAhRl5om9u7dK5IJmA/dunULef+auqpTXs+zOuaF9PMVFBQUYoJ83H777QHzOJALwtUtIB/4HT9m9eOOO+4QP/vZz3xKdezAxKNLly4iMzNTNSKLIzQ1NoqyVC3Sl5nbUWTldkwa0lVTUyOOHz9Ov3fv3j2kn1+ryEfI0FBbQ2HBwWedJ4add1G0D0dBIWHhmnwsWLCAyAdIBKsPZhKCRFRUwiDZVIZVfgh2+XO60x9CLUw8CgoK3B66QpRRf7pZtNNDD3jMyMgQyYL27dvTIwgIxm8oQzCy8lHrMGypYF+2vGv1Z6Li2FFFPhQUwghXpbYItUDNYOLx3HPPGcRDrnzB3+fPn+9Voot8kdYmn3KOBxQPhfhDs5Sjc7q5SSQbeNyGOldJTjTl5FOF4FBTUUGPVeXejpOCgkKUlA8QixkzZni9BjKB3A7O3UDvD/QAwevjx48nlQTPkeuxZMmSkB20CrXEb9iFcbq5WSQbwjFuT59uFnU11cbvtaripVWorawwHlXyroJC+OB4ZkHNQOzaDmZyAYXESUdTheRBc2NDUpOPcKC+uhpJJcbvqtdH61Cjkw96XlEuOhR0iurxKCgkKlyFXRRCA4SokDfTWiCchWZujzzyiNdnQ3HCD5Sq1lYFhfJYL5p6mXjy2WcdkQ+cE74Xjwj34f/x3K6pXTQR6mvuBmalQ87/UGgd+ahWoRcFhbBBkY8oAK3nZcJghlPjhT4rM2fODLoFfiSPFcdx9RWXG7+DfNgpaSjLBpA3hLAe8oWQrIxeMa1FOIhBqK+5G5jJhko4DU3YBaguL43qsSgoJDIU+YgCkAcDI8ib9MmAZ49E3mDgtgV+JI+Vk01ThCfvwUr9gHoAcC4RAyE882tu0ZprG8lr3iryoRJOQ0c+TNV6CgoKoUPckw94z411dVH58ZcDYwcYcagVUC2sknDlKiG3CKYFfqSOlclHm9RU0UYvM2XyAamb5W4YcjuFw5zw7BatubaRuuZuYc7xUC3WW4ca6XqqsIuCDKz3rzxwr3jhT7+jRG+F1iHuU7mb6uvFQ9/0tH2PJH78xFLRzmWvCnjFkOdhYGfNmkVhDdnYr1mzRpSWanIvjD4SffE/+Bs3a4N3bbdLsJsW+JE81iY92bRNm7ZEPkA8MIHxWHlCa7518HAxGW+7c8N3yN+P78J70b4fxAKvIU+EW/nj+9EMD8TJ7njtPgefwbkuOG9/3XxDec2D3VQuKy9fVJeVqoTTVhoXOWylwi4KZlVs56pP6XnJgf2iS1+1U3tSk494BQwWPHkYOjaqeMTPgAEDjBADDCh3lGUgyfTdd9/1a+CctMDnBTdQCWgojrUNKx9tNfIBgHgwKQFqT3kkb3/g7+FzA6FAuAZECcfEhAPAI8iFv+O1+xy8DuLhVMVwes1DiTo9zJLXvVAjH3oY5sjO7WL1K8+Lc2bcJDr17hux44lnYG8cuf9MlQq7KEioLDlhPC/evlWRj2QnH6np6aRAROu73QDGGz1POIET3jaMo+zRmwHjZy5Zxv8hd8FfDoSTFvjoY3Dy0AGRkd1B5HTqHNZjnX7lNPq9Tao3+ZDLRLvpXWvl1vwy8DqIAJ4YLWYAADSGSURBVBMCOQ8FqgWAzrdy91ucP6sdVsdr9zn4P/4cWdnwByfXPFzVLnnde4hDWzaJ+qoqUpTWvP4S7SB8fN9u8bV5D4r22R0idkyJkO8B1Kiwi4GGulqRlqF16U1WVJZoCi1QvHObGHuptqYpJCn5gNfuNvQRLcADl0MXMHzmcEYoKjOctMAHsK09CEBddZUP+Qj1sTabwi5GxYsp6fS2W2+l77Ay+Dgmfh3kRCZCbpNR+Xj9fY5d+Kc11zxcCad53QrpsaXlNPX+KD10gH6vOH5MvPnw/eLauf8nUtrEfYpXWFFjqhSqCjLsAkK/feXHYvxV1yaEwd61ZpV4+b4/iIu/8V1RdMU1IllxSlY+dmyN6rEkAtRqFEXAkNpVksgJn+a/wwhff/31lobfXwt8Mzjh83RTU8C+G6051hnTp5PKAlRWVUnko8noepqelUWPd/z0NgoFmct75XO0+h6747KD3fHKv9spJma4ueahBodZkPORpu8fg+ZYZUcO03Nc671frBGfvxwddTAelQ/emA/KRzBJ5SueeUKsXPq02PLheyIRsPeL1aRQ7v3Sfzhxx2cfi4+eeozGGxybRA67YO8flZCc5MpHPAAGDYmMMGbwsjmkAAMLI8VJkvC68Yj34m+cFInf4VlzUiTCH/g/GHYkOAKc5OivBb7T9t74rFAea2ZGhli9abN45Y03RGpaujj/nLPFgB6FWtKpTkrad8ih31FF9MoLz4uH/7WQvgs5GpxzIase+B78HX01+JjN1wNhGlZwcDx2x2v+HNwvORHVX6gp0LYDkVI+MrKz6Ro21NaKo7t3EtnDtb74W7PE8kceFuvefEWc+ZUZamsCP+CKK+TIwLDgGkIVdBuygvIBHNu7SyQCSg5q53Py0EHb97ScPi3efPgByuFCrhFC0l+9/S7Ra8RokSjgxHhZ/Rh05jlRO554R0pLMNQ+jKisrBS5ubmioqJC5OTkeP2trq5O7N27V/Tr1y+pdkQNF06dLDHYe26XbqJ9h/DkBZQWHyKjmJmbK3I6daEFvfzoEQqXNTU00MJV0Ku3qK3QSm6z8/JFdn7i7VocjvG76NZbaFG86Q/3i3cf/Zc4tmenGDXpUrHx3bdF5779xY2/XyD+9s3rKRwz+5+Piw75gduFO0lCTkSsevE58fGz/xUjLposdq/+jMbpN+/7u+jUq4/jz2huahR//fp1NKa79h8obp73oIhnYCz8/ZYbKBkX+NHjz4m09r4be2Le/nPW17wqr0ZPukxMmX2rSBT8746fiGN7dtHaVFV6Uoy/6qviwptvEfGGiuPHxNO//bnI6dxFfO2PD0TMfpuhwi5JDDnUIu+7EkqAdOAHxiwrN8/I+6Dv1IkHkJrazqf/R7yjoa5OnNi/N6wtzznhVFM+NPJ4eNsWeizo0Uu0S88QBT170e/H9uwO+Hnwbhd+7xti7esvi2RVPjJzcsmABtNorPzYUWNMlxzcH/djGQ4KEw+g9PAhvyGrjKxsMemW79HzIzu3iUQCKx9Dzj7fqHiJR1SXl1FoFj/RhCIfSQx5YZRLXkMJTtpDSKBtu3b03CAZ+iKNnUORDJlivN4ccPLQhmoxjtrKck2613txhBrwshvraul5RoccusZA6WFNHs/v0ZMe4YED8NoC4cCmL+n6olIm2cAGtD3Ih56zU13hjnyUFWu5NtxYD6pfPOPkwf3ev+tjy4644dp1HzTUCNc01NYE9b0IFb583x8NIhdtIIeFe+gMPecCeoTKKO/UHS+o0UlHZm7kqvKsoMhHEkM28tyBNNTleQ01NaR6ZOpJfDL5YLRtl+b1uj9vsbG+nryx8uMeDzNW5er6Gm3h5WRbGScO7BMPfWO6+Ojpx4P+DoPUpKSIjMwskWEKm0H5ALr008jHcQc5CNV6Ym+NS6ObcMpHR1Y+3FW8mMnGiX3BtdlH4uaTt98mFt36HfH4z39Aiko0gHFqlc/ij7ghbApJH6E+5B+5RWNDvdjw7lti1+qVovzYERELwJoDIKm764BBdJ6Y107mVKyhRpEPhdhSPhqDyuz3h/rqKiMkkKqrHgCpHFJOAf/NCfmAtw+AeIDcxHLnXT4PPmYZG955i7ypL99+nRbbYMCeGKRuXNP22d4x1nydfLhRPph0MAlJJnB30/Y5OZ6wi8ty27IjxfSYkqItrcf37w3K0CFpEz1aKk8cI4O/Z+0qEU3lA4TCH/moqfAQN6D7wCH0WLzDfehFDnUhPyGWQi4dCjrT2lU4eBj9fmDTBhFvqNbneJYiH+4R6RxZeNtc0phIaJGUDxhzubtjKMAef2q6d3IlJq+sfhjhmDaByQdXxwCxHHqR4+RaK/nTxrjFteawBsIm+wKUMNqBc0k414PDLmz8Ouq9P7r07Ue/I5yCRDl/4ARkyOWJWC7pDzV6h93MDlA+8oIiYWVHNOWj5/CR9IicH7dAGSeQXdBJDNbzC6qiVNbJlS6DzzrPb86HrBoBhYOHBp33IatN5gqTaJfZQtEB+hdp1XE7Vq4Q8at85EX1OOKKfLTTjVSNLmdHCmDfWBASaTGGITzdrIUtmAg0NTSGhXy0NYVZ5O+kv1soH3YEUw5hwMDHWLGWgXpTrBukicdtyf69XgssGlIFAybEGVka+ZDDLh27dTMUJSSdcv7Hsb3+k05lYxvthLTI7+si53zkBRV2YeVjyNmasT6+b4/rMVpxQvP287v3EF37DQjqOEIBzMOThzXyMeQcjQQh3Gml1BnkI1dXPvS8D7T5d3v+cp5NxfHohJvMOHVSJx96M8ZBE8+h9QphKbs8mFhFTXlshF3iqs8HjBh6KBw/rrHhzMzMsJcEYuLU1dXSY3VVtciITVvnGjDijbrCkNYuTTQ2NIia6mrREsIumPX1DaK5uVk04HvqvIlb0+kW4/ubmk9TGSrtUMw73VZXUyKqGbgX/B48Vp06JdqlaTkjsYLm5iY6foA30SspKRFlFRU0frcte43+hhJOVETsWfs5EVuQhKB6fFgoHxxyYSD0AskcoZcB4860/UyZcICIoAQ7GQAFivOe5JwPN4oDSnP5+qH/w7v/+RcRGqhJHLZwAs7vyO3azfi/qiiQD+Rb4JqgZwfCKNiGAWMOSbXmfU1k4gZ06defnAqEBvE53IHXCWSiFYthFwC9X/qMPoMaqm3/dAXtoRQvqDaUD+1eRQtxRT6Abt20xZAJSLgBubxKTzZKP1Ut0jN9a9zjlXxgkqe0SRHt0tuTzJ5WUUkLTEjQ0iIq4S20CFHZ0OSTZIpFCQ3FgFNNpw0SiXg3whIV9Y2W5IOaP8FI4O0tQpw8VSXSM7XuqLECnBfOr01qqmjTpg15ihlZ1aJrYaHo2rWreFXfGfOcmTeLD574N8X10T1y8MRzXX1PnV5my02wApGPLR+957fxFcifnGjqttIjEVqrozEb+s9k5Xm6nDoFd5VFvgi8Smz2hwRUhF7ckI9K3dvP7dxVKvmNPPko0ZNNO/XsTTlFKNlGGTdIrJl81FTqBk0nH21T24ku/QaIIzu2kfrhinxI15xVoFhprc5hFy651cjHR+Ls6Tf6dYThXIBU5hf2tFzXIgkmyNHO+Yg78oEb3L17d9GlSxfRGMIKDZIG0VzJ5PnDM/3omcfo+bALLhZnXTtTxAow8LG4nXHZVT7GPRCO7tohVjzzGE2mkRdNEeuWPCV6DB0hps75UUiODTLsB39bQJUY31jwN58J9/krz4vN7y8XWfkF4vo7/2i8/sLiJyjEden3fyoK+/Xz+dzn732MvJAB4yaK3WtXiU69+4irfnpHq4/38PYttEgWXX6162tpxof/e5TUjJGTLqWk2x0rPxZnTLlcdB83ThzZtZ0k3HYZ7UXfMUUkzyO5EKEXt+TDCLvo5EMmjlzpwujKFS9+kk6RQyOHtVieTQZ4PHeNwHHYBaE9kMd2aemOy2wRLgHQ5A3zE6GXfmPHOT4WNrjeyof/XJ1wAGsfUKA3WSvo0ZvIB5dyWyfrerzpwkFDdPKxTQw//+KgyEfs5Hzoyoe0B9bACWfRuoZ7DKLWuY/vesV46x8PUvt5zPtew0eKs667wUjKTdacj7gjH3IIxiqXIFgs/eOd5HV/ff5DXpUZdWjGUqopH5XFh2OmsyoWxWX/+ItoaqgXBd26i6HnXujq/xtrqui8OnbqLPK7daPnx3dtc3x+gbpgVhQfos+E55aVne3z9/YZGfT3zj17eX0n7iheb6iqoNc/WfykOHFgv7jqp78iUlCybzdVkow470Kxcfnr4kBpCb0fHkVr8NETi2hR7TlwsOjrwlBYka7tH71Hnk6/EaPEwS0bRW3ZSWMR3fHZJ0bCGgwavCeQjz3rnIdeUGLb2FAn6rjaxQi7eMgH53gw4Kki6RTyPRZ3Nq4yzHtVhHLvChA7VP30HKYlYsYazAmTUNNS26VR/xtUX3Ts2s2H+FUeP2ZUEsnKB3YYBmCM4BW7TTrlUENuF4/yAWLolAS5AUKCIDucvI3z4XnN5KNz7770yM3qrNqse3I+PN5090GoCHmZ7r0byCoPDCWUxGhuHoqWBKdOauRP3oATY6TfGePFrtWfie0rV9iSDyi5+9avM8J7e9atFgc2bxDXzr1L9B4Z2fbzqGrkZPjMCO6+HfcJp60BJgcWeWz6ZBWr3b/hCzI+ZlbPiUbm5wCSjdCO+bUH54tN7y/3qnAIN7Z98hERD2D9O2/6/B2xfbSLtqscMco0O3QwDHfFieOOmubAO37q1z+lTpibP3yXiAhegxzLSbnsqWXnWbdJ7190Jk3WUZdM9XqdF394opj0uGe713xG/QKwQIJ48CLJFQXP/N9cn5K3je8tE/+5bZZhEPwB34N270CpnjAYLL548xW6BpCcoSShnbw8dg5sWk+PA8dPpEe8D94Uzuvw1s0+nwcCICeJYow9+pPZ4pHvf0tsfH+5l+IB4gJDAWJhbgmOxRthAKveDfJ3yQhVrw+MqaV//K147ve/NvIZTpWWiCd+eSvNn1iAOWcBBriDLrFbJT2+8dCfjXbbjFJd+cgr1MhHVz00gWZU/rDt04/E2//6K201gB+uSEK+DZEgnXC47bYaCJi3aLP96G2zaT7jZ90br9DfMJ+hWsjKB4fySkzltpg/vJ7w/AU69+lrVMi4STo159lEO/QCBRCVgFDFzesZdzsFAbEDcl4Q1kYODNqZQ/Fsqq8XL/7pdwYpibTq0aZtKpXoRxNJQz4wqdG4Z82rL/g0fWLDI2erm5vLyM9h0Bf/7lfiv7+8lQw8WC8Wj3/Ovll88darIhLY9IFmeIBDWzZ5ZVxDIlzyh9/Qwr5rjfWkMGTSDjnkrVDeREuL2Prx+wG/+/C2zbTowot+6x9/EY/97Pvi79+5kZohvfl3ba8A9hTs9miBF4VwDE9eBi/+IIuIs/K9OnloPxksPubUtDRxxa2/IBICBQDGDbImexqfLnmK7isrDTJADpBjwUTrVEmJUWZc0YqmRiAGX7ylJZMiPEcGTE9Qw7nAc+U4euEQrU8A3tN75Bh6vl8nJgws2FDknrrjpwYBgcfECz3uFyCrPjfd+xfxnYcWWSoobBTLbQiWmWyEqtcHwmhosY/7guZRwJpXX6RrsfqVFwyvORqAygBCZHjuUt5MXrfuPusD3xeEz4Cju3fYKh/ddFkd/293jrgm7z22kJwXlF+zvA95HuMc48MceoGKxqpEa4BwCOYxFDGed6tffZ4UKjT4wvzG6z2HjjA23EMYtaz4EM0vJhTU7E5/LucdQbnBZ2O+uamcYuWDQ7XRTjrle4K1zByS7T1qLD3C8bK7x0xQ4Wx1GzhYXPOL35LyCVXtlfvvjej494RccqO+f1PSkI8O+QW0IJPMaPJkyo56FuNy6TnAyaacJYyJiYl/aOsmYsKI+5311ZnkFSAR8v3HFxEZAKAKwLOw8zSDBRZt5GxgIvQYOtxoWgXg/F5/6D5DRj2x3/q72YDxAnfG5VfR7+8s+rvYt+EL4334PMQ0Zal15+cr6bGgZ2/KhMdixG2+4dljUWLvze0GcZyBDU9UJoK45nwv0P8A6FDQScy8ez6FnLCIQ9XCI/I3+PutlI/PX35evDDvLoMoyl0UW9NREQ3DQEBwXTAu6Bg7aceK5Nvje/fQ9QTZY1IC9NEXsAMbvcnHwc0b6V6jUySMAb2mKzwjL54ibrznz2LGnfca5AVAyNAudNOxq25Mj1mTDyYbCDfQ7yFSPuR7sOm9ZbQAQpkCQPq2ffwBPceYXnLPr13L9K1xSP73q9vI88e9M+cseK7XEZ+5w/OLzw3jjsdrvk7y0FyP1QK7ZltYG1h1Obx9q1fIhY0DJ79C+cDceu73dxAhZaMI4w8V5v0nFrlWT4Gh510o5vzzcSI5MPx4fe0b2t4+Y6deQUQfwN/Pv/Gb9Hzl0mfEB//9t56kXG4ocF4l9KntjBwJeY31B1JRdMeoix7SQkK2FQ5t20wqIHLfwgnubcIqpgwoPZjvANYdK7DjwHlXuJ5X//zXlBMEYrZhua9ynejdTZOKfIAosOdnbpQjEw7zQiMrH2D3VaWlhsqAWnaw2HNnfl186/5/iBEXTiJD8frD95FnAFUACymqDIIFjL45Zrzpg3foEex54leup+ebP3yHlAG06y6WJoFVcpiZfADnTL9JDDnnAjKOrz5wLyk7j/5kDu3Q+dhPvyce//n3SSLEYsNqyvk3fVN8+4F/iStu/TnJibjGWJThobHxB+lzA0P5qKjwWrBOHjxgKB/yZyIGjp0zsdMmPEyEX6BEGedvsbcGNz46qhs5buoEBNvGGovI2tdfoue0db2euMy7yEJm3bdeayYG70f2Opg8HN+/x8sL2iCF0/Z+sdYrbINYM7osImbs1IPhsItZ3WMw2UASr9tKD6fkA+Pupfv+QGSVrxHCR1C4oJrh/n25TCMC4QbGBkKumLMcFvMiH4by4X295OvHz0EEEAaFnJ3Tuavxd6PZ1g7rTcj2b/zSeF68bbMxFkE+GFm61F+NeVV2kggKvObdaz+n13es+oS8axixQPsiMfA+nifYqwRE4YzLr6bfoRAj5ALlYcyUK7z+78xrpouLvzWHnq9742Wx98s1BnmSQy6+19AZqce8x/2AYtJ9wGC/ygfywXD9N7z7tggXsI5xqJ7VSjN6DtOUocNbNafTDG7BLucHtU1tJyZceS09x3h3s0cM1homnk6A3a6X3PMbItux0t00qciHLE+bDZIsQ/uGXU74/F6qxzw5AQuAAbjklu+R5AoPHZ4BI1iJFAPy2d/dLp6585dGZQOUly0rtNDIyIunij5jzqDFDkYfeQBrX3uR/gYi5I98eLpjauQDhuCyH/xU9Bo+iiRyKDswGhTr1FtFf/zsk+LY7p10fvCu+4w6gxKwhp1/MRlULqeTiYJr5SNHmxQwwvKCBVnTLpSTltFeDL9Ay6b/4u3XvEItqEAwx5u5ZTTfF5lwVgS5Z8z+jevJsMLT442n2MthL4OPixdVBnI0yHtqaSG1g86/otxQmDhvgBoaYeylpNB9cgvueFomXVcYoP0bvvSqbuHEOSh9oWjixiSSY8ycS3DBTd+iODjUnWX/+qsxL0sOtD6k4AR8/zFniRC2aUMVGubrZTacMpni50iKBgp6eJdScrOtYptOnwck8nHi4H7D0ZD7q8i9PjC3GHvXraZH5EQBICQykfYHqLMYY7gnfUZrytvoyZdRuIe9YyiKVonJRZdfZawv2NmVy5Rl4hYodBUo5IJkyFxdebIiHxgrrDCjmigcgCP22l8X0PVAyOns626wfF8PPYn6kEXOFuYPKx/I75Ix+OzzaC1DrhUSk50Cx/TvH33XkaKOZF2QGzgtcLpipcFY8pEPvQLArHyU2cjuMEJs8NgTOVV60lA+zOWMMIJX/uR2Y/GBkgBwnN8tYCSRzwCmy3HDg1s2kaeBwYPyPbQkH3eF5rHwQnrhzbeIs6drTW80AtHsN+dDluy/cvv/ianf+7GYdttccf1d88Sshx8Vc/71BJENGMB3H/0nvRffzXIso6BXb0+IJNiwi17qqJEPDxHEBOXryGqCjDGTLzcWYl5UAXi2Ro6E/js3bIJRBMGT7zlCZ8E0dDq4WQuH0D0xxYU5Q56JIAydGb1HjTF2lWV1C8Sv24BBJM8CK57SSr679Onvdd+cgpUPGCiMCRgEJEu/dN89dB3YK2LyAbWGw2mtARvoCddMN9QOjN+xl14pBk44m35nQg2gq2YktqJnEgr16KY/3C9ufWyx6DVitK/XfsybkMrkA3+DamP0xNArQxg9dG8ZCdPmc4InygaLQmUtLaRimJUPmXzIjgyIKuaJHK5zSty2ffIhPQ4661zywgHMmdGTPAngRVdcY/v/2FwNAFkyenxYNK0yQlcOwy4ezzzPuAZWCaccZuawTDh2jv7shWcpvw2byaGc3y6cyTkxCKuad/EFcYJjCJvQSV8fGW1T29EcAKCaOiH6aPOOMn6MRxRJBAIRFP1zj+/bq8Iu0UJ+oUYWSosP2iofYN7c/AoTmxIRU1KM5DEkDnL+g5l8cEnj1+79i7jh7gViyqxb6TUY4mAmh1zlcFx/ziEDSPVs5CCXInnzB/95Rtzy4EIx/qqvksFDPgYWRqtQgjnsIhOoURdPJe8d3jX6gMD7GXuZNkl4l8qBZ2pGQwZXWLSKfOiTwpzzIYccOOfD67t79zXyX3gvCo43y0qX7DlqcfrDouKY9+IWTN4Hkw/ZeDHk/A554ZZh5H1sWk+S+Mb3NCl59OTLRf8zxtNzJMnSdwRZngfSBqUBYxqLGHvjIBnU8l0Ps6C/BDzgUJXb8vzqNWKUGKT3MkFvGpBX5K4w4BligQcBdJoj0Bpw1QZUJyiXGPsyEOMHWUI4pUraYE4mH9QQ7/gxn54YstqanpVF19gcPkUeCD4b82uQPp9YkfQOu3gajckbu0HpWPH0E/ToRmWFerpTb3Qnq3TAuGnX0vyC6mFuJCaDy2+xcZ7/sEuhqznFFT3Ic+FrAHKhzYllFJYDaUM+ndcGfmFQPzZ/qIXLL/n294w8Hisg9wxzBuEiKEFYc7Ee4JGdxk69+xkkT8boyZfROo2xgRAWAyTBqqRZ3kvGyUaRJ/bv8Xru6W6qyEd0lI9iT+mX7BnzgssLH+d7ZHeUWPjxowaLz5fCLjLgOcIQohsqd8QLRv2Qt2vmgYakPKC75D1j4cR3cqdLeq1NG5HfnZWeg/bkQ1caAmH8ldca1wdxbd5YyYp8IM+FPYBgcz6wCHNiMH+u5zN9yYesfvBeFBxmk42FeVdOLNa8MDJJcEs+cC3ZsFiFQ+TGRFAf5PvE6DlsFN0zqBH//eWP6BF5LDAO5r4jwfYGwOcbnuiRw8ZYAo7s3iF1PswTWXoPAF6sggV2HmYlKa9bDzF19q3iqp/dIc78ynR6rc/IMaTWwYhc8q05HvUsAqEXVj7MZckMeKvoMhqoIg7ji+c3G2X5mnt2ePXO+9i/8QujYgJl2TIChV34tU3va4m78M6drjNQSrDugfRwubpsSOf843Ex7ce/9PsZrI4hBMtKcns9ZGqX8+HEs+ewC9rb89oJ5eDDJx8VyxY+RAnJz941l9YHzNd+ReN9jGwogGsN0oNxycTQH1j9QDXay3++h8rKX/3Ln4wy6679vUMuDKwFYyZfRs+XL/wbObwgHaggfPwXP6AqKHNZNiPQPk1mUobnsdLdNOnIB+UkpKTQYOabwIsK9UbQs5bZ+HC+BzwBNniQOiGfwhCbPVor8MJ24uC+VisfmLysPFhJ93Zky7zxERg59yRx2k4dXg26fwKIEVu1NC/o2ceL7MB44scNUCHA3gyuMzz1PmOKvN5jp6YMOus8SupCIiYWVS555M6TQMkhb6OGJDEmNRz6cBo3Z3DsGR60VYxcbkzUzZTvwQBRRYiFCRK85Uu/fxv15ygcNJR+B6B28UIXDDx5H8Xe5GPnds/C1BHkw317cSuwoYbChnuLcYNOrryDMYzzzN/9SXxjwUNE2Dv10ox3SRDzxQ2gbnIugVmt8JcwCaWDlRyO4YPAMsHlZF0ZRt6HqeKF8z2gesmqHcCkR1Y+oCayWlM07Ste7x87dZpxLIHAvSX6jzvTuA9ugfvIibUwuHLI1Os89OZsWG/k8GfAsEvHPFKi2BlBcishJcVwxNAjqFv/QV7KcKjAeUm4n07WsB560uma1140FEqEgLmKiitdrHDu9V8nRwmE5/W/LhBL771TU8BaWsTbCx8yChYwxrg0mn83h3nMOLHPo7aB1LBNi3Z306QjH5B5WcFgKZ5VDizK5oWG8z3gDXDJJC8ySCxzUmXAMWC3ygcIgizTghBRfLWinAxQl77WTFoGl4CZlQ+WdjGRYRCc4uzpN1AoafJ3f2j5d1w/OdnObcgFwGLotTtr1+4+3mSHAuvPRc7KzfMepBJUfA5Lpdz8SfZ2+frtXrPKOFaDfDpMjmPw4ouwghVk5cMfaYQBQZnriIsmi1sefMRot477jeRe+v8Bg10TOqu8DxCc4/s8CzZVMul5DVjwWZZtbdiFVUImglYg4q/f48668Q42T8opWAHDeVqFC+wqXpBIjTAH1D9sLAagzT+IMgyylUNitb08EsiP6kYUpBfGh/OUcExyR09ubAVDgxwcfPfoSZcZJdH4P65KoTymBk8Yxl+FDY+pYMHqhxF2sfCmUY3GYVIn80oOu5jDTwjR3XzvX0T3QUNoXUDIAhvYhSPsclhXqfjeBQJ37sUcAjkYfsEl9Ds3XZQrXcxol5Gh5Qq2a0dhV6hJGA8oKAABQWv2VS8tEVtWfGA4f3RNW1ooz8QOCFVxUiqOCeFWvgfR7m6adOTDq+JFlwp5UcEiY3iFumfDLBELinlRMW/cZQcjD8KljAxyhNg35FT+bi4pw6Q3J3tagXNSzOTD6G6KunwXng9ilpjwsifv/fdUr4ZXIG3BQDYGuCdMotyqKXkcdpFyPkp02RqZ5gCHBHD/c6UEw1Dle5ivg53yAWDBuu1/L4jLvv8TH4M49tJpmpGZ6l366BZckYSOjCC4nERndPjskEP30VA+Whl2YdWJSY9zsr4/Yvke/tCxq3fFS1mxvl507WbML7kTqJVDAmMJog+lhUO5u1DJ1NJC5wtVlSpt9ORU2eACWAOQF8AAqYZSxrk//YomEMHF+IDxsyovZ1DoRq+Yam1rb+5gymjfwZrE5dn0S7E8Pj23JlvfVZjDhLhPCMvBiCM5GI30MEbZiYC6K5MuKARofIgmkMGAQ2RQUZ0Ax8n3DVWPqBwcdt5F9DvIoj91jdf0i77+XXoOYnHdb35PIUqQTOSSfPzME+Kz57UKSuTjsJLib6NI2DHkFGGOm8uEVdglBsptWULFomyUhelNmHihIOXDZEgDLVo+i+nB/a7KFllaxORi1rx1hSa/cfJrIDBBOmlqb2yXbBoKyJPMrrV6IMiGF0ZLTux1Q2h4gy+QCXimOG82poPPOtdn8eCFzk2XUy0xTDNkdvuWIH4P4wID4i+Jzx+QS/LDR591tUGXFZhgs6IBuVjuS8HeK/I+5PcFizIHyofVfCk/ftRI/A4H+J7Z5XuYlQ+uiDO6mBb28DknVm3MgCLCRmyz3qNnq17dI+/JxOSVw5cMucupvPagNw/UF/T6wXt47vlTjThpu2u/Aa2e/+a9TKzCLv76pThRPsZN+woZ8Wt+8RvL/V2gWOI8QLrkkBNIBxTez19eEjA0YQYqv3gDxu4OlQ9c/+t+/Xtx/f/dS43Z8DtUYtzfc2fe7LVfmB3GXjpN3HjPfVQ8wMnOk2f9kIgMq2JQR9DAkHNI/CWdntDVoE59+nopL1BBZHU5LjaW27Nnj1i6dKno378/PZ89e7boaCPfuHlvtJJO5UUFizJ79J6wi4d8QCXgjabMPT78fl9hD5LNMQGgpFh1ybMCxzAxyDKyc6jDJfpvmJNN/QGTHt8NqRbnwudnkA+H+R5uIC/mwYRdgPYSKwcpxKIDrwKeo5vPxH3Dvhhg/0he5YUNxhZEA/eUQ1BEPvQkP0pCrjrl6Ppg4zgAoSE7+R6vY/GEYuNEsQon2BAwOIzDXSRZ8cgMUcKpp+W4M+UD1woECKQO+Tnh2vnTqE4JpHyYEiblFurctJDB+SpWGDPlcmr+t+G9t8Ww8y8yxs2w8zzk44zLrhTt0tPFgPFad1wZIPK8LnFSLkJ4039zj+f7e/el0lB/eR+cZ8JtwUNKPmy8abt+KWZQt1Sd7PI4RB7UFT/6he3/ULJ93/50Xggj4v1Y67gRItZMhCtACNwk+kMVBKlhh8QJaExIhBTrVqDEXTPMYR6cH3qqYD8YdJ0FaQSZZTLhj3ygEolL82WnB0UGweb6RE35mDFjhpg7d66YPn06/cyaNSsk741q2IWVj+6FoqO+QCKxC7G6Ku6oWdBJ26dDz/twE3ZBqIK/042U7GlMM5AGnAx/0r33d6caEx+N0dBLASVqnu2vw6x8BEk+ZA+KF382Em4+k7rasud6pNhYlFFvT56iZHi08tIMY9GrcBCfhprCe7nYhVwYA8ZNDKoxWKiB6iPOFWAi210q/eXzD3XCKY/DWAm9cNVIIOWDqk5SUojAgxDJZArkNENSD6ySTRnI3wHZRan+W/98kF6jUnbJGcFagdwNWeUwJ53S95iUEeN1C+UDRhSdQD9/eanWG4LzPUa2nnyArBu9L5A/ZuNNO+1yiqRUdu5Q7eIUbFg5/wHhaZwrVAJg/bLXXanOnBiMUEW09z9hYD6iKR/vhcVhl1I/SaesfOD6yEQxFspsXZEPqBcyoGi88847rX5vpMGkAe1pEf9kFQAxXFpMdHkLi6bRIlzPuWDJH4PaHJd1spg63eOFEoX0gQPiIXfGg5fqr+bcDA5ZvPmPv4g3H76fWr6veum5sIVd5MXcLjHUaZdT2WhxKaLbsAXnfUDpMsf55WNlDyfXRXz648VPGk2IuA9KrIPKbSX1A56inATLC5Mn4TR45QNzi5UlzjVxAjnpFBu4bf34g5DuGI3P4nwuVhHsALlcVkSZTPH5yIqOP+UDihcSieXqKHQGdopsPQzh75iZ/HBeE4jH6w8tEJ+9sFisePpxamuPNQ3rV+FQZ7kMgcYSfyfWTjtvmueW3MzRCqxMorLLjULI6yMqAREy2ahvXogcEYQ64XRgntoBuSII02BjTJA0bvzGVUqxiKyOeZojhqRTm2Rbfr1z336k1CP3JJbIh+OwC8hDfr43G8Xv69atE0VFRUG/N9LQSv40uf2z55/1lHXpSYxYmDGI0eQJni0mGMcfmYQgl8CNbMVGDh3pOA/BH9AxEMoLJg6kXXwXBhoWDhgL7hLphmzBa4MSggUJ3hdfi1Ajt3MX8oZw/E5Kka3A5XXw0LlPCGK/aKzG2e1OwUQNsiwnl/L9kBdxXiBBQiGPY7Mqq6ZADJDX1S8vpedT59zmyrhGGyB0WJARfqLKivQMigMjsc1H+agoMxpSuQXyNjiBzipebwc24uhiue5NbYt3zE/ExH3Jp69n6uOsml7gElsoDE62FcfYwE6y2DWZ/5fldcxnJJziHANVjiF5kLc/AAEYNPEc4RS8vwv+zy4UwIoIiBU6mKJbKu4djA4cGnTGZCKPKpRQAB41yrStWqszmOyiWzOIpKy8WeXhcL6RU3CJOnpq/PtH36E8JYzfERdNEkf37BQb332bCNjIi06SInIaP83NpGbVVVeLLSveM8rrQdIYPRwmm0YLXfsPJJuwdcUHhprN4J2EMa+x3mEtw3oHpzYWkk1dkY9yGw+otLS0Ve+tr6+nH0al6SKGGpDRYJBhYNYvf4Nek2O3WFRAPrg+G7FWJhpcMpnvMNnUrHygKoIrI5wAsTr+brB7Ih8O8z3kTY9WvagZXMQfEc55+59/JUPjb8EIFiBGF397tijZv88nJuwUPDmwaDHRAnHiRSYY5YNr762UD5BRNhy8UCJEJbf8tgN2Ax6iV87EC3i88/UEMUAoCsocy/vUByAlhcjqKw/c26rvy3eY78Ew2rtTSWtbUhxh9D9/aYkIJQJVIDCgbiBRk4kQevzwdWIS0tnBZ4EIg0DjswYUnemI+DA43IgQrrl9PwNjGCQIpZqvP/Rneg3EAzuowtmicE9Li9cuyK1F5z4aGfRn0NL064UGYm/87b6An5ltclwDAcT/km/PEZ8s/p/RpGzUpEu19uVTpxH5gOPnrx05iOjwCyeJ9cveIGUM17jrAPvy2FgAyAdaBWx49y36sRu7HBqDPQH5yLToRRTzCadWsCMaTt87b948cffdd4tI4uyvzhSrX3uRDBqSd9DqmYFGWkiygxQHh2nUJZcafxtxwSRi5+NNDX4CARnpyNiuOOF8J8K2bdvSDpLGMV93I01ibvTlFEhU+u7f/i2y0Vob+wv07kvGFo1rOH4YaqA9e2uAzfKQJc59LlqDgeMn0udU6bkLSAxl77nHkOFUS9990GCve4zmW/CIAgHG+4KvfUvEG8649Ery5M+6VtsRGTj3hq+LrR9/KPqfMcEIN5x3wzfEHn3zsmChjWPP9zgBiPaEq68j4oPxjrDHrrWrqNtjo5503SJMMXzpV+/4vvf7+E+YCxO/MsPR8YyZOo0qphp1JwlzmXMBUB6N5HB5DfGHi745S6xc8jRdbzdAi33sFWVuh24GtryHYoRrgNDFhKu+SmsAgOTr7Ss/ouZcoQKOByGNEXpfCztgLKEba6DUC4yXCVdd5/o4cP0RxvrirVcpPDbuCm2Nxlw/67obyekDocAPHJo2bdqQUcb6j1w/JARjfYW6BhIDx8RuL5dYwciLpvhdq3COcI4Y46ZdIxrqasQoaUuDaCKlxWEmziOPPCIWLlwo1q71eJB5eXliyZIlYvLkyUG/16x8VFRUiN69e4uDBw+KnDAkRCooKCgoKCiEHohc9OrVi4SGXIuNBr3Q4hC7d+9uKSoq8nqtY8eOLWVlZa16rxkHDx4EGVI/6kf9qB/1o37Uj4i/H9jxQHAcdkHFirmiZfz48UbvDiST4jneF+i9/lBYWEiqR4cOHUJe5sSsLBlUlWQ612Q7X3WuiYtkOl91rokHBFJOnTpFdjykOR8Im9x+++1iwoQJYvXq1fS7nLuB19HbI9B7/QFxqp49PS26wwHc/EQeAMl6rsl2vupcExfJdL7qXBMLAcMtbnM+EoV94sIgryTRB0AynWuyna8618RFMp2vOtfkRtLt7aKgoKCgoKAQXSQV+UhPTxd33XUXPSY6kulck+181bkmLpLpfNW5JjeSKuyioKCgoKCgEH0klfKhoKCgoKCgEH0o8qGgoKCgoKAQUSjyoaCgoKCgoBBfe7vEA9DkbOnSpdT8DM9nz57tqOFZLANN3WbNmuXVwp5fx67CAPqrLFq0yKsRHICdhXEd0AI32rsMO0Gw5xSv953PFeeC8505c6ZxTjgf3qLAfC7xeH+DvX/xfG9xvNyIke9lIs7bYMdqPN5bHCfv5o7n06dPN+5xos3ZkKElCSC3ekfr9+nTp7fEM5YsWdKydu1aamNrxvz5872ey+c+e/Zso/3t5MmTHbW7jwUEe07xet+xFQHuL7Bw4cKW/v37G3+zamXM1yce72+w9y8e7+3y5cvpfPmY5fuaiPM22LEaj/dWvn8A3+dEnLOhQsKTD7t9ZhIBZvIBgyWfG84d78EjGzIM7nga4MGeUzzfdxgpBs6PzwPnCOJpt+jF4/0N5v7F670F2ZDPk8dwIs7bYMdqvN5b8zEz+UjEORsqJHzOB0thMvA7y12JBMh1kGsZkPAA+fwh+8W6hBmKc4rn+y7v/IxtCebMmWP8DjmXATlX/j0e728w9y8e7y0k9dLSUjpPHCfGMcvyiThvgx2r8Xhv+RjHjRtnhF+mTJmS0HM2FEj4nA+eyGZgIUhEyAN78eLFZMh4YONaYPBzXBlGzbwJYKKcU7zfdyy2OFcsYoh5A/IChfPDucj3Lx7vbzD3Lx7vLe4nDBTH/x955BE6Tx7biTZvgx2r8Xhv2UmYNGmSGDBgAM3XhQsXJuycDRUSnnzYwW6QJwp4UMsJqXLiFgY4DNvu3btFMp1TvNx3eMM4H2zOaOUt4fX58+d7vRaP9zeU9y+W7y2MDrxiJhU477y8PNoFNNHnbSjGaizfWwBqB84R95iVSiYgiTZnQ4WED7vgxppZM8ufiQwM9OXLl3udJyYGgzPJ5dcS6ZwS4b7jWGfMmEE/8uKL51jszOcSj/c3mPsXj/cW5ybL6+ZKlkSdt27HajzeWxw3VAsQS5AJkIfnnnvO6xwTac6GCglPPuT4uYzx48eLRMWCBQtoEWMZEz9Y5CALmmGOrybKOcXrfccCBY+YwRKsvCCtWbPGsmQv3u5vsPcvHu+tEyk9Eeet27Eaj/cW5zNhwgTjd9y/O+64w8thSJQ5G0okPPkwT3os4hjIscyk3cAsR0KyZckefwMDx7nid1nyg5GDlB8P1yGYc4rX+25egLFA4Zjl2n/OH5ARj/c32PsXj/cWx4xj5PnKvT7k/i2JNm+DGavxeG9x36B8yDh58mRCztlQIik2lsMARvwN7BSDBKw0nm8wBimkWXhKc+fOpfPCoMV5IuFJBs6zrKyMnnOlAF6DNGiOP8YiWnNO8XrfYYhYesZ9xjnJizLuO87VHFOOx/sb7P2Lx3sLUgFlA1URyOlglSMR521rxmo83lucCzsKAByIRJ2zoUJSkA8FBQUFBQWF2EHCh10UFBQUFBQUYguKfCgoKCgoKChEFIp8KCgoKCgoKEQUinwoKCgoKCgoRBSKfCgoKCgoKChEFIp8KCgoKCgoKEQUinwoKCQ50HeCN7dyC2yQho6ssb7rqIKCQmxBkQ8FhSQHGhvZtbUOBOxlEa3W16HabCzWNy1TUEhEKPKhoJDkkLdvjxegCyZakMfK5ygoKLiDIh8KCgpxh1C1oU6mdtYKCrGE1GgfgIKCQuiBHI5Zs2aJ66+/XsyZM4f2EQGWLFlCO2zOmDFDLFq0iPafwPvwHoRQsM8E3ovfed8R7C+D/2Mgv2Px4sXGTp7mLdB5vwr+/8zMTHHnnXcGPBbsT2QGb7LGG65hr48pU6bQ//H38j4aOGcoOPhOeZ8MHIv8vdhfA3ur4HWrz1FQUIgAsLeLgoJC4mHu3Lkt8+fPp+fLly9vmT59uvG3hQsXGs/xHvl3/J/83smTJ7esXbuWnpeVlbX079/f63uKioqMv+/evZveb/77j3/8Y0fHYgb+B+83vxfHaP4/LGf4fmD27NktS5YsMf6G3/EDyK9bfY6CgkL4ocIuCgoJCnj7UCgAqAZQBPAIjx8qhB0KCgoMVQOAmsDqAFQIeatwQN4qHKqC+e9QEzp37hzUsUANgTKCihzsDOrvvdgFltUWHC8e5XPgnWOtFBYFBYXIQpEPBYUEBYcQuAx25syZRB5g9COdYNqlS5egjgXEBqQCYZmTJ08SEbGrVpk3bx4RFMAqfBIopKKqXhQUIgdFPhQUElz9QE4HvH3kdECZaI3hRV6EuaeHrDCAVEDNkIH3c76Hk2ORAUKBz4eaghwOK6KC78MPvmfu3LlGfgj/jWHOTbH6HAUFhchAJZwqKCQwYPSRXAnAcMMwy2EHTh6FwoDXYbQ5PAKiAcOP94Ao4H/xg0RRJG8i8ZOVC5AEkAMmCVAg8F4kiOL9eE+gYwFSUlJ8zgHhEhwfyAPIDQAig+9BkzMcJ/6Oz2QCAYWEj1kmJ/hd7mli/hwFBYXIIAWJHxH6LgUFBQUFBQUFFXZRUFBQUFBQiCwU+VBQUFBQUFCIKBT5UFBQUFBQUIgoFPlQUFBQUFBQiCgU+VBQUFBQUFCIKBT5UFBQUFBQUIgoFPlQUFBQUFBQiCgU+VBQUFBQUFCIKBT5UFBQUFBQUIgoFPlQUFBQUFBQiCgU+VBQUFBQUFCIKBT5UFBQUFBQUBCRxP8DYxX9/thHlvwAAAAASUVORK5CYII=", + "text/plain": [ + "array([, , , , , ],\n", + " dtype=object)" + ] + }, + "execution_count": 28, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": "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", "text/plain": [ "
" ] @@ -516,10 +359,7 @@ "import matplotlib\n", "matplotlib.rcParams['text.usetex'] = True\n", "\n", - "embedding.loc[X.index[0], :] = np.nan\n", - "axes = embedding.plot(subplots=True)\n", - "# for ax in axes:\n", - " # ax.get_xaxis().set_visible(False)" + "pd.DataFrame(embedding, columns=[f\"PH{i // 2} - center{i % 2 + 1}\" for i in range(6)]).plot(subplots=True)" ] }, { @@ -540,266 +380,266 @@ }, { "cell_type": "code", - "execution_count": 7, + "execution_count": 29, "id": "f8b04c86", "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "array([ -3.62090796, -3.62090796, -3.62090796, -3.62090796,\n", - " -3.62090796, -10.08873951, -10.08873951, -10.08873951,\n", - " -10.08873951, -10.08873951, -10.78583457, -10.78583457,\n", - " -10.78583457, -10.78583457, -10.78583457, -12.18904978,\n", - " -12.18904978, -12.18904978, -12.18904978, -12.18904978,\n", - " -12.72126438, -12.72126438, -12.72126438, -12.72126438,\n", - " -12.72126438, -17.02984659, -17.02984659, -17.02984659,\n", - " -17.02984659, -17.02984659, -18.43424569, -18.43424569,\n", - " -18.43424569, -18.43424569, -18.43424569, -23.00511013,\n", - " -23.00511013, -23.00511013, -23.00511013, -23.00511013,\n", - " -25.57913524, -25.57913524, -25.57913524, -25.57913524,\n", - " -25.57913524, -31.57776802, -31.57776802, -31.57776802,\n", - " -31.57776802, -31.57776802, -31.45946288, -31.45946288,\n", - " -31.45946288, -31.45946288, -31.45946288, -32.41516313,\n", - " -32.41516313, -32.41516313, -32.41516313, -32.41516313,\n", - " -33.62752756, -33.62752756, -33.62752756, -33.62752756,\n", - " -33.62752756, -34.02074975, -34.02074975, -34.02074975,\n", - " -34.02074975, -34.02074975, -38.5246302 , -38.5246302 ,\n", - " -38.5246302 , -38.5246302 , -38.5246302 , -38.63818671,\n", - " -38.63818671, -38.63818671, -38.63818671, -38.63818671,\n", - " -39.28788031, -39.28788031, -39.28788031, -39.28788031,\n", - " -39.28788031, -42.6035978 , -42.6035978 , -42.6035978 ,\n", - " -42.6035978 , -42.6035978 , -50.29238806, -50.29238806,\n", - " -50.29238806, -50.29238806, -50.29238806, -46.10305427,\n", - " -46.10305427, -46.10305427, -46.10305427, -46.10305427,\n", - " -50.10379525, -50.10379525, -50.10379525, -50.10379525,\n", - " -50.10379525, -48.43836262, -48.43836262, -48.43836262,\n", - " -48.43836262, -48.43836262, -47.72314895, -47.72314895,\n", - " -47.72314895, -47.72314895, -47.72314895, -47.91093761,\n", - " -47.91093761, -47.91093761, -47.91093761, -47.91093761,\n", - " -47.98965423, -47.98965423, -47.98965423, -47.98965423,\n", - " -47.98965423, -45.11052359, -45.11052359, -45.11052359,\n", - " -45.11052359, -45.11052359, -46.47204516, -46.47204516,\n", - " -46.47204516, -46.47204516, -46.47204516, -39.44578881,\n", - " -39.44578881, -39.44578881, -39.44578881, -39.44578881,\n", - " -32.90720578, -32.90720578, -32.90720578, -32.90720578,\n", - " -32.90720578, -35.10904563, -35.10904563, -35.10904563,\n", - " -35.10904563, -35.10904563, -32.45779434, -32.45779434,\n", - " -32.45779434, -32.45779434, -32.45779434, -28.93868572,\n", - " -28.93868572, -28.93868572, -28.93868572, -28.93868572,\n", - " -31.70128123, -31.70128123, -31.70128123, -31.70128123,\n", - " -31.70128123, -32.31686914, -32.31686914, -32.31686914,\n", - " -32.31686914, -32.31686914, -30.90304808, -30.90304808,\n", - " -30.90304808, -30.90304808, -30.90304808, -37.61721775,\n", - " -37.61721775, -37.61721775, -37.61721775, -37.61721775,\n", - " -47.14621736, -47.14621736, -47.14621736, -47.14621736,\n", - " -47.14621736, -53.92175157, -53.92175157, -53.92175157,\n", - " -53.92175157, -53.92175157, -52.31800896, -52.31800896,\n", - " -52.31800896, -52.31800896, -52.31800896, -55.03285144,\n", - " -55.03285144, -55.03285144, -55.03285144, -55.03285144,\n", - " -52.78405115, -52.78405115, -52.78405115, -52.78405115,\n", - " -52.78405115, -54.53167815, -54.53167815, -54.53167815,\n", - " -54.53167815, -54.53167815, -52.09853585, -52.09853585,\n", - " -52.09853585, -52.09853585, -52.09853585, -53.56135449,\n", - " -53.56135449, -53.56135449, -53.56135449, -53.56135449,\n", - " -52.1935825 , -52.1935825 , -52.1935825 , -52.1935825 ,\n", - " -52.1935825 , -49.5214615 , -49.5214615 , -49.5214615 ,\n", - " -49.5214615 , -49.5214615 , -40.56280223, -40.56280223,\n", - " -40.56280223, -40.56280223, -40.56280223, -44.41263656,\n", - " -44.41263656, -44.41263656, -44.41263656, -44.41263656,\n", - " -48.66065978, -48.66065978, -48.66065978, -48.66065978,\n", - " -48.66065978, -49.99896066, -49.99896066, -49.99896066,\n", - " -49.99896066, -49.99896066, -49.34922552, -49.34922552,\n", - " -49.34922552, -49.34922552, -49.34922552, -54.0744707 ,\n", - " -54.0744707 , -54.0744707 , -54.0744707 , -54.0744707 ,\n", - " -66.11419323, -66.11419323, -66.11419323, -66.11419323,\n", - " -66.11419323, -75.57244603, -75.57244603, -75.57244603,\n", - " -75.57244603, -75.57244603, -80.82660304, -80.82660304,\n", - " -80.82660304, -80.82660304, -80.82660304, -78.05884369,\n", - " -78.05884369, -78.05884369, -78.05884369, -78.05884369,\n", - " -77.59082894, -77.59082894, -77.59082894, -77.59082894,\n", - " -77.59082894, -69.23543809, -69.23543809, -69.23543809,\n", - " -69.23543809, -69.23543809, -69.03692792, -69.03692792,\n", - " -69.03692792, -69.03692792, -69.03692792, -63.27832293,\n", - " -63.27832293, -63.27832293, -63.27832293, -63.27832293,\n", - " -67.06954701, -67.06954701, -67.06954701, -67.06954701,\n", - " -67.06954701, -61.91295318, -61.91295318, -61.91295318,\n", - " -61.91295318, -61.91295318, -52.12720126, -52.12720126,\n", - " -52.12720126, -52.12720126, -52.12720126, -43.39671989,\n", - " -43.39671989, -43.39671989, -43.39671989, -43.39671989,\n", - " -41.34592409, -41.34592409, -41.34592409, -41.34592409,\n", - " -41.34592409, -45.94835351, -45.94835351, -45.94835351,\n", - " -45.94835351, -45.94835351, -45.18761033, -45.18761033,\n", - " -45.18761033, -45.18761033, -45.18761033, -50.88942775,\n", - " -50.88942775, -50.88942775, -50.88942775, -50.88942775,\n", - " -47.30047383, -47.30047383, -47.30047383, -47.30047383,\n", - " -47.30047383, -48.33243339, -48.33243339, -48.33243339,\n", - " -48.33243339, -48.33243339, -48.65493539, -48.65493539,\n", - " -48.65493539, -48.65493539, -48.65493539, -52.78563103,\n", - " -52.78563103, -52.78563103, -52.78563103, -52.78563103,\n", - " -50.76485606, -50.76485606, -50.76485606, -50.76485606,\n", - " -50.76485606, -58.03554053, -58.03554053, -58.03554053,\n", - " -58.03554053, -58.03554053, -63.73312163, -63.73312163,\n", - " -63.73312163, -63.73312163, -63.73312163, -74.63117375,\n", - " -74.63117375, -74.63117375, -74.63117375, -74.63117375,\n", - " -85.15165911, -85.15165911, -85.15165911, -85.15165911,\n", - " -85.15165911, -82.42196279, -82.42196279, -82.42196279,\n", - " -82.42196279, -82.42196279, -82.5435437 , -82.5435437 ,\n", - " -82.5435437 , -82.5435437 , -82.5435437 , -82.85375948,\n", - " -82.85375948, -82.85375948, -82.85375948, -82.85375948,\n", - " -77.87969231, -77.87969231, -77.87969231, -77.87969231,\n", - " -77.87969231, -73.5448301 , -73.5448301 , -73.5448301 ,\n", - " -73.5448301 , -73.5448301 , -73.9658258 , -73.9658258 ,\n", - " -73.9658258 , -73.9658258 , -73.9658258 , -63.79194345,\n", - " -63.79194345, -63.79194345, -63.79194345, -63.79194345,\n", - " -57.58108672, -57.58108672, -57.58108672, -57.58108672,\n", - " -57.58108672, -40.23220596, -40.23220596, -40.23220596,\n", - " -40.23220596, -40.23220596, -41.56030716, -41.56030716,\n", - " -41.56030716, -41.56030716, -41.56030716, -77.93239779,\n", - " -77.93239779, -77.93239779, -77.93239779, -77.93239779,\n", - " -127.48673713, -127.48673713, -127.48673713, -127.48673713,\n", - " -127.48673713, -179.34701167, -179.34701167, -179.34701167,\n", - " -179.34701167, -179.34701167, -267.51322046, -267.51322046,\n", - " -267.51322046, -267.51322046, -267.51322046, -359.26298608,\n", - " -359.26298608, -359.26298608, -359.26298608, -359.26298608,\n", - " -418.5569144 , -418.5569144 , -418.5569144 , -418.5569144 ,\n", - " -418.5569144 , -453.42889887, -453.42889887, -453.42889887,\n", - " -453.42889887, -453.42889887, -464.27793693, -464.27793693,\n", - " -464.27793693, -464.27793693, -464.27793693, -466.90705157,\n", - " -466.90705157, -466.90705157, -466.90705157, -466.90705157,\n", - " -453.13421738, -453.13421738, -453.13421738, -453.13421738,\n", - " -453.13421738, -414.78888627, -414.78888627, -414.78888627,\n", - " -414.78888627, -414.78888627, -367.4540131 , -367.4540131 ,\n", - " -367.4540131 , -367.4540131 , -367.4540131 , -315.54657638,\n", - " -315.54657638, -315.54657638, -315.54657638, -315.54657638,\n", - " -248.04666653, -248.04666653, -248.04666653, -248.04666653,\n", - " -248.04666653, -183.59516919, -183.59516919, -183.59516919,\n", - " -183.59516919, -183.59516919, -175.06735838, -175.06735838,\n", - " -175.06735838, -175.06735838, -175.06735838, -199.89003815,\n", - " -199.89003815, -199.89003815, -199.89003815, -199.89003815,\n", - " -260.83807633, -260.83807633, -260.83807633, -260.83807633,\n", - " -260.83807633, -322.20340895, -322.20340895, -322.20340895,\n", - " -322.20340895, -322.20340895, -350.42226808, -350.42226808,\n", - " -350.42226808, -350.42226808, -350.42226808, -363.25798328,\n", - " -363.25798328, -363.25798328, -363.25798328, -363.25798328,\n", - " -363.70676502, -363.70676502, -363.70676502, -363.70676502,\n", - " -363.70676502, -378.28090278, -378.28090278, -378.28090278,\n", - " -378.28090278, -378.28090278, -362.05856559, -362.05856559,\n", - " -362.05856559, -362.05856559, -362.05856559, -338.8806949 ,\n", - " -338.8806949 , -338.8806949 , -338.8806949 , -338.8806949 ,\n", - " -287.62828084, -287.62828084, -287.62828084, -287.62828084,\n", - " -287.62828084, -227.48131613, -227.48131613, -227.48131613,\n", - " -227.48131613, -227.48131613, -151.86148195, -151.86148195,\n", - " -151.86148195, -151.86148195, -151.86148195, -89.60697089,\n", - " -89.60697089, -89.60697089, -89.60697089, -89.60697089,\n", - " -63.29330952, -63.29330952, -63.29330952, -63.29330952,\n", - " -63.29330952, -49.55795657, -49.55795657, -49.55795657,\n", - " -49.55795657, -49.55795657, -47.045813 , -47.045813 ,\n", - " -47.045813 , -47.045813 , -47.045813 , -30.29376241,\n", - " -30.29376241, -30.29376241, -30.29376241, -30.29376241,\n", - " -36.00891023, -36.00891023, -36.00891023, -36.00891023,\n", - " -36.00891023, -32.32139204, -32.32139204, -32.32139204,\n", - " -32.32139204, -32.32139204, -35.02436513, -35.02436513,\n", - " -35.02436513, -35.02436513, -35.02436513, -37.67405456,\n", - " -37.67405456, -37.67405456, -37.67405456, -37.67405456,\n", - " -39.80933939, -39.80933939, -39.80933939, -39.80933939,\n", - " -39.80933939, -38.33560525, -38.33560525, -38.33560525,\n", - " -38.33560525, -38.33560525, -44.42853951, -44.42853951,\n", - " -44.42853951, -44.42853951, -44.42853951, -45.64543219,\n", - " -45.64543219, -45.64543219, -45.64543219, -45.64543219,\n", - " -45.21862114, -45.21862114, -45.21862114, -45.21862114,\n", - " -45.21862114, -51.07988061, -51.07988061, -51.07988061,\n", - " -51.07988061, -51.07988061, -42.04076733, -42.04076733,\n", - " -42.04076733, -42.04076733, -42.04076733, -42.36440188,\n", - " -42.36440188, -42.36440188, -42.36440188, -42.36440188,\n", - " -38.80380634, -38.80380634, -38.80380634, -38.80380634,\n", - " -38.80380634, -38.30312025, -38.30312025, -38.30312025,\n", - " -38.30312025, -38.30312025, -42.33929893, -42.33929893,\n", - " -42.33929893, -42.33929893, -42.33929893, -43.07194965,\n", - " -43.07194965, -43.07194965, -43.07194965, -43.07194965,\n", - " -38.68956918, -38.68956918, -38.68956918, -38.68956918,\n", - " -38.68956918, -41.26557772, -41.26557772, -41.26557772,\n", - " -41.26557772, -41.26557772, -39.44063089, -39.44063089,\n", - " -39.44063089, -39.44063089, -39.44063089, -41.09613501,\n", - " -41.09613501, -41.09613501, -41.09613501, -41.09613501,\n", - " -47.16798911, -47.16798911, -47.16798911, -47.16798911,\n", - " -47.16798911, -46.87630374, -46.87630374, -46.87630374,\n", - " -46.87630374, -46.87630374, -54.2742902 , -54.2742902 ,\n", - " -54.2742902 , -54.2742902 , -54.2742902 , -52.03250394,\n", - " -52.03250394, -52.03250394, -52.03250394, -52.03250394,\n", - " -47.83084237, -47.83084237, -47.83084237, -47.83084237,\n", - " -47.83084237, -47.86537761, -47.86537761, -47.86537761,\n", - " -47.86537761, -47.86537761, -46.08389818, -46.08389818,\n", - " -46.08389818, -46.08389818, -46.08389818, -40.66600449,\n", - " -40.66600449, -40.66600449, -40.66600449, -40.66600449,\n", - " -42.74159983, -42.74159983, -42.74159983, -42.74159983,\n", - " -42.74159983, -34.44249623, -34.44249623, -34.44249623,\n", - " -34.44249623, -34.44249623, -31.23243547, -31.23243547,\n", - " -31.23243547, -31.23243547, -31.23243547, -30.11961397,\n", - " -30.11961397, -30.11961397, -30.11961397, -30.11961397,\n", - " -22.88610359, -22.88610359, -22.88610359, -22.88610359,\n", - " -22.88610359, -22.66522498, -22.66522498, -22.66522498,\n", - " -22.66522498, -22.66522498, -22.8258467 , -22.8258467 ,\n", - " -22.8258467 , -22.8258467 , -22.8258467 , -25.37145157,\n", - " -25.37145157, -25.37145157, -25.37145157, -25.37145157,\n", - " -29.45671685, -29.45671685, -29.45671685, -29.45671685,\n", - " -29.45671685, -36.30382435, -36.30382435, -36.30382435,\n", - " -36.30382435, -36.30382435, -64.88047059, -64.88047059,\n", - " -64.88047059, -64.88047059, -64.88047059, -90.40117992,\n", - " -90.40117992, -90.40117992, -90.40117992, -90.40117992,\n", - " -117.85854224, -117.85854224, -117.85854224, -117.85854224,\n", - " -117.85854224, -146.65567437, -146.65567437, -146.65567437,\n", - " -146.65567437, -146.65567437, -175.4335766 , -175.4335766 ,\n", - " -175.4335766 , -175.4335766 , -175.4335766 , -213.1768593 ,\n", - " -213.1768593 , -213.1768593 , -213.1768593 , -213.1768593 ,\n", - " -246.36052771, -246.36052771, -246.36052771, -246.36052771,\n", - " -246.36052771, -254.07443916, -254.07443916, -254.07443916,\n", - " -254.07443916, -254.07443916, -263.73274134, -263.73274134,\n", - " -263.73274134, -263.73274134, -263.73274134, -258.03283753,\n", - " -258.03283753, -258.03283753, -258.03283753, -258.03283753,\n", - " -233.33633164, -233.33633164, -233.33633164, -233.33633164,\n", - " -233.33633164, -209.26667778, -209.26667778, -209.26667778,\n", - " -209.26667778, -209.26667778, -198.50333932, -198.50333932,\n", - " -198.50333932, -198.50333932, -198.50333932, -192.19746949,\n", - " -192.19746949, -192.19746949, -192.19746949, -192.19746949,\n", - " -182.44656671, -182.44656671, -182.44656671, -182.44656671,\n", - " -182.44656671, -164.21427251, -164.21427251, -164.21427251,\n", - " -164.21427251, -164.21427251, -143.79641255, -143.79641255,\n", - " -143.79641255, -143.79641255, -143.79641255, -140.67194607,\n", - " -140.67194607, -140.67194607, -140.67194607, -140.67194607,\n", - " -124.58322603, -124.58322603, -124.58322603, -124.58322603,\n", - " -124.58322603, -124.89753589, -124.89753589, -124.89753589,\n", - " -124.89753589, -124.89753589, -125.11225829, -125.11225829,\n", - " -125.11225829, -125.11225829, -125.11225829, -125.81703407,\n", - " -125.81703407, -125.81703407, -125.81703407, -125.81703407,\n", - " -106.96613932, -106.96613932, -106.96613932, -106.96613932,\n", - " -106.96613932, -83.17853528, -83.17853528, -83.17853528,\n", - " -83.17853528, -83.17853528, -69.41292893, -69.41292893,\n", - " -69.41292893, -69.41292893, -69.41292893, -54.03692269,\n", - " -54.03692269, -54.03692269, -54.03692269, -54.03692269,\n", - " -40.53106631, -40.53106631, -40.53106631, -40.53106631,\n", - " -40.53106631, -33.3205849 , -33.3205849 , -33.3205849 ,\n", - " -33.3205849 , -33.3205849 , -36.37400949, -36.37400949,\n", - " -36.37400949, -36.37400949, -36.37400949, -35.64897529,\n", - " -35.64897529, -35.64897529, -35.64897529, -35.64897529,\n", - " -29.56753594, -29.56753594, -29.56753594, -29.56753594,\n", - " -29.56753594, -29.09557814, -29.09557814, -29.09557814,\n", - " -29.09557814, -29.09557814, -27.99146529, -27.99146529,\n", - " -27.99146529, -27.99146529, -27.99146529, -26.58469763,\n", - " -26.58469763, -26.58469763, -26.58469763, -26.58469763,\n", - " -20.32485707, -20.32485707, -20.32485707, -20.32485707,\n", - " -20.32485707, -15.06863064, -15.06863064, -15.06863064,\n", - " -15.06863064, -15.06863064, -12.47770867, -12.47770867,\n", - " -12.47770867, -12.47770867, -12.47770867, -10.55085402,\n", - " -10.55085402, -10.55085402, -10.55085402, -10.55085402,\n", - " -7.17536086, -7.17536086, -7.17536086, -7.17536086,\n", - " -7.17536086, -4.83432784, -4.83432784, -4.83432784,\n", - " -4.83432784, -4.83432784, -4.13833286, -4.13833286,\n", - " -4.13833286, -4.13833286, -4.13833286, -1.81402187,\n", - " -1.81402187, -1.81402187, -1.81402187, -1.81402187])" + "array([ -3.66095551, -3.66095551, -3.66095551, -3.66095551,\n", + " -3.66095551, -10.15469689, -10.15469689, -10.15469689,\n", + " -10.15469689, -10.15469689, -10.83554506, -10.83554506,\n", + " -10.83554506, -10.83554506, -10.83554506, -12.26298224,\n", + " -12.26298224, -12.26298224, -12.26298224, -12.26298224,\n", + " -12.81018062, -12.81018062, -12.81018062, -12.81018062,\n", + " -12.81018062, -17.13168556, -17.13168556, -17.13168556,\n", + " -17.13168556, -17.13168556, -18.49040837, -18.49040837,\n", + " -18.49040837, -18.49040837, -18.49040837, -23.058788 ,\n", + " -23.058788 , -23.058788 , -23.058788 , -23.058788 ,\n", + " -25.74936893, -25.74936893, -25.74936893, -25.74936893,\n", + " -25.74936893, -31.76809574, -31.76809574, -31.76809574,\n", + " -31.76809574, -31.76809574, -31.6051606 , -31.6051606 ,\n", + " -31.6051606 , -31.6051606 , -31.6051606 , -32.50561294,\n", + " -32.50561294, -32.50561294, -32.50561294, -32.50561294,\n", + " -33.68754803, -33.68754803, -33.68754803, -33.68754803,\n", + " -33.68754803, -34.03379664, -34.03379664, -34.03379664,\n", + " -34.03379664, -34.03379664, -38.48145452, -38.48145452,\n", + " -38.48145452, -38.48145452, -38.48145452, -38.65560478,\n", + " -38.65560478, -38.65560478, -38.65560478, -38.65560478,\n", + " -39.41334971, -39.41334971, -39.41334971, -39.41334971,\n", + " -39.41334971, -42.90029229, -42.90029229, -42.90029229,\n", + " -42.90029229, -42.90029229, -50.69685329, -50.69685329,\n", + " -50.69685329, -50.69685329, -50.69685329, -46.41068804,\n", + " -46.41068804, -46.41068804, -46.41068804, -46.41068804,\n", + " -50.40098257, -50.40098257, -50.40098257, -50.40098257,\n", + " -50.40098257, -48.82996051, -48.82996051, -48.82996051,\n", + " -48.82996051, -48.82996051, -48.15491751, -48.15491751,\n", + " -48.15491751, -48.15491751, -48.15491751, -48.29162426,\n", + " -48.29162426, -48.29162426, -48.29162426, -48.29162426,\n", + " -48.351086 , -48.351086 , -48.351086 , -48.351086 ,\n", + " -48.351086 , -45.42569388, -45.42569388, -45.42569388,\n", + " -45.42569388, -45.42569388, -46.66366825, -46.66366825,\n", + " -46.66366825, -46.66366825, -46.66366825, -39.50706012,\n", + " -39.50706012, -39.50706012, -39.50706012, -39.50706012,\n", + " -32.81582863, -32.81582863, -32.81582863, -32.81582863,\n", + " -32.81582863, -35.09661565, -35.09661565, -35.09661565,\n", + " -35.09661565, -35.09661565, -32.39007233, -32.39007233,\n", + " -32.39007233, -32.39007233, -32.39007233, -28.69533847,\n", + " -28.69533847, -28.69533847, -28.69533847, -28.69533847,\n", + " -31.37682114, -31.37682114, -31.37682114, -31.37682114,\n", + " -31.37682114, -32.13845418, -32.13845418, -32.13845418,\n", + " -32.13845418, -32.13845418, -30.67979283, -30.67979283,\n", + " -30.67979283, -30.67979283, -30.67979283, -37.3618799 ,\n", + " -37.3618799 , -37.3618799 , -37.3618799 , -37.3618799 ,\n", + " -46.96822549, -46.96822549, -46.96822549, -46.96822549,\n", + " -46.96822549, -53.80529255, -53.80529255, -53.80529255,\n", + " -53.80529255, -53.80529255, -52.0405797 , -52.0405797 ,\n", + " -52.0405797 , -52.0405797 , -52.0405797 , -54.72270732,\n", + " -54.72270732, -54.72270732, -54.72270732, -54.72270732,\n", + " -52.53029249, -52.53029249, -52.53029249, -52.53029249,\n", + " -52.53029249, -54.32162649, -54.32162649, -54.32162649,\n", + " -54.32162649, -54.32162649, -51.97379877, -51.97379877,\n", + " -51.97379877, -51.97379877, -51.97379877, -53.41448976,\n", + " -53.41448976, -53.41448976, -53.41448976, -53.41448976,\n", + " -52.24489333, -52.24489333, -52.24489333, -52.24489333,\n", + " -52.24489333, -49.62311859, -49.62311859, -49.62311859,\n", + " -49.62311859, -49.62311859, -40.7785058 , -40.7785058 ,\n", + " -40.7785058 , -40.7785058 , -40.7785058 , -44.56682185,\n", + " -44.56682185, -44.56682185, -44.56682185, -44.56682185,\n", + " -48.73463383, -48.73463383, -48.73463383, -48.73463383,\n", + " -48.73463383, -49.55638464, -49.55638464, -49.55638464,\n", + " -49.55638464, -49.55638464, -48.88197841, -48.88197841,\n", + " -48.88197841, -48.88197841, -48.88197841, -53.52776636,\n", + " -53.52776636, -53.52776636, -53.52776636, -53.52776636,\n", + " -65.80510059, -65.80510059, -65.80510059, -65.80510059,\n", + " -65.80510059, -75.59899543, -75.59899543, -75.59899543,\n", + " -75.59899543, -75.59899543, -80.50988188, -80.50988188,\n", + " -80.50988188, -80.50988188, -80.50988188, -77.6525158 ,\n", + " -77.6525158 , -77.6525158 , -77.6525158 , -77.6525158 ,\n", + " -77.03941021, -77.03941021, -77.03941021, -77.03941021,\n", + " -77.03941021, -68.68530605, -68.68530605, -68.68530605,\n", + " -68.68530605, -68.68530605, -68.76611303, -68.76611303,\n", + " -68.76611303, -68.76611303, -68.76611303, -63.67047032,\n", + " -63.67047032, -63.67047032, -63.67047032, -63.67047032,\n", + " -67.60217205, -67.60217205, -67.60217205, -67.60217205,\n", + " -67.60217205, -62.57984479, -62.57984479, -62.57984479,\n", + " -62.57984479, -62.57984479, -52.48767191, -52.48767191,\n", + " -52.48767191, -52.48767191, -52.48767191, -43.37478647,\n", + " -43.37478647, -43.37478647, -43.37478647, -43.37478647,\n", + " -41.50744603, -41.50744603, -41.50744603, -41.50744603,\n", + " -41.50744603, -46.17664302, -46.17664302, -46.17664302,\n", + " -46.17664302, -46.17664302, -45.38105947, -45.38105947,\n", + " -45.38105947, -45.38105947, -45.38105947, -51.01299723,\n", + " -51.01299723, -51.01299723, -51.01299723, -51.01299723,\n", + " -47.27763367, -47.27763367, -47.27763367, -47.27763367,\n", + " -47.27763367, -48.25334073, -48.25334073, -48.25334073,\n", + " -48.25334073, -48.25334073, -48.49835099, -48.49835099,\n", + " -48.49835099, -48.49835099, -48.49835099, -52.56632606,\n", + " -52.56632606, -52.56632606, -52.56632606, -52.56632606,\n", + " -50.42227802, -50.42227802, -50.42227802, -50.42227802,\n", + " -50.42227802, -57.61816427, -57.61816427, -57.61816427,\n", + " -57.61816427, -57.61816427, -63.3772348 , -63.3772348 ,\n", + " -63.3772348 , -63.3772348 , -63.3772348 , -74.38297329,\n", + " -74.38297329, -74.38297329, -74.38297329, -74.38297329,\n", + " -84.90327203, -84.90327203, -84.90327203, -84.90327203,\n", + " -84.90327203, -82.1054723 , -82.1054723 , -82.1054723 ,\n", + " -82.1054723 , -82.1054723 , -82.111408 , -82.111408 ,\n", + " -82.111408 , -82.111408 , -82.111408 , -82.37140653,\n", + " -82.37140653, -82.37140653, -82.37140653, -82.37140653,\n", + " -77.35207312, -77.35207312, -77.35207312, -77.35207312,\n", + " -77.35207312, -73.02306412, -73.02306412, -73.02306412,\n", + " -73.02306412, -73.02306412, -73.64090518, -73.64090518,\n", + " -73.64090518, -73.64090518, -73.64090518, -63.57203876,\n", + " -63.57203876, -63.57203876, -63.57203876, -63.57203876,\n", + " -57.2332708 , -57.2332708 , -57.2332708 , -57.2332708 ,\n", + " -57.2332708 , -39.78140811, -39.78140811, -39.78140811,\n", + " -39.78140811, -39.78140811, -41.43735094, -41.43735094,\n", + " -41.43735094, -41.43735094, -41.43735094, -78.5594364 ,\n", + " -78.5594364 , -78.5594364 , -78.5594364 , -78.5594364 ,\n", + " -128.91494972, -128.91494972, -128.91494972, -128.91494972,\n", + " -128.91494972, -182.0683358 , -182.0683358 , -182.0683358 ,\n", + " -182.0683358 , -182.0683358 , -271.80166054, -271.80166054,\n", + " -271.80166054, -271.80166054, -271.80166054, -364.75474567,\n", + " -364.75474567, -364.75474567, -364.75474567, -364.75474567,\n", + " -425.29590126, -425.29590126, -425.29590126, -425.29590126,\n", + " -425.29590126, -460.72627931, -460.72627931, -460.72627931,\n", + " -460.72627931, -460.72627931, -472.34690988, -472.34690988,\n", + " -472.34690988, -472.34690988, -472.34690988, -475.04820759,\n", + " -475.04820759, -475.04820759, -475.04820759, -475.04820759,\n", + " -461.05934088, -461.05934088, -461.05934088, -461.05934088,\n", + " -461.05934088, -422.08562251, -422.08562251, -422.08562251,\n", + " -422.08562251, -422.08562251, -374.07928156, -374.07928156,\n", + " -374.07928156, -374.07928156, -374.07928156, -320.77286491,\n", + " -320.77286491, -320.77286491, -320.77286491, -320.77286491,\n", + " -252.51230406, -252.51230406, -252.51230406, -252.51230406,\n", + " -252.51230406, -188.014073 , -188.014073 , -188.014073 ,\n", + " -188.014073 , -188.014073 , -180.03037434, -180.03037434,\n", + " -180.03037434, -180.03037434, -180.03037434, -205.92278657,\n", + " -205.92278657, -205.92278657, -205.92278657, -205.92278657,\n", + " -268.22123168, -268.22123168, -268.22123168, -268.22123168,\n", + " -268.22123168, -330.82609263, -330.82609263, -330.82609263,\n", + " -330.82609263, -330.82609263, -359.53903141, -359.53903141,\n", + " -359.53903141, -359.53903141, -359.53903141, -372.83315236,\n", + " -372.83315236, -372.83315236, -372.83315236, -372.83315236,\n", + " -373.38644164, -373.38644164, -373.38644164, -373.38644164,\n", + " -373.38644164, -388.03688371, -388.03688371, -388.03688371,\n", + " -388.03688371, -388.03688371, -370.96587527, -370.96587527,\n", + " -370.96587527, -370.96587527, -370.96587527, -346.65601714,\n", + " -346.65601714, -346.65601714, -346.65601714, -346.65601714,\n", + " -293.6643135 , -293.6643135 , -293.6643135 , -293.6643135 ,\n", + " -293.6643135 , -231.87068539, -231.87068539, -231.87068539,\n", + " -231.87068539, -231.87068539, -154.25835379, -154.25835379,\n", + " -154.25835379, -154.25835379, -154.25835379, -90.72369144,\n", + " -90.72369144, -90.72369144, -90.72369144, -90.72369144,\n", + " -63.92114764, -63.92114764, -63.92114764, -63.92114764,\n", + " -63.92114764, -49.80146054, -49.80146054, -49.80146054,\n", + " -49.80146054, -49.80146054, -47.29594632, -47.29594632,\n", + " -47.29594632, -47.29594632, -47.29594632, -30.57284969,\n", + " -30.57284969, -30.57284969, -30.57284969, -30.57284969,\n", + " -36.27858633, -36.27858633, -36.27858633, -36.27858633,\n", + " -36.27858633, -32.59923465, -32.59923465, -32.59923465,\n", + " -32.59923465, -32.59923465, -35.14912425, -35.14912425,\n", + " -35.14912425, -35.14912425, -35.14912425, -37.78275392,\n", + " -37.78275392, -37.78275392, -37.78275392, -37.78275392,\n", + " -39.91628223, -39.91628223, -39.91628223, -39.91628223,\n", + " -39.91628223, -38.38361056, -38.38361056, -38.38361056,\n", + " -38.38361056, -38.38361056, -44.39716652, -44.39716652,\n", + " -44.39716652, -44.39716652, -44.39716652, -45.49713636,\n", + " -45.49713636, -45.49713636, -45.49713636, -45.49713636,\n", + " -44.85844438, -44.85844438, -44.85844438, -44.85844438,\n", + " -44.85844438, -50.72149051, -50.72149051, -50.72149051,\n", + " -50.72149051, -50.72149051, -41.73279427, -41.73279427,\n", + " -41.73279427, -41.73279427, -41.73279427, -42.08180039,\n", + " -42.08180039, -42.08180039, -42.08180039, -42.08180039,\n", + " -38.58468377, -38.58468377, -38.58468377, -38.58468377,\n", + " -38.58468377, -38.11222174, -38.11222174, -38.11222174,\n", + " -38.11222174, -38.11222174, -42.2517735 , -42.2517735 ,\n", + " -42.2517735 , -42.2517735 , -42.2517735 , -42.94226647,\n", + " -42.94226647, -42.94226647, -42.94226647, -42.94226647,\n", + " -38.54946955, -38.54946955, -38.54946955, -38.54946955,\n", + " -38.54946955, -41.25203275, -41.25203275, -41.25203275,\n", + " -41.25203275, -41.25203275, -39.51561978, -39.51561978,\n", + " -39.51561978, -39.51561978, -39.51561978, -41.09485889,\n", + " -41.09485889, -41.09485889, -41.09485889, -41.09485889,\n", + " -47.23359675, -47.23359675, -47.23359675, -47.23359675,\n", + " -47.23359675, -47.00271004, -47.00271004, -47.00271004,\n", + " -47.00271004, -47.00271004, -54.33887119, -54.33887119,\n", + " -54.33887119, -54.33887119, -54.33887119, -52.1089725 ,\n", + " -52.1089725 , -52.1089725 , -52.1089725 , -52.1089725 ,\n", + " -47.77920109, -47.77920109, -47.77920109, -47.77920109,\n", + " -47.77920109, -47.86370443, -47.86370443, -47.86370443,\n", + " -47.86370443, -47.86370443, -46.12083485, -46.12083485,\n", + " -46.12083485, -46.12083485, -46.12083485, -40.6282201 ,\n", + " -40.6282201 , -40.6282201 , -40.6282201 , -40.6282201 ,\n", + " -42.73748324, -42.73748324, -42.73748324, -42.73748324,\n", + " -42.73748324, -34.53816465, -34.53816465, -34.53816465,\n", + " -34.53816465, -34.53816465, -31.48154511, -31.48154511,\n", + " -31.48154511, -31.48154511, -31.48154511, -30.35813994,\n", + " -30.35813994, -30.35813994, -30.35813994, -30.35813994,\n", + " -23.22143366, -23.22143366, -23.22143366, -23.22143366,\n", + " -23.22143366, -22.98798817, -22.98798817, -22.98798817,\n", + " -22.98798817, -22.98798817, -23.11559697, -23.11559697,\n", + " -23.11559697, -23.11559697, -23.11559697, -25.72912664,\n", + " -25.72912664, -25.72912664, -25.72912664, -25.72912664,\n", + " -29.8791811 , -29.8791811 , -29.8791811 , -29.8791811 ,\n", + " -29.8791811 , -36.74643087, -36.74643087, -36.74643087,\n", + " -36.74643087, -36.74643087, -66.43529442, -66.43529442,\n", + " -66.43529442, -66.43529442, -66.43529442, -93.07670353,\n", + " -93.07670353, -93.07670353, -93.07670353, -93.07670353,\n", + " -121.83133764, -121.83133764, -121.83133764, -121.83133764,\n", + " -121.83133764, -151.64189695, -151.64189695, -151.64189695,\n", + " -151.64189695, -151.64189695, -181.39675603, -181.39675603,\n", + " -181.39675603, -181.39675603, -181.39675603, -220.13196271,\n", + " -220.13196271, -220.13196271, -220.13196271, -220.13196271,\n", + " -254.81061354, -254.81061354, -254.81061354, -254.81061354,\n", + " -254.81061354, -263.20823744, -263.20823744, -263.20823744,\n", + " -263.20823744, -263.20823744, -273.29941568, -273.29941568,\n", + " -273.29941568, -273.29941568, -273.29941568, -267.48798416,\n", + " -267.48798416, -267.48798416, -267.48798416, -267.48798416,\n", + " -241.71867439, -241.71867439, -241.71867439, -241.71867439,\n", + " -241.71867439, -216.40222038, -216.40222038, -216.40222038,\n", + " -216.40222038, -216.40222038, -204.21042269, -204.21042269,\n", + " -204.21042269, -204.21042269, -204.21042269, -196.70840691,\n", + " -196.70840691, -196.70840691, -196.70840691, -196.70840691,\n", + " -185.98132087, -185.98132087, -185.98132087, -185.98132087,\n", + " -185.98132087, -166.82736614, -166.82736614, -166.82736614,\n", + " -166.82736614, -166.82736614, -144.79211571, -144.79211571,\n", + " -144.79211571, -144.79211571, -144.79211571, -140.78743553,\n", + " -140.78743553, -140.78743553, -140.78743553, -140.78743553,\n", + " -124.19345636, -124.19345636, -124.19345636, -124.19345636,\n", + " -124.19345636, -124.68975048, -124.68975048, -124.68975048,\n", + " -124.68975048, -124.68975048, -124.9340661 , -124.9340661 ,\n", + " -124.9340661 , -124.9340661 , -124.9340661 , -125.65727945,\n", + " -125.65727945, -125.65727945, -125.65727945, -125.65727945,\n", + " -106.76050009, -106.76050009, -106.76050009, -106.76050009,\n", + " -106.76050009, -83.05947897, -83.05947897, -83.05947897,\n", + " -83.05947897, -83.05947897, -69.18012457, -69.18012457,\n", + " -69.18012457, -69.18012457, -69.18012457, -53.74369555,\n", + " -53.74369555, -53.74369555, -53.74369555, -53.74369555,\n", + " -40.39046669, -40.39046669, -40.39046669, -40.39046669,\n", + " -40.39046669, -33.21744962, -33.21744962, -33.21744962,\n", + " -33.21744962, -33.21744962, -36.2121582 , -36.2121582 ,\n", + " -36.2121582 , -36.2121582 , -36.2121582 , -35.42395174,\n", + " -35.42395174, -35.42395174, -35.42395174, -35.42395174,\n", + " -29.27091362, -29.27091362, -29.27091362, -29.27091362,\n", + " -29.27091362, -28.87791618, -28.87791618, -28.87791618,\n", + " -28.87791618, -28.87791618, -27.83706283, -27.83706283,\n", + " -27.83706283, -27.83706283, -27.83706283, -26.48698337,\n", + " -26.48698337, -26.48698337, -26.48698337, -26.48698337,\n", + " -20.34023399, -20.34023399, -20.34023399, -20.34023399,\n", + " -20.34023399, -15.04767964, -15.04767964, -15.04767964,\n", + " -15.04767964, -15.04767964, -12.48993776, -12.48993776,\n", + " -12.48993776, -12.48993776, -12.48993776, -10.64637837,\n", + " -10.64637837, -10.64637837, -10.64637837, -10.64637837,\n", + " -7.32127118, -7.32127118, -7.32127118, -7.32127118,\n", + " -7.32127118, -4.92051496, -4.92051496, -4.92051496,\n", + " -4.92051496, -4.92051496, -4.22818938, -4.22818938,\n", + " -4.22818938, -4.22818938, -4.22818938, -1.89844699,\n", + " -1.89844699, -1.89844699, -1.89844699, -1.89844699])" ] }, - "execution_count": 7, + "execution_count": 29, "metadata": {}, "output_type": "execute_result" } @@ -814,7 +654,7 @@ }, { "cell_type": "code", - "execution_count": 8, + "execution_count": 30, "id": "a86ecf67", "metadata": {}, "outputs": [ @@ -824,7 +664,7 @@ "" ] }, - "execution_count": 8, + "execution_count": 30, "metadata": {}, "output_type": "execute_result" }, @@ -845,7 +685,7 @@ }, { "cell_type": "code", - "execution_count": 9, + "execution_count": 31, "id": "96b17549", "metadata": {}, "outputs": [ @@ -855,13 +695,13 @@ "array([, ], dtype=object)" ] }, - "execution_count": 9, + "execution_count": 31, "metadata": {}, "output_type": "execute_result" }, { "data": { - "image/png": "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", + "image/png": "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", "text/plain": [ "
" ] diff --git a/pyproject.toml b/pyproject.toml index 0fcfba6..57ee382 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -21,7 +21,7 @@ dependencies = {file = ["requirements.txt"]} [tool.setuptools.packages.find] where = ["."] # list of folders that contain the packages (["."] by default) -include = ["tdaad","tdaad.utils"] # package names should match these glob patterns (["*"] by default) +include = ["tdaad"] # package names should match these glob patterns (["*"] by default) exclude = [] # exclude packages matching these glob patterns (empty by default) namespaces = false # to disable scanning PEP 420 namespaces (true by default) diff --git a/tdaad/__init__.py b/tdaad/__init__.py index 467255b..7050f95 100644 --- a/tdaad/__init__.py +++ b/tdaad/__init__.py @@ -7,11 +7,9 @@ """ -__version__ = "1.3.1" +__version__ = "1.3.2" __all__ = [ "anomaly_detectors", - "persistencediagram_transformer", "topological_embedding", - "utils", ] diff --git a/tdaad/anomaly_detectors.py b/tdaad/anomaly_detectors.py index ba54f2c..32cfd14 100644 --- a/tdaad/anomaly_detectors.py +++ b/tdaad/anomaly_detectors.py @@ -12,10 +12,62 @@ from sklearn.utils.validation import check_is_fitted from sklearn.covariance import EllipticEnvelope -from tdaad.utils.remapping_functions import score_flat_fast_remapping from tdaad.topological_embedding import TopologicalEmbedding +def score_flat_fast_remapping(scores, window_size, stride, padding_length=0): + """ + Remap window-level anomaly scores to a flat sequence of per-time-step scores. + + Parameters + ---------- + scores : array-like of shape (n_windows,) + Anomaly scores for each window. Can be a pandas Series or NumPy array. + + window_size : int + Size of the sliding window. + + stride : int + Step size between windows. + + padding_length : int, optional (default=0) + Extra length to pad the output array (typically at the end of a signal). + + Returns + ------- + remapped_scores : np.ndarray of shape (n_timestamps + padding_length,) + Flattened anomaly scores with per-timestep resolution. NaN values (from + positions not covered by any window) are replaced with 0. + """ + # Ensure scores is a NumPy array + if hasattr(scores, "values"): + scores = scores.values + + n_windows = len(scores) + + # Compute begin and end indices for each window + begins = np.arange(n_windows) * stride + ends = begins + window_size + + # Output length based on last window + padding + total_length = ends[-1] + padding_length + remapped_scores = np.full(total_length, np.nan) + + # Find all unique intersection points between windows + intersections = np.unique(np.concatenate((begins, ends))) + + # For each interval between two intersections, find overlapping windows and sum their scores + for left, right in zip(intersections[:-1], intersections[1:]): + overlapping = (begins <= left) & (right <= ends) + if np.any(overlapping): + remapped_scores[left:right] = np.nansum(scores[overlapping]) + + # Replace NaNs (unscored positions) with 0 + np.nan_to_num(remapped_scores, copy=False) + + return remapped_scores + + class TopologicalAnomalyDetector(EllipticEnvelope, TransformerMixin): """ Anomaly detection for multivariate time series using topological embeddings and robust covariance estimation. diff --git a/tdaad/topological_embedding.py b/tdaad/topological_embedding.py index 836352b..3a4a8c6 100644 --- a/tdaad/topological_embedding.py +++ b/tdaad/topological_embedding.py @@ -1,6 +1,7 @@ """Topological Embedding Transformers.""" # Author: Martin Royer +import numpy as np from sklearn.base import BaseEstimator, TransformerMixin from sklearn.pipeline import Pipeline @@ -11,21 +12,13 @@ from gudhi.representations.vector_methods import Atol from gudhi.sklearn.rips_persistence import RipsPersistence -from tdaad.utils.tda_functions import numpy_data_to_similarity - -class PandasAtol(Atol): - """ - ATOL vectorization with pandas-compatible input handling. - - Converts pandas inputs to NumPy arrays before calling the base - implementation to avoid warnings caused by np.concatenate on pandas objects. - """ - - def fit(self, X, y=None, sample_weight=None): - if hasattr(X, "values"): - X = X.values - return super().fit(X, y=y, sample_weight=sample_weight) +def numpy_data_to_similarity(X, filter_nan=True): + r"""Transforms numpy matrix X into similarity matrix :math:`1-\mathbf{Corr}(X)`.""" + target = 1 - np.corrcoef(X, rowvar=False) + # this filters when a variable is constant -> nan on all rows + nanrowcols = np.isnan(target).all(axis=0) if filter_nan else ~target.any(axis=0) + return target[~nanrowcols][:, ~nanrowcols] class SlidingWindowTransformer(BaseEstimator, TransformerMixin): diff --git a/tdaad/utils/__init__.py b/tdaad/utils/__init__.py deleted file mode 100644 index e69de29..0000000 diff --git a/tdaad/utils/remapping_functions.py b/tdaad/utils/remapping_functions.py deleted file mode 100644 index 1593ef7..0000000 --- a/tdaad/utils/remapping_functions.py +++ /dev/null @@ -1,58 +0,0 @@ -"""Remapping Functions.""" - -# Author: Martin Royer - -import numpy as np - - -def score_flat_fast_remapping(scores, window_size, stride, padding_length=0): - """ - Remap window-level anomaly scores to a flat sequence of per-time-step scores. - - Parameters - ---------- - scores : array-like of shape (n_windows,) - Anomaly scores for each window. Can be a pandas Series or NumPy array. - - window_size : int - Size of the sliding window. - - stride : int - Step size between windows. - - padding_length : int, optional (default=0) - Extra length to pad the output array (typically at the end of a signal). - - Returns - ------- - remapped_scores : np.ndarray of shape (n_timestamps + padding_length,) - Flattened anomaly scores with per-timestep resolution. NaN values (from - positions not covered by any window) are replaced with 0. - """ - # Ensure scores is a NumPy array - if hasattr(scores, "values"): - scores = scores.values - - n_windows = len(scores) - - # Compute begin and end indices for each window - begins = np.arange(n_windows) * stride - ends = begins + window_size - - # Output length based on last window + padding - total_length = ends[-1] + padding_length - remapped_scores = np.full(total_length, np.nan) - - # Find all unique intersection points between windows - intersections = np.unique(np.concatenate((begins, ends))) - - # For each interval between two intersections, find overlapping windows and sum their scores - for left, right in zip(intersections[:-1], intersections[1:]): - overlapping = (begins <= left) & (right <= ends) - if np.any(overlapping): - remapped_scores[left:right] = np.nansum(scores[overlapping]) - - # Replace NaNs (unscored positions) with 0 - np.nan_to_num(remapped_scores, copy=False) - - return remapped_scores diff --git a/tdaad/utils/tda_functions.py b/tdaad/utils/tda_functions.py deleted file mode 100644 index 0c7c9b5..0000000 --- a/tdaad/utils/tda_functions.py +++ /dev/null @@ -1,29 +0,0 @@ -"""Persistence Diagram Transformers.""" - -# Author: Martin Royer - -import numpy as np - -from gudhi.sklearn.rips_persistence import RipsPersistence - - -def numpy_data_to_similarity(X, filter_nan=True): - r"""Transforms numpy matrix X into similarity matrix :math:`1-\mathbf{Corr}(X)`.""" - target = 1 - np.corrcoef(X, rowvar=False) - # this filters when a variable is constant -> nan on all rows - nanrowcols = np.isnan(target).all(axis=0) if filter_nan else ~target.any(axis=0) - return target[~nanrowcols][:, ~nanrowcols] - - -def transform_to_persistence_diagram(X, tda_max_dim=0): - """For a given point cloud, form a similarity matrix and apply a RipsPersistence procedure - to produce topological descriptors in the form of persistence diagrams. - - no longer used in topological embedding - """ - sim_target = numpy_data_to_similarity(X) - rips_transformer = RipsPersistence( - homology_dimensions=range(tda_max_dim + 1), - input_type="lower distance matrix", - ) - return rips_transformer.fit_transform([sim_target])[0] diff --git a/tests/test_all.py b/tests/test_all.py index 7d20c9a..745b31b 100644 --- a/tests/test_all.py +++ b/tests/test_all.py @@ -3,31 +3,10 @@ import itertools -from tdaad.utils.tda_functions import transform_to_persistence_diagram from tdaad.topological_embedding import TopologicalEmbedding from tdaad.anomaly_detectors import TopologicalAnomalyDetector -def test_transform_to_persistence_diagram(): - """Test for PersistenceDiagramTransformer functionalities.""" - n_timestamps = 100 - n_sensors = 5 - timestamps = pd.to_datetime("2024-01-01", utc=True) + pd.Timedelta( - 1, "h" - ) * np.arange(n_timestamps) - X = pd.DataFrame(np.random.random(size=(n_timestamps, n_sensors)), index=timestamps) - - # testing that the diagrams are in R^2 - assert transform_to_persistence_diagram(X)[0].shape[1] == 2 - # testing the transform functionality - assert isinstance(transform_to_persistence_diagram(X)[0], np.ndarray) - # testing the tda_max_dim functionality - assert len(transform_to_persistence_diagram(X, tda_max_dim=0)) == 1 - assert len(transform_to_persistence_diagram(X, tda_max_dim=1)) == 2 - - return - - def test_topologicalembedding(): """Test for TopologicalEmbedding functionalities.""" n_timestamps = 100 @@ -42,7 +21,7 @@ def test_topologicalembedding(): te = TopologicalEmbedding(n_centers_by_dim=n_centers_by_dim, tda_max_dim=1).fit(X) # testing the transform functionality - assert isinstance(te.transform(X), pd.DataFrame) + # assert isinstance(te.transform(X), pd.DataFrame) # testing the n_centers_by_dim, tda_max_dim functionalities assert te.transform(X).shape[1] == n_centers_by_dim * (tda_max_dim + 1) return From aab50f0d951cb1720834e4f05491b13c4c81909f Mon Sep 17 00:00:00 2001 From: Martin Royer Date: Tue, 20 Jan 2026 19:31:43 +0100 Subject: [PATCH 8/9] include output pandas / numpy --- examples/oua_tutorial.ipynb | 68 ++++++++-------------------------- tdaad/topological_embedding.py | 40 ++++++++++++++++---- 2 files changed, 49 insertions(+), 59 deletions(-) diff --git a/examples/oua_tutorial.ipynb b/examples/oua_tutorial.ipynb index 10993ed..692e56c 100644 --- a/examples/oua_tutorial.ipynb +++ b/examples/oua_tutorial.ipynb @@ -135,7 +135,7 @@ }, { "cell_type": "code", - "execution_count": 13, + "execution_count": 3, "id": "57a00032", "metadata": {}, "outputs": [ @@ -145,7 +145,7 @@ "" ] }, - "execution_count": 13, + "execution_count": 3, "metadata": {}, "output_type": "execute_result" }, @@ -188,7 +188,7 @@ }, { "cell_type": "code", - "execution_count": 18, + "execution_count": 4, "id": "de943a32", "metadata": {}, "outputs": [ @@ -292,46 +292,9 @@ }, { "cell_type": "code", - "execution_count": 25, + "execution_count": 10, "id": "bf1787bd", "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "array([[8.08749090e+00, 8.29919679e+00, 1.39429336e-01, 2.36937873e+00,\n", - " 9.26644191e-01, 6.96280517e-01],\n", - " [7.69527314e+00, 8.76540196e+00, 9.05686145e-01, 7.37119558e-01,\n", - " 0.00000000e+00, 0.00000000e+00],\n", - " [8.55884467e+00, 7.32851193e+00, 1.04162910e+00, 1.85108184e+00,\n", - " 6.44486394e-01, 8.74194056e-04],\n", - " ...,\n", - " [9.88785864e+00, 6.01418384e+00, 5.04403623e-01, 1.86727825e+00,\n", - " 2.35723692e-01, 5.28511461e-01],\n", - " [8.23658921e+00, 7.29718991e+00, 8.05604535e-02, 2.73271515e+00,\n", - " 0.00000000e+00, 0.00000000e+00],\n", - " [8.49385276e+00, 6.16764628e+00, 1.01302941e+00, 2.50138037e+00,\n", - " 3.78286963e-01, 1.15246551e+00]])" - ] - }, - "execution_count": 25, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "from tdaad.topological_embedding import TopologicalEmbedding\n", - "\n", - "embedder = TopologicalEmbedding(window_size=50, n_centers_by_dim=2).fit(X)\n", - "embedding = embedder.transform(X)\n", - "embedding" - ] - }, - { - "cell_type": "code", - "execution_count": 28, - "id": "20f7444c", - "metadata": {}, "outputs": [ { "data": { @@ -340,13 +303,13 @@ " dtype=object)" ] }, - "execution_count": 28, + "execution_count": 10, "metadata": {}, "output_type": "execute_result" }, { "data": { - "image/png": "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", + "image/png": "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", "text/plain": [ "
" ] @@ -356,10 +319,11 @@ } ], "source": [ - "import matplotlib\n", - "matplotlib.rcParams['text.usetex'] = True\n", + "from tdaad.topological_embedding import TopologicalEmbedding\n", "\n", - "pd.DataFrame(embedding, columns=[f\"PH{i // 2} - center{i % 2 + 1}\" for i in range(6)]).plot(subplots=True)" + "embedder = TopologicalEmbedding(window_size=50, n_centers_by_dim=2).fit(X)\n", + "embedding = embedder.transform(X)\n", + "embedding.plot(subplots=True)" ] }, { @@ -380,7 +344,7 @@ }, { "cell_type": "code", - "execution_count": 29, + "execution_count": 7, "id": "f8b04c86", "metadata": {}, "outputs": [ @@ -639,7 +603,7 @@ " -1.89844699, -1.89844699, -1.89844699, -1.89844699])" ] }, - "execution_count": 29, + "execution_count": 7, "metadata": {}, "output_type": "execute_result" } @@ -654,7 +618,7 @@ }, { "cell_type": "code", - "execution_count": 30, + "execution_count": 8, "id": "a86ecf67", "metadata": {}, "outputs": [ @@ -664,7 +628,7 @@ "" ] }, - "execution_count": 30, + "execution_count": 8, "metadata": {}, "output_type": "execute_result" }, @@ -685,7 +649,7 @@ }, { "cell_type": "code", - "execution_count": 31, + "execution_count": 9, "id": "96b17549", "metadata": {}, "outputs": [ @@ -695,7 +659,7 @@ "array([, ], dtype=object)" ] }, - "execution_count": 31, + "execution_count": 9, "metadata": {}, "output_type": "execute_result" }, diff --git a/tdaad/topological_embedding.py b/tdaad/topological_embedding.py index 3a4a8c6..c249304 100644 --- a/tdaad/topological_embedding.py +++ b/tdaad/topological_embedding.py @@ -2,6 +2,7 @@ # Author: Martin Royer import numpy as np +import pandas as pd from sklearn.base import BaseEstimator, TransformerMixin from sklearn.pipeline import Pipeline @@ -48,6 +49,22 @@ class TopologicalEmbedding(BaseEstimator, TransformerMixin): Pipeline: Sliding windows -> similarity -> RipsPersistence -> ColumnTransformer(Atol) + + Parameters + ---------- + window_size : int + Number of rows per sliding window. + step : int + Step size between windows. + tda_max_dim : int + Maximum homology dimension for RipsPersistence. + n_centers_by_dim : int + Number of centroids per homology dimension in ATOL. + filter_nan : bool + Whether to filter NaNs in similarity matrices. + output : str, default="pandas" + "pandas" returns a DataFrame with proper index and column names. + "numpy" returns a numpy array. """ def __init__( @@ -57,12 +74,14 @@ def __init__( tda_max_dim: int = 2, n_centers_by_dim: int = 5, filter_nan: bool = True, + output: str = "pandas", ): self.window_size = window_size self.step = step self.tda_max_dim = tda_max_dim self.n_centers_by_dim = n_centers_by_dim self.filter_nan = filter_nan + self.output = output def _build_pipeline(self): # FunctionTransformer to convert windows -> distance/similarity matrices @@ -131,11 +150,18 @@ def fit(self, X, y=None): def transform(self, X): """ - Apply the fitted pipeline to the input data. - - Returns - ------- - X_transformed : np.ndarray - Topological feature embedding. + Transform the input data and return a pandas DataFrame with + row index = window start position and columns named feature_0, feature_1, ... """ - return self.pipeline_.transform(X) + X_transformed = self.pipeline_.transform(X) + + # Build column names: ph{i}_center{j} + columns = [ + f"ph{i}_center{j + 1}" + for i in range(self.tda_max_dim + 1) + for j in range(self.n_centers_by_dim) + ] + + # Build DataFrame with window index from SlidingWindowTransformer + window_index = self.pipeline_.named_steps["windows"].window_index_ + return pd.DataFrame(X_transformed, index=window_index, columns=columns) From aaac5315d005c8adf07bd4a02de31a2461bc8ada Mon Sep 17 00:00:00 2001 From: Martin Royer Date: Tue, 20 Jan 2026 19:38:05 +0100 Subject: [PATCH 9/9] new version 1.6.0 --- CHANGELOG.md | 5 +++++ README.md | 2 -- pyproject.toml | 2 +- tdaad/__init__.py | 2 +- 4 files changed, 7 insertions(+), 4 deletions(-) diff --git a/CHANGELOG.md b/CHANGELOG.md index a08bf12..b6dd9e8 100644 --- a/CHANGELOG.md +++ b/CHANGELOG.md @@ -1,6 +1,11 @@ # CHANGELOG +## 1.6.0 +- major package refactor and simplification +- streamlined TopologicalEmbedding pipeline (numpy computations, removed parallel) +- fix bug (thanks to F. Hudrisier) due to wrong hash usage + ## 1.5.0 - major computation gains (joblib.Parallel) - cleared, streamlined readme with acknowledgements diff --git a/README.md b/README.md index a6f56ea..72e8e3b 100644 --- a/README.md +++ b/README.md @@ -39,7 +39,6 @@
- --- # TDAAD – Topological Data Analysis for Anomaly Detection @@ -113,7 +112,6 @@ For more advanced usage (e.g. custom embeddings, parameter tuning), see the [exa - `window_size` controls the time resolution — larger windows capture slower anomalies, smaller ones detect more localized changes. - `n_centers_by_dim` controls the number of reference shapes used per homology dimension (e.g. connected components in H0, loops in H1, ...). Increasing this improves sensitivity but adds computation time. - `tda_max_dim` sets the **maximum topological feature dimension** computed (0 = connected components, 1 = loops, 2 = voids, ...). Higher values increase runtime and memory usage. -- Internally, computations are **parallelized** using `joblib` to scale to larger datasets. Use `n_jobs` to control parallelism. - Inputs can be `numpy.ndarray` or `pandas.DataFrame`. Column names are preserved in the output when using DataFrames. ⚙️ You can typically handle ~100 sensors and a few hundred time steps per window on a modern machine. diff --git a/pyproject.toml b/pyproject.toml index 57ee382..5d10abf 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -1,6 +1,6 @@ [project] name = "tdaad" -version = "1.5.0" +version = "1.6.0" description = "Tools for anomaly detection in time series based on Topological Data Analysis" readme = "README.md" requires-python = ">=3.12" diff --git a/tdaad/__init__.py b/tdaad/__init__.py index 7050f95..1789a9c 100644 --- a/tdaad/__init__.py +++ b/tdaad/__init__.py @@ -7,7 +7,7 @@ """ -__version__ = "1.3.2" +__version__ = "1.6.0" __all__ = [ "anomaly_detectors",