{
"cells": [
{
"cell_type": "markdown",
"id": "672b9895-a53e-4f36-8367-fd699de28118",
"metadata": {},
"source": [
"# Uplift Modeling Analysis & Evaluation - Intro"
]
},
{
"cell_type": "markdown",
"id": "07189c62-a6c4-4395-a779-b3b04339f96b",
"metadata": {},
"source": [
"This tutorial demonstrates how the `uplift-analysis` package can be used for analyzing and evaluating uplift models."
]
},
{
"cell_type": "markdown",
"id": "0983f6da-186d-455e-abe3-d93a8ac2f51f",
"metadata": {},
"source": [
"## Preliminaries"
]
},
{
"cell_type": "markdown",
"id": "40b5b144-a28a-4040-b76d-369c4dd87b0d",
"metadata": {},
"source": [
"We'll start by importing the required libraries:"
]
},
{
"cell_type": "code",
"execution_count": 4,
"id": "659c6471-2a21-4c5f-a1c4-d1f35d5fb238",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"The autoreload extension is already loaded. To reload it, use:\n",
" %reload_ext autoreload\n"
]
}
],
"source": [
"%load_ext autoreload\n",
"%autoreload 2"
]
},
{
"cell_type": "code",
"execution_count": 5,
"id": "c4895f50-d8e0-41e1-a1b6-a07cf8d07dcc",
"metadata": {},
"outputs": [],
"source": [
"from matplotlib import rcParams\n",
"rcParams.update({'figure.autolayout' : True,\n",
" 'figure.figsize' : [15, 8.5],\n",
" 'font.size': 17})\n",
"from typing import Tuple,Dict,Union\n",
"import itertools\n",
"from tqdm import tqdm\n",
"import numpy as np\n",
"import pandas as pd\n",
"from scipy.special import softmax\n",
"import matplotlib.pyplot as plt\n",
"import seaborn as sns\n",
"from sklearn.ensemble import GradientBoostingRegressor, GradientBoostingClassifier\n",
"from sklearn.linear_model import LinearRegression,LogisticRegression\n",
"from uplift_analysis import scoring,evaluation,visualization,data"
]
},
{
"cell_type": "markdown",
"id": "bcced28b-c57c-42b1-8e99-354251a3d46e",
"metadata": {},
"source": [
"Next, we initiate the numpy random generator, and assign some parameters:\n",
"\n",
"- `num_treatments` - the number of possible non-neutral actions.\n",
"- `num_samples` - the number of observations composing each of the datasets we'll use.\n",
"- `binary_thresh` - we'll start by generating some stochastic continous response variable, and use this threshold value for transfroming it into a binary response variable.\n",
"\n",
"*Note*: During this tutorial the term **action** will be used interchangeably with **treatment**."
]
},
{
"cell_type": "code",
"execution_count": 6,
"id": "8763c5ff-364a-41b5-99aa-787325684408",
"metadata": {},
"outputs": [],
"source": [
"np.random.seed(2023)\n",
"\n",
"num_treatments = 4\n",
"num_samples = 100000\n",
"binary_thresh = 5.0"
]
},
{
"cell_type": "markdown",
"id": "77612dcc-8859-4987-8f05-3983f179339c",
"metadata": {},
"source": [
"### Synthetic Data Generation"
]
},
{
"cell_type": "markdown",
"id": "ab693583-9ae5-4045-bcd8-14c8691033f2",
"metadata": {},
"source": [
"For demonstrating the suggested methodologies, we'll need some appropriate data. \n",
"For that purpose, we employ a modified version of the setup suggested in the paper [_**\"Uplift Modeling with Multiple Treatments and General Response Types**_\"](https://arxiv.org/pdf/1705.08492.pdf), by *Yan Zhao*, *Xiao Fang* and *David Simchi-Levi*."
]
},
{
"cell_type": "markdown",
"id": "2cf2fb2a-fe2f-4b12-b177-f0eb4b7d36ef",
"metadata": {},
"source": [
"The schema according to which the synthetic data is generated assumes a $d$-dimensional space, and a set of $T$ treatments (excluding the neutral action or *no-action* treatment), where $d > T$.\n",
"\n",
"The feature-space is structured as follows:\n",
"\n",
"- The first $T$ features (out of $d$ in total), are the features that specify and are responsible for the treatment-dependent effect.\n",
"- The rest of the features, $x_i$ ($i=T+1,...,d$), are uniformly distributed in a range represented as a hyper-cube between $[v_{low},v_{high}]$ for each of these variables. Hence, $X_i \\sim U[v_{low},v_{high}]$, for $i=T+1,...,d$.\n",
"- Correspondingly, and in order to allow a negative treatment effect as well, the first $T$ features, responsible for the effect associated with each treatment, are distributed in a zero-centered hyper-cube, as follows: $X_i \\sim U[v_{low} - \\frac{v_{low} + v_{high}}{2},v_{high} - \\frac{v_{low} + v_{high}}{2}]$, for $i=1,...,T$ (fixed values of $v_{low}$ and $v_{high}$ are used for all $i$).\n",
"\n",
"*Note*: On this section, we denote random variables using uppercase letters, and their realizations using lowercase letters."
]
},
{
"cell_type": "markdown",
"id": "378bf91e-6880-4305-9a73-acecdab49619",
"metadata": {},
"source": [
"Moreover, we consider a continuous response variable, modeled as follows: \n",
"\n",
"$$\n",
"\\begin{align}\n",
"Y = f(X) + E + \\epsilon\n",
"\\end{align}\n",
"$$\n",
"\n",
"Components:\n",
"\n",
"- $f(X)$ defines the systematic dependence of the response on the features (regardless of the intervention / treatment). In that case, $f$ is a mixture of $d$ exponential functions, defined as follows:\n",
"$$\n",
"\\begin{align}\n",
"f(x_1,...,x_d) = \\sum_{i=1}^{d} a^i \\cdot exp\\{-b_1^i |x_1 - c_1^i| - ... - b_d^i |x_d - c_d^i|\\}\n",
"\\end{align}\n",
"$$\n",
"where $a^i$, $b_j^i$ and $c_j^i$ are chosen randomly.\n",
"\n",
"- $E$ is the treatment effect, and is unique for each treatment $t = 1,...,T$:\n",
"$$\n",
"\\begin{align}\n",
"E(X,t)=\n",
"\\begin{cases}\n",
"U[0,\\alpha X_{t^*}] & \\text{for $t=t^*$ and $X_{t^*} > 0$}\\\\\n",
"U[\\alpha X_{t^*},0] & \\text{for $t=t^*$ and $X_{t^*} < 0$}\\\\\n",
"0 & \\text{otherwise}\\\\\n",
"\\end{cases}\n",
"\\end{align}\n",
"$$\n",
"so that the effect for assigned to an observation if it was assigned with the treatment $t^*$ is a random value, distributed uniformly between zero and the value of the corresponding attribute $X_{t^*}$, multiplied by $\\alpha$ which sets the magnitude of the effect.\n",
"\n",
"- $\\epsilon$ is the zero-mean Gaussian noise, $\\epsilon \\sim \\mathbb{N}(0,\\sigma^2)$, where the standard deviation $\\sigma$ is identical, regardless of the treatment."
]
},
{
"cell_type": "markdown",
"id": "ca72f69b-6356-4be6-bf46-72e7005cd127",
"metadata": {},
"source": [
"Of course, there are other ways for creating synthetic datasets for the examination of uplift modeling techniques. Refer to this detailed [blogpost](https://humboldt-wi.github.io/blog/research/applied_predictive_modeling_19/data_generating_process_blogpost/#Theory-behind-the-package), by Julian Winkel and Tobias Krebs, for more details."
]
},
{
"cell_type": "markdown",
"id": "2998633c-fbde-4f46-90bf-fdc2bc3511f5",
"metadata": {},
"source": [
"Let us implement and wrap the data generation scheme detailed above, with a class named `TreatmentEffectDataGenerator`:"
]
},
{
"cell_type": "code",
"execution_count": 7,
"id": "6fd9e873-a160-4dc5-99f1-f38d73b3fe38",
"metadata": {},
"outputs": [],
"source": [
"class TreatmentEffectDataGenerator:\n",
" \"\"\"\n",
" A class for generating random treatment effect data, according to a parametric scheme.\n",
" \n",
" Parameters\n",
" ----------\n",
" response_func: dict\n",
" A dictionary containing the lower and upper boundaries for the random variables `a` and `b`.\n",
" It contains the keys `a` and `b`, with corresponding values represented as two-value tuples.\n",
" num_treatments: int\n",
" The number of non-neutral actions/treatments.\n",
" feat_dim: int\n",
" The dimension of the feature space.\n",
" hypercube_bounds: Tuple\n",
" The bounds of the random variables composing the feature space.\n",
" effect_magnitude: float\n",
" A parameter which will scale the randomized effect, computed according to the relevant features,\n",
" for yielding the final effect size for each observation.\n",
" noise_var: float\n",
" The standard deviation associated with the noise factor.\n",
" treat_rate: Union[float,None]\n",
" The rate in which treatments (excluding the neutral action) are assigned.\n",
" \"\"\"\n",
" \n",
" def __init__(self,\n",
" response_func: Dict,\n",
" num_treatments: int = 1,\n",
" feat_dim: int = 50,\n",
" hypercube_bounds: Tuple = (0, 10),\n",
" effect_magnitude: float = 0.3,\n",
" noise_std: float = 0.8,\n",
" treat_rate:Union[float,None] = None):\n",
"\n",
" self.a_bounds = response_func['a']\n",
" self.b_bounds = response_func['b']\n",
" \n",
" assert feat_dim > num_treatments\n",
"\n",
" self.num_treatments = num_treatments\n",
" self.feat_dim = feat_dim\n",
" self.hypercube_bounds = hypercube_bounds\n",
" self.effect_magnitude = effect_magnitude\n",
" self.noise_std = noise_std\n",
" \n",
" assert treat_rate is None or 0 < treat_rate < 1.0\n",
" self.treat_rate = treat_rate\n",
" \n",
"\n",
" # set the random parameters defining the systematic dependence\n",
" # between the response and the feautre space.\n",
" self.a = np.random.uniform(low=self.a_bounds[0], high=self.a_bounds[1],\n",
" size=(self.feat_dim,))\n",
" self.b = np.random.uniform(low=self.b_bounds[0], high=self.b_bounds[1],\n",
" size=(self.feat_dim, self.feat_dim))\n",
" self.c = np.random.uniform(low=self.hypercube_bounds[0],\n",
" high=self.hypercube_bounds[1],\n",
" size=(self.feat_dim, self.feat_dim))\n",
"\n",
" def generate(self, num_samples: int) -> Dict:\n",
" \"\"\"\n",
" The interface method of the class, for generating a sample composed of a desired quantity of\n",
" randomized observations, sampled according to the parametric data model.\n",
" \n",
" Parameters\n",
" ----------\n",
" num_samples: int\n",
" The number of observations required.\n",
" \n",
" Returns\n",
" ----------\n",
" Dict[str,np.ndarray]\n",
" A dictionary holding the following keys: ``feats`` - the feature vector associated with each\n",
" observation, ``treatments`` - the randomly assigned treatments, ``f`` - the systematic dependence\n",
" between the response variable and the features, ``treatment_effect`` - the random treatment effect\n",
" computed and sampled according to the assigned treatment, and ``response``- the resulting response\n",
" variable according to the data model, and the sampled factors. \n",
" \"\"\"\n",
" \n",
" # according to the configured hyper-cube bounds, calculate the center value\n",
" cube_mid = (self.hypercube_bounds[0] + self.hypercube_bounds[1]) / 2\n",
" # for creating the offset bounds of the features responsible for the causal effect:\n",
" effect_feats = np.random.uniform(low=self.hypercube_bounds[0] - cube_mid,\n",
" high=self.hypercube_bounds[1] - cube_mid,\n",
" size=(num_samples,self.num_treatments))\n",
" # the rest of the features are sample according to the prescribed setting\n",
" other_feats = np.random.uniform(low=self.hypercube_bounds[0],\n",
" high=self.hypercube_bounds[1],\n",
" size=(num_samples, self.feat_dim - self.num_treatments))\n",
" # then we concatenate both for creating the union feature set\n",
" feats = np.concatenate((effect_feats,other_feats),axis=1)\n",
" \n",
" # assign treatments randomly (zero is also an option - corresponding to no-action / neutral action)\n",
" if self.treat_rate is None: # uniform choice\n",
" treatments_assignment = np.random.randint(self.num_treatments + 1,\n",
" size=(num_samples,))\n",
" else:\n",
" no_action_rate = 1 - self.treat_rate\n",
" weights = [no_action_rate] + [self.treat_rate / num_treatments] * num_treatments\n",
" treatments_assignment = np.random.choice(np.arange(self.num_treatments + 1),\n",
" replace=True, p=weights, size=(num_samples,))\n",
" \n",
" # compute systematic dependence\n",
" f = 0\n",
" for idx in range(self.feat_dim):\n",
" expit = -np.dot(np.abs(feats - self.c[idx, ...]), self.b[idx, ...])\n",
" f += self.a[idx] * np.exp(expit)\n",
" \n",
" # compute and sample treatment effect\n",
" treatment_effect = 0\n",
" for idx in range(self.num_treatments):\n",
" treatment_indicator = (treatments_assignment == idx + 1).astype(float)\n",
" treatment_effect += np.random.uniform(low=0.0, high=self.effect_magnitude * feats[..., idx]) * \\\n",
" treatment_indicator\n",
" # sample the noise\n",
" noise = np.random.normal(scale=self.noise_std, size=(num_samples,))\n",
" \n",
" # aggregate all for the final response values\n",
" response = f + noise + treatment_effect\n",
"\n",
" return {\n",
" 'features': feats,\n",
" 'treatments': treatments_assignment,\n",
" 'f': f,\n",
" 'treatment_effect': treatment_effect,\n",
" 'response': response\n",
" }"
]
},
{
"cell_type": "markdown",
"id": "d9fb9825-af6c-44ab-8ec5-8e2113733a32",
"metadata": {},
"source": [
"Now, we can initalize the parameterized synthetic data generator, as follows:"
]
},
{
"cell_type": "code",
"execution_count": 8,
"id": "01477c48-06bf-434d-8412-9c08b8b6674f",
"metadata": {},
"outputs": [],
"source": [
"dg = TreatmentEffectDataGenerator(response_func={'a': (0, 0.025), 'b': (-0.05, 0.0275)},\n",
" num_treatments=num_treatments,\n",
" feat_dim=50,\n",
" hypercube_bounds=(0, 10),\n",
" effect_magnitude=0.3,\n",
" noise_std=0.8,\n",
" treat_rate=0.5)"
]
},
{
"cell_type": "markdown",
"id": "b04b8a71-c0aa-4bb6-9023-c2817cbcabf2",
"metadata": {},
"source": [
"And use it for creating corresponding train and validation sets:"
]
},
{
"cell_type": "code",
"execution_count": 9,
"id": "7f1537ff-59de-4cbc-84b4-ce7d4d414c19",
"metadata": {},
"outputs": [],
"source": [
"train_set = dg.generate(num_samples)\n",
"valid_set = dg.generate(num_samples)"
]
},
{
"cell_type": "markdown",
"id": "317b2ba1-9db7-4ffd-b3df-4a18b42dad92",
"metadata": {},
"source": [
"Each of these sets is represented as dictionary of `numpy` arrays."
]
},
{
"cell_type": "markdown",
"id": "68f223e6-ee2c-49c8-8c42-152e02d75230",
"metadata": {},
"source": [
"As noted earlier, our data generation process yields a continuous response variable $Y$. Using a suitable threshold value we can create a synthetic binary response variable:"
]
},
{
"cell_type": "code",
"execution_count": 10,
"id": "dfda1bdc-05f4-4fbf-a5ee-8478c4caed1c",
"metadata": {},
"outputs": [],
"source": [
"train_set['binary_response'] = (train_set['response'] > binary_thresh).astype(int)\n",
"valid_set['binary_response'] = (valid_set['response'] > binary_thresh).astype(int)"
]
},
{
"cell_type": "markdown",
"id": "2a5f02e5-f94c-4966-9f1b-a0b5b9f33843",
"metadata": {},
"source": [
"#### A Brief Glance"
]
},
{
"cell_type": "markdown",
"id": "734d0fcd-8e8c-45c7-8816-242843c5445f",
"metadata": {},
"source": [
"Before moving on, let get a sneak peek at the datasets we created."
]
},
{
"cell_type": "code",
"execution_count": 11,
"id": "b40dc965-c756-4b1f-9f9f-7ab40556c5f0",
"metadata": {},
"outputs": [],
"source": [
"# creating dataframes to represent each set\n",
"train_df = pd.DataFrame({k:v for k,v in train_set.items() if k != 'features'})\n",
"valid_df = pd.DataFrame({k:v for k,v in valid_set.items() if k != 'features'})"
]
},
{
"cell_type": "markdown",
"id": "c2b90345-839c-4e6d-a5c9-ebe10b231e41",
"metadata": {},
"source": [
"Using these dataframes we can view the treatment assignment distribution (and verify that it matches the configuation according to which we initialized the data generator):"
]
},
{
"cell_type": "code",
"execution_count": 12,
"id": "1a98345a-7a72-4eca-8c42-ee304c6b6c04",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": "
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\n"
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"fig,ax = plt.subplots(figsize=(9,4.5))\n",
"assignments = pd.merge(train_df['treatments'].value_counts().rename('train'),\n",
" valid_df['treatments'].value_counts().rename('validation'),\n",
" left_index=True,right_index=True)\n",
"assignments.sort_index().plot(kind='bar',ax=ax)\n",
"ax.grid(True)\n",
"ax.set_xlabel('Treatment Index')\n",
"ax.set_ylabel('# of Assignment')\n",
"ax.set_title('Treatment Assignment Distribution')\n",
"plt.show()"
]
},
{
"cell_type": "markdown",
"id": "2be7d344-1d0e-445b-a0e1-309ec5c32f8c",
"metadata": {},
"source": [
"We can also examine the distribution of the response variable, both overall, and for each treatment sepeartely:"
]
},
{
"cell_type": "code",
"execution_count": 13,
"id": "7cfa4997-d8a1-443c-99c6-fbe0c4fc69fa",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": "
",
"image/png": 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\n"
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"fig,ax = plt.subplots(figsize=(9,4.5))\n",
"ate = pd.merge(train_df.groupby('treatments')['binary_response'].mean().rename('train'),\n",
" valid_df.groupby('treatments')['binary_response'].mean().rename('validation'),\n",
" left_index=True,right_index=True)\n",
"ate.sort_index().plot(kind='bar',ax=ax)\n",
"ax.grid(True)\n",
"ax.set_xlabel('Treatment Index')\n",
"ax.set_ylabel('Binary Response Rate')\n",
"ax.set_title('Binary Response Rate Across Actions')\n",
"plt.show()"
]
},
{
"cell_type": "markdown",
"id": "a442e005-119a-4abc-9184-4c296adb2b26",
"metadata": {},
"source": [
"As demonstrated below, the average treatment effect ($ATE$) associated with each treatment, in our syntetic data simulation is of really small magnitude compared to the magnitude and scale of the response:"
]
},
{
"cell_type": "code",
"execution_count": 15,
"id": "d1e7f80b-55a4-4a6f-9283-c10d3abdc9fd",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": "
",
"image/png": 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\n"
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"fig,ax = plt.subplots(figsize=(9,4.5))\n",
"ate = pd.merge(train_df.groupby('treatments')['treatment_effect'].mean().rename('train'),\n",
" valid_df.groupby('treatments')['treatment_effect'].mean().rename('validation'),\n",
" left_index=True,right_index=True)\n",
"ate.sort_index().plot(kind='bar',ax=ax)\n",
"ax.grid(True)\n",
"ax.set_xlabel('Treatment Index')\n",
"ax.set_ylabel('Average Treatment Effect')\n",
"ax.set_title('Average Treatments Effects')\n",
"plt.show()"
]
},
{
"cell_type": "markdown",
"id": "0b328a2b-5824-4cc9-92ec-7b53e517b2a6",
"metadata": {},
"source": [
"### Acquiring Uplift Scores"
]
},
{
"cell_type": "markdown",
"id": "37bd46db-5bee-4c69-9e8a-6baecb8bfa81",
"metadata": {},
"source": [
"The domain of *Uplift Modeling* refers to a collection of methodologies for solving personalized treatment selection problems. In these problems, the model aims to predict the optimal treatment based on given subject characteristics.\n",
"The general setup includes:\n",
"\n",
"- $\\boldsymbol{X}$: A set of an observation-level covariates, e.g. medical history records patients.\n",
"- $T$: The assigned treatment/action/intervention assigned to each observation, e.g. the medication given to each patient, if at all.\n",
"- $y$: The response variable observed after assigning the treatment $t \\in T$ to context $\\boldsymbol{x} \\in \\boldsymbol{X}$, e.g. the health condition of the patient after $N$ days. We'll assume higher response value is *better* (for continuous response variables), and for binary response variables a response of 1 is the desired outcome.\n",
"\n",
"Using the data $(\\boldsymbol{X}, T, \\boldsymbol{y})$, an uplift model is trained for creating some kind of *policy*, a treatment assignment policy, that will use $\\boldsymbol{x}$ to assign $t \\in T$, in order to maximize the value of $y$. \n",
"In some sense, this type of problem puts the *uplift modeling* under the *umbrella* of **Causal Inference**. For more information regarding this topic, one can refer to the paper [*\"A survey and benchmarking study of multitreatment uplift modeling*\"](https://link.springer.com/article/10.1007/s10618-019-00670-y), by Diego Olaya, Kristof Coussement & Wouter Verbeke, as an example - but there are lots of literature resources for more details on this domain. "
]
},
{
"cell_type": "markdown",
"id": "558f04ae-2f2b-4a65-a462-5192930e9a37",
"metadata": {},
"source": [
"Besides the optimal treatment predicted by the uplift model for each observation, one more output of the model is termed the *uplift score*, which will be denoted as $\\hat{u}_i$, for the $i^{th}$ observation. This score is often used to handle the prioritization of treatment assignment; to give high priority to observations that are expected to benefit the most from the suggested treatment, and low priority to observations that are expected to have low benefit (or even a negativee effect), w.r.t to the response variable, due to the treatment."
]
},
{
"cell_type": "markdown",
"id": "a58b5db5-d11a-4019-b0dd-fc88ac24b980",
"metadata": {},
"source": [
"Often, the *uplift score* (also known as the *uplift signal*) the model outputs, is a proxy, or an estimation of the **Conditional Average Treatment Effect** (or __**CATE**__):\n",
"\n",
"$$\n",
"\\begin{align}\n",
"\\tau ( \\boldsymbol{t}^{'},\\boldsymbol{t}, \\boldsymbol{x}) \\mathrel{\\mathop:} = \\mathop{\\mathbb{E}} \\left[ Y | \\boldsymbol{X} = \\boldsymbol{x}, \\boldsymbol{T} = \\boldsymbol{t}^{'} \\right] - \\mathop{\\mathbb{E}} \\left[ Y | \\boldsymbol{X} = \\boldsymbol{x}, \\boldsymbol{T} = \\boldsymbol{t} \\right]\n",
"\\end{align}\n",
"$$\n",
"\n",
"which quantifies how different will be the expected outcome/response for a covariate vector $\\boldsymbol{x}$, under the treatment $\\boldsymbol{t}^{'}$, compared to another treatment $\\boldsymbol{t}$. The treatment $\\boldsymbol{t}$ can serve as the reference action, the neutral action, or for indicating no-action at all. The neutral action is denoted as $t_0$"
]
},
{
"cell_type": "markdown",
"id": "5647708a-b688-4cbf-a4e4-6e035f28082c",
"metadata": {},
"source": [
"As the goal of this tutorial is to demonstrate the *evaluation* of uplift models, modeling techniques will not be covered here too deeply, and the reader is referred to surveys such as [this paper](https://link.springer.com/article/10.1007/s10618-019-00670-y) for more details.\n",
"\n",
"Instead, we will use quite simple, naive, and not too complex modeling approaches for demonstration purposes. The approaches applied in this tutorial are part of a broader set of techniques for uplift modeling, termed as ***Meta-Learners*** .\n",
"A *Meta-Learner* in the context of uplift modeling, employs possibly multiple *base-learners*, and combines their outputs for estimating the final *CATE*. Each base-learner, which can be represetned by any learning algorithm, used supervised learning, for a specific prediction task.\n",
"\n",
"Here are two examples of Meta-learners:\n",
"\n",
"- ***T-Learner*** takes a *separate-model* approach (also known as *SMA*), according to which the *CATE* is estimated by:\n",
"$$\n",
"\\begin{align}\n",
"\\tau ( \\boldsymbol{t}^{'},\\boldsymbol{t}, \\boldsymbol{x}) \\mathrel{\\mathop:} = \\hat{\\mu}_{\\boldsymbol{t}^{'}}(\\boldsymbol{x}) - \\hat{\\mu}_{\\boldsymbol{t}}(\\boldsymbol{x})\n",
"\\end{align}\n",
"$$\n",
"where $\\hat{\\mu}_{\\boldsymbol{t}}(\\boldsymbol{x})$ is a model, represented by a base-learner, which is responsible for learning $\\mathop{\\mathbb{E}} \\left[ Y | \\boldsymbol{X} = \\boldsymbol{x}, \\boldsymbol{T} = \\boldsymbol{t} \\right]$, and is exposed, during its training phase, only to observations assigned with the treatment $\\boldsymbol{t}$.\n",
"This meta-learner is relatively simplistic, and fail to perform in many scenarios, compared to other advanced meta-learners, such as [*X-Learner*](https://www.pnas.org/content/116/10/4156) and [*R-Learner*](https://arxiv.org/abs/1712.04912).\n",
"\n",
"- ***S-Learner*** in which the treatment indicator is included as a feature, similarly to all of the other features, without the indicator being given any special role. Thus, it employs a single model which expects as input also the identity of the action assigned to the observation:\n",
"$$\n",
"\\begin{align}\n",
"\\tau ( \\boldsymbol{t}^{'},\\boldsymbol{t}, \\boldsymbol{x}) \\mathrel{\\mathop:} = \\hat{\\mu}(\\boldsymbol{x},\\boldsymbol{\\boldsymbol{t}^{'}}) - \\hat{\\mu}(\\boldsymbol{x},\\boldsymbol{\\boldsymbol{t}})\n",
"\\end{align}\n",
"$$\n",
"where the base-learner $\\hat{\\mu}(\\boldsymbol{x},\\boldsymbol{\\boldsymbol{t}})$ is defined as:\n",
"$$\n",
"\\begin{align}\n",
"\\hat{\\mu}(\\boldsymbol{x},\\boldsymbol{\\boldsymbol{t}^{*}}) \\mathrel{\\mathop:} = \\mathop{\\mathbb{E}} \\left[ Y | \\boldsymbol{X} = \\boldsymbol{x}, \\boldsymbol{T} = \\boldsymbol{t}^{*} \\right]\n",
"\\end{align}\n",
"$$"
]
},
{
"cell_type": "markdown",
"id": "f4001136-d66f-4669-ba25-19ad50a05685",
"metadata": {},
"source": [
"Let us apply these concepts for retrieving uplift scores for enabling the evaluation process.\n",
"\n",
"We will consider:\n",
"\n",
"- A single type of meta-learner: the *T-learner*.\n",
"- The two types of response variables available in our datasets: binary and continuous.\n",
"- Two possiblities for base-learners: Gradient-Boosting Decision-Tree (*GBDT*) ensemble, or a simple linear learner (linear regression for the continuous response variable, or logistic regression for the binary response variable)."
]
},
{
"cell_type": "markdown",
"id": "26de755f-d8b4-4748-b618-ca6519908241",
"metadata": {
"tags": []
},
"source": [
"#### T - learner"
]
},
{
"cell_type": "markdown",
"id": "47678710-03ac-4336-8429-89bf9e07c04c",
"metadata": {},
"source": [
"As noted above, for the *T-learner* we train separate models for each treatment, where each model is exposed during training only to observerations that were assigned to a specific treatment."
]
},
{
"cell_type": "code",
"execution_count": 16,
"id": "c73ff3d2-8f6b-4740-84a2-0e436043e24e",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Training\n"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"100%|██████████| 5/5 [00:27<00:00, 5.50s/it]\n"
]
}
],
"source": [
"# accumulate treatment-dependet models for each case:\n",
"t_gbdt_cont_models = [] # response: continuous, base-learner: gbdt\n",
"t_linear_cont_models = [] # response: continuous, base-learner: linear\n",
"t_gbdt_bin_models = [] # response: binary, base-learner: gbdt\n",
"t_linear_bin_models = [] # response: binary, base-learner: linear\n",
"\n",
"print('Training')\n",
"\n",
"# for each treatment\n",
"for treat in tqdm(range(num_treatments + 1)):\n",
" # get the subset of observations related to the treatment\n",
" subset_idx = train_set['treatments'] == treat\n",
" \n",
" # train the treatment-dependent response model\n",
" t_gbdt_cont_models.append(GradientBoostingRegressor(n_estimators=10).fit(X = train_set['features'][subset_idx],\n",
" y = train_set['response'][subset_idx]))\n",
" \n",
" t_linear_cont_models.append(LinearRegression().fit(X = train_set['features'][subset_idx],\n",
" y = train_set['response'][subset_idx]))\n",
" \n",
" t_gbdt_bin_models.append(GradientBoostingClassifier(n_estimators=10).fit(X = train_set['features'][subset_idx],\n",
" y = train_set['binary_response'][subset_idx]))\n",
" \n",
" t_linear_bin_models.append(LogisticRegression().fit(X = train_set['features'][subset_idx],\n",
" y = train_set['binary_response'][subset_idx]))\n",
"\n"
]
},
{
"cell_type": "markdown",
"id": "af545294-4ca7-4e76-9b1d-ae05b6d83e89",
"metadata": {},
"source": [
"Using the trained models, we retrieve the estimations of the response variable, associated with each treatment, and stack them as numpy arrays, which will be included in the dictionary representing our validation set (each model will have a dedicated key):"
]
},
{
"cell_type": "code",
"execution_count": 17,
"id": "f669d1f3-1268-49ad-9e3e-6008d897ffbf",
"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"100%|██████████| 5/5 [00:00<00:00, 8.96it/s]\n"
]
}
],
"source": [
"# accumulate treatment-dependet estimations for each case:\n",
"t_gbdt_cont_outputs = [] # response: continuous, base-learner: gbdt\n",
"t_linear_cont_outputs = [] # response: continuous, base-learner: linear\n",
"t_gbdt_bin_outputs = [] # response: binary, base-learner: gbdt\n",
"t_linear_bin_outputs = [] # response: binary, base-learner: linear\n",
"\n",
"# for each treatment\n",
"for treat in tqdm(range(num_treatments + 1)):\n",
" # apply the treatment-dependent response model on the entire dataset\n",
" t_gbdt_cont_outputs.append(t_gbdt_cont_models[treat].predict(valid_set['features']))\n",
" t_linear_cont_outputs.append(t_linear_cont_models[treat].predict(valid_set['features']))\n",
" \n",
" # in the case of binary response - `predict()` is replaced with `predict_proba()`\n",
" t_gbdt_bin_outputs.append(t_gbdt_bin_models[treat].predict_proba(valid_set['features'])[:,-1])\n",
" t_linear_bin_outputs.append(t_linear_bin_models[treat].predict_proba(valid_set['features'])[:,-1])\n",
" \n",
"valid_set['t_learner_gbdt_cont'] = np.stack(t_gbdt_cont_outputs,axis=-1)\n",
"valid_set['t_learner_linear_cont'] = np.stack(t_linear_cont_outputs,axis=-1)\n",
"valid_set['t_learner_gbdt_bin'] = np.stack(t_gbdt_bin_outputs,axis=-1)\n",
"valid_set['t_learner_linear_bin'] = np.stack(t_linear_bin_outputs,axis=-1)"
]
},
{
"cell_type": "markdown",
"id": "31b1772e-5dfa-4da2-ae8a-29e362feec21",
"metadata": {},
"source": [
"# Scoring\n",
"`uplift-analysis.scoring` is a module that implements the class `Scorer`. The `Scorer` class is used for abstracting the procedure of uplift score computation, in case it is not provided directly by the model (just like in *T-learner* or *S-learner*). It can be used for scoring a gived dataset, according to a provided configuration (or a set of configurations). Each configuration, should specify the relevant fields according to which the score is computed, and the function to apply to these fields. \n",
"*Note*: using the `Scorer` is optional, and it is not obligatory for the rest of the evaluation procedure. It is only used to facilitate the scoring phase."
]
},
{
"cell_type": "markdown",
"id": "364f05a8-cd54-4e56-ad25-1809aac0095a",
"metadata": {},
"source": [
"We'll start by scoring only a single model - the binary response *T-learner* using *GBDT* as a base-learner:"
]
},
{
"cell_type": "code",
"execution_count": 18,
"id": "86818402-02e8-4a4a-b38e-07a6550adc5b",
"metadata": {},
"outputs": [],
"source": [
"t_gbdt_bin_scorer = scoring.Scorer({\n",
" 'scoring_func': 'binary_score_calc',\n",
" 'name': 't_gbdt_bin',\n",
" 'scoring_field': 't_learner_gbdt_bin',\n",
" 'reference_field': 't_learner_gbdt_bin',\n",
" 'reference_idx': 0,\n",
" })"
]
},
{
"cell_type": "markdown",
"id": "30849352-8e15-454f-b9cf-79233eb1ed55",
"metadata": {},
"source": [
"The `scoring_func` key represent the `Callable` object defining the functionality applied for computing the score. It can be either one of the scoring functions implemented as part of the scorer: `binary_score_calc`,`sigmoid_frac_score_calc`, `cont_score_calc`, `identity_score_calc`, or any other user-defined function (for configuring one of the pre-defined function, one can specify the associated function name as a string).\n",
"In addition, `scoring_field` specifies the field according to which the scoring is performed, and the `reference_field`, and `reference_idx` specifies the field and the column index used for inferring the base/reference response estimated, if it is required for computing the scores."
]
},
{
"cell_type": "markdown",
"id": "db3e95f0-15f3-4943-ba9b-bf44a458fa82",
"metadata": {},
"source": [
"Then, applying the scorer for calculating the scores:"
]
},
{
"cell_type": "code",
"execution_count": 19,
"id": "1f5c32c4-4526-4b3d-a675-f17743aba6b7",
"metadata": {},
"outputs": [],
"source": [
"ranking, recommended_action, score, action_dim = t_gbdt_bin_scorer.calculate_scores(dataset=valid_set)"
]
},
{
"cell_type": "markdown",
"id": "ae6a4a79-e560-4ad5-a7e0-68ca4496189c",
"metadata": {},
"source": [
"we get:\n",
"\n",
"- `ranking`: The relative rank $\\in (0,1]$ associated with each observation in the dataset w.r.t to the uplift score, where the highest rank corresponds to the highest score.\n",
"- `recommended_action`: The serial index of the action associated with the highest uplift score, for each observation - inferred as the recommended treatment by the model.\n",
"- `score`: The computed uplift score, for each observation, according to the provided configuration.\n",
"- `action_dim`: The quantity of actions (action space cardinality) taken into account during scoring (including the neutral/no-action)."
]
},
{
"cell_type": "markdown",
"id": "af624a7c-efa9-4dc2-9f0f-b9bcce9d2f8b",
"metadata": {
"tags": []
},
"source": [
"# Evaluation"
]
},
{
"cell_type": "markdown",
"id": "6bfcd5db-d51a-47b7-b176-eb7bdc087761",
"metadata": {},
"source": [
"An uplift model can be considered as a dynamic and continuous policy $\\pi(\\boldsymbol{x},q)$. $\\boldsymbol{x}$ represents the context / the featre vector associated with an observation, $q$ can be treated as the rate of exposure of the model's recommendations (further elaboration to follow), and $\\pi$ is a function of both which outputs the actual action - whether or not to assign a treatment to the observation, and which treatment it will be. \n",
"Usually the considered treatments are associated with some cost, and in most of the cases assigning treatments (that are not the neutral action) to the entire population is not feasible. Moreover, some of the observations might be associated with negative effects as a result of a/the treatment. \n",
"\n",
"As noted the uplift score is used to serve as a proxy measure for the positive effect estimated and associated with a specific treatment. Hence, higher uplift scores imply higher magnitude (more positive) effect on the response variable. \n",
"\n",
"Hence, the variable $q$, controlling $\\pi(\\boldsymbol{x},q)$, corresponds to the *exposure rate* of the recommendations of the model, in terms of score quantiles. It means, that the upper $q$ quantiles of the scores are exposed to the recommendations of the model, and the rest of the population, associated with lower scores, are not exposed to the recommendations, and get the default/netural/no-action treatment, noted from now on as $t_0$. "
]
},
{
"cell_type": "markdown",
"id": "dfdf60fc-b88b-4e7c-a07e-ce1991f3ceed",
"metadata": {},
"source": [
"Therefore, each upper quantile $q=q^{*} \\in (0,1)$, can also be interpreted by a corresponding threshold, given the distribution of uplift scores, $\\boldsymbol{\\hat{u}}$, observed among the validation set. The corresponding threshold is defined as follows:\n",
"$$\n",
"\\begin{align}\n",
"Thresh(q^{*},\\boldsymbol{\\hat{u}})=p_{q^{*}}, \\hspace{0.5cm} \\text{for} \\hspace{0.5cm} \\frac{1}{N} \\sum_{i=1}^{N} \\mathbb{1} \\left[ \\hat{u}_i \\geq p_{q^{*}} \\right] = q^{*}\n",
"\\end{align}\n",
"$$\n",
"where $N$ denotes the number of observations in the evaluated dataset, and $\\mathbb{1}$ denotes the indicator function."
]
},
{
"cell_type": "markdown",
"id": "0a13ddc9-ca57-4559-b395-8ccb3d6a6d3e",
"metadata": {},
"source": [
"Accordingly, for each value of $q=q^{*} \\in (0,1)$, the dynamic policy $\\pi(\\boldsymbol{x},q)$ is fixed as $\\pi(\\boldsymbol{x},q^{*}) = h_{q^{*}}(x)$, which is mapping from the feature space to the space of treatments, i.e. $h(\\cdot) : \\mathbb{X}^d \\rightarrow \\{t_0,t_1,...,t_T \\}$. Each fixed mapping $h_{q^{*}}(x)$ assigns the treatments recommended by the model to observations associated with high uplifts scores, or more precisely to observations associated with uplift scores that are in the upper $q^{th}$ quantile of the score distribution (those with $\\hat{u}_i \\geq Thresh(q^{*},\\boldsymbol{\\hat{u}})$), and assigns the neutral action to the rest of the distribution (where $\\hat{u}_i < Thresh(q^{*},\\boldsymbol{\\hat{u}})$).\n",
"\n",
"Each value of $q=q^{*} \\in (0,1)$, and the corresponding $h_{q^{*}}(x)$ and $Thresh(q^{*},\\boldsymbol{\\hat{u}})$, define what will be termed as the *acceptance region* - the range of scores, $\\hat{u}_i \\geq Thresh(q^{*},\\boldsymbol{\\hat{u}})$ , in which the model (or the resulting *policy*) aims to assign a treatment (non-neutral action, action different than $t_0$), and the complement *rejection region* - the range of scores, $\\hat{u}_i < Thresh(q^{*},\\boldsymbol{\\hat{u}})$, where the model will assign the neutral treatment $t_0$."
]
},
{
"cell_type": "markdown",
"id": "d0bf4f5f-3b5b-4e07-9a34-d452b24a0249",
"metadata": {},
"source": [
"## Representing Evaluation Sets with `EvalSet` objects"
]
},
{
"cell_type": "markdown",
"id": "3bbccf57-9453-4ed0-8c09-2c4ed40adbbe",
"metadata": {},
"source": [
"Equipped with this terminlogoy, we will create a corresponding `EvalSet` object (implemented in `uplift_analysis.data`). `EvalSet` is a dataclass used to represente a dataset object, going through the uplift evaluation procedure, together with the corresponding meta-data. \n",
"For creating, a `pandas.DataFrame` is required, along with the specification of the following:\n",
"\n",
"- `observed_action_field`: The name associated with the field / column containing the actual action assigned for each observation in the evaluated set.\n",
"- `response_field`: The name associated with the field / column containing the observed response for each observation in the evaluated set.\n",
"- `score_field`: The name associated with the field / column containing the output score for each observation in the evaluated set.\n",
"- `proposed_action_field`: The name associated with the field / column containing the recommended action by the model, for each observation in the evaluated set.\n",
"- `control_indicator`: The action value associated with the neutral action."
]
},
{
"cell_type": "code",
"execution_count": 20,
"id": "e3c92a8d-8e41-47ad-831c-edf995a6430b",
"metadata": {},
"outputs": [],
"source": [
"scored_df = pd.DataFrame({\n",
" 'recommended_action': recommended_action,\n",
" 'score': score,\n",
" 'observed_action': valid_set['treatments'],\n",
" 'response': valid_set['binary_response'],\n",
" })\n",
"\n",
"eval_set = data.EvalSet(\n",
" df=scored_df,\n",
" observed_action_field='observed_action',\n",
" response_field='response',\n",
" score_field='score',\n",
" proposed_action_field='recommended_action',\n",
" control_indicator=0,\n",
" )"
]
},
{
"cell_type": "markdown",
"id": "00540d4d-52ab-43bf-9729-63bcdce2792e",
"metadata": {},
"source": [
"## Performance Evaluation Using `Evaluator`"
]
},
{
"cell_type": "markdown",
"id": "c4abc93a-5440-4092-adfb-2f14a25181c6",
"metadata": {},
"source": [
"For performing the evaluation procedure of the dataset represented as an `EvalSet` object, we employ an `Evaluator` object (implemented under `uplift_analysis.evaluation`)."
]
},
{
"cell_type": "code",
"execution_count": 21,
"id": "8711f4d4-ddcc-4b05-8aec-8bbb0faf3619",
"metadata": {},
"outputs": [],
"source": [
"evaluator = evaluation.Evaluator()\n",
"eval_res,summary = evaluator.evaluate_set(eval_set)"
]
},
{
"cell_type": "markdown",
"id": "d4ad4d9e-64d5-48cf-ab93-58f464c0ae6a",
"metadata": {},
"source": [
"As a result of the evaluation, we get:\n",
"\n",
"- `eval_res`: The resulting `EvalSet` on which the evaluation was performed.\n",
"- `summary`: A gross statistics summary of the evaluation process (the values contained in this summary will be elaborated [later in this tutorial](#Evaluation-Summaries))."
]
},
{
"cell_type": "markdown",
"id": "9d7b87ea-c48b-4143-a2b0-f5a7c213e538",
"metadata": {},
"source": [
"## Inspect Treatment Assignment\n",
"Before visualizing the evaluated performance, it can be very useful to examine how the treatments are distributed according to the model. \n",
"It can easily expose tendencies of the model to prefer a specific treatment, or a region of the score distribution, in which other treatments are preferred by the model. Insights such as these can expose other pitfalls or strengths of the model. \n",
"For describing the assignment of treatments and their distribution, we show the cumulative sum of assignments for each treatment, as the accepatance-region is expanded, and the score threshold goes lower."
]
},
{
"cell_type": "code",
"execution_count": 22,
"id": "6292c84b-fcae-4a49-b2e1-357f2ccf7b63",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": "
",
"image/png": 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\n"
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"_ = visualization.visualize_selection_distribution(eval_res)"
]
},
{
"cell_type": "markdown",
"id": "0ed1f53e-83c4-47ec-a431-0b5df1922e23",
"metadata": {},
"source": [
"In the case of the dataset we generated, there should not be any preference towards a specific treatment, thus the assignment rate is quite similar across all the treatments. However, in real-life scenarios, preferences of the model will be easily observed in a similar chart."
]
},
{
"cell_type": "markdown",
"id": "c6627860-ff8d-4dfa-870d-d19c95ed01e6",
"metadata": {},
"source": [
""
]
},
{
"cell_type": "markdown",
"id": "b956e070-9fdb-457b-a5f7-bc420807ea90",
"metadata": {
"tags": []
},
"source": [
"### Inspect Operating Point Treatment Assignment Distribution"
]
},
{
"cell_type": "markdown",
"id": "6294e518-fc40-4e1f-9291-ae44dc4d0fce",
"metadata": {},
"source": [
"In practice, when an uplift model is deployed for treatment assignment on new observations, the score threshold $p_{q^{*}}$ should also be specified. The threshold defines the bounds of the acceptance region w.r.t uplift score. \n",
"In inference, the acceptance region cannot be defined using the specification of the upper quantile $q=q^{*} \\in (0,1)$. As opposed to the *offline* evaluation of the validation dataset, in the phase of inference, we won't necessarily be exposed to a distribution of samples; possibly only to a single instance (in streaming use-cases), for which the model will need to decide, whether to apply the recommendation of the model or not. Thus, in practice, a score threshold, inferred according to the observed distribution of uplift scores would be used.\n",
"Thresholding and bounding the acceptance region of model recommendations, might be required due to multiple reasons. Two prominent reasons could be i) budget limitations which prohibit the assignment of treatments (which impose some cost) to the entire population, or ii) a negative effect on the response due to the treatment for specific segments of the population (termed in the literature as \"*sleeping dogs*\"). \n",
"\n",
"The selected threshold applied to new instances, as part of the deployment of the model, is termed as the *operating point*. Inspecting the assignment distribution under the chosen *operating point* can also be useful:"
]
},
{
"cell_type": "code",
"execution_count": 23,
"id": "77be7ae9-5b42-4843-92f9-df77541ce914",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": "
",
"image/png": 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SJW9NlLSiug9gd9Dl3+wKOed+N7ND8a1furL73C43syfwLTi253Hb2V33+VkulF4ln+stiGzPufNjLW0k9+cciva8i0guKAghUnJE+zVmTfA+zTl3fK5X5NzXQK9gdOlDgOPwU04+aGY7nHOP5bOOoS/jNbMpUyuibHbrqmpmlSO/TAcD1lWLtlCMXxizk+4yT2n5U/DeOEb5xhHlsvMr/stSAzNLcs7tiMjPy7oKYlXwnuOMHs5PLxuX1iTOueyu6bOccy/kclU34bugnOOcmxCeYWbDyP6BLx7WBO83OufuSGRFcis4N/8AdwYDrN6KH7jw1LBia4DK+PEacvq1GHyXDsjdL+qF+VlSXKwJ3vNybedHfj4743UPhZ/XaA+lxeKcmlkqu3+Z/zKn8s65n4CzzE/x3BLfTeRifGCiAr6FSV7k5n6KJtb9EkpfE5YWaqUR61miSj7rECnbezkYtLIivpuWiOwhNEWnSMm2EP/Fvq2ZJed1Yefcdufc18652/GDmYHvn5kvzrn1wM9AqpkdEpkfpKUBi3LoigG7mzhH++W4PbF/Abk1j6+BEcuHZrzI0rw8+LLUDj/bxVc51J+gOe3n+C+h0fYjtI1sZ9koBEcG79Ga6RY3XwTvHfKwTKPg/Y0oeUfHWCbUtD0ev6TlZ5/yo6j26U78mAR9zax9WPoX+IH3skwtHMPX+AefI80s22bUhfxZUlzE6zrIz2dnvO6hUN06R2YE/4e1wz+Af5eHdRaFG/DdUWYHAYZccc7tcs7Ndc49iJ8lBTL/n1rUnzt1zaxhlPROwXv4cQ0FBbNMKRz8XxctEJ+f+i/E/5/ZNJglKFJoRqpo3ZpEpJhSEEKkBAv6CD+I/zI+xqLMAW9mlczs8LC/28UIWIR+pdhcwGo9HbzfF/yCGtpuuaCusHuqvew8E7zfZmbhTe+T8Q9FUTnnLI+vThGrmAEsANqbWWRA5nZ8QGG8c25jeIaZNQ1ekc25Q61K7gg/7ubnjr8E2BK2r/kSnOOmUdJLmdk1+IeRFUSZdrQYegs/IOEgMzstWgEza2xmdcOS0oP3DhHlziFKMCkQ+tWtboz8QuOc+w4/PecJZnZF8GtpJma2f7RzmEer8Q9wWR4qCiIIpoW66IwOywoNcvt/wVgimZhZkpllPGw651bgZ8WoCjwa/CofXr6MmYV3Eyisz5LiIj/Xdn7k57MzPXgv6ntobPB+nZlFXqe34ruJvOOc+4sEMLMUMxsFXIv/bL4sF8u0MbMqUbKi/Z9a1J87pYB7wj9jgilErw/+fDas7EJ8K4WjzKxZWPnS+EFpo31PyPNnTNAVZTy+O8/dEXVLw0+HCnvWvSxS4qk7hojcDrQAzsY/5HyInxs+Dd+/vwN+oKxeQflrgWPNbBawBD/tWSP8yO3b8NOkFcQDwPH4XzcWmNmbQXpP/MwNH+Dnlc+Wc+5FM+uL/xVpgZm9zu657lfgB4WL9qtKgTjndpnZQPxD40vBeAqL8YPKHY0fYO/GKIuGBvZswO4v9DjnXjazXviZKuaZ2RR8n+/T8c1dhzjnfg9fkZlVA+4NS6ofvN9rZqFffZ92zn0a/Hsf4Acz+w4/COVf+Ae99sCB+BkW+gW/LhdrwYCnvfHXyUtmdi3+F7I1+Gb8zfF91Hvjr3PwD6QnAK+a2Sv4PtyH4H/9exXoG2VT0/BdC54KzvF6YI1z7tGi2C/gLPxgfA8CF5nZ50E99wOa4FsTDMU/GOSLc26DmX0BtDOzt/C/em4HZjrnZhas+jyP/+w4ysx6OOfedM7NMLOh+GDET2b2LvALvnXE/vh7piyZm3Vfhr8mz8S3iJiKH8+hDr5b2J3sDjAUymdJcZHPazs/28nPZ+eDxOEecs59ZWYj8eOIzAu2tRL//1Q7/H4Pycdu51lY171SQCX8L/9HB//+HTjXOZdjVwygP/6e/gx//a/EX/898Q/s4YGfn/CDKh5tZhPxQamd+GlJ5xV0n/DTHrcG/mdm7wX7ciq+C8794fsTXI8P4GfC+Sw4F1vwrVSS8OMHtQpfeQE+Y4bh/z86G2hpZh/gA/p98MGaZ5xzkwu68yISPwpCiJRwQWuI04Jf1gbhv8hXwY8D8AfwCH5GjJDH8V+SjsA30y+Hf2h9EbjPOTe/gPXZbmYn4R82zgYuCrJ+wj9kPRplbIRY+gHX4PdrCH6U/sn4/ssFqmd2gsE72wAj8A9AvfGD6d2HH2RsTR5XeTa+W8b5+NYP2/Ejvd/tnHsvSvkUYECU9PCWGdPxI92DP9ePAofiH9qqBttIBx4GHnDOpeexzgnjnPvBzA4CrgB64B/gS+P7kP+Ev7ZmhJV/z8xOxl8XvfFf6r/Gf5luSPQHqLH4B4UzgavwAwj+hj+ORbFPf5sfvG4IcFpQp/L4h71f8b9UvlwIm+qPv06PBk7CP2CNAAoUhAiCczfhp928w8zeDpqePxg8fF2Bf5Dsim96/Tf+l//XItaz1syOxk8Z2A/fHaoU/jPoHXaPlF/YnyXFQl6v7QLI02dnPO8h59wtZvY//L6ehv/F/U980OnOiMFPi1Kodc8OfADlL/w1+zZ+SuwtuVzPJPy+H4V/aE/Bn88P8J+9n4UKOud2BkHpu4Bu+PNk+P0vjCDEauBEfIulgfhBIX8GbnLOPRml/G34IPWFQfmV+C45NxJx74bJ82dMcN8fhR8b41T8DF078Ps8LGJcJhHZA1juxoISERERERERESkYjQkhIiIiIiIiInGhIISIiIiIiIiIxIWCECIiIiIiIiISFwpCiIiIiIiIiEhcKAghIiIiIiIiInGhIISIiIiIiIiIxIWCECIiIiIiIiISFwpCiIiIiIiIiEhcKAghIiIiIiIiInGhIISIiIiIiIiIxIWCECIiIiIiIiISFwpCiIiIiIiIiEhcKAghIiIiIiIiInGhIISIiIiIiIiIxIWCECIiIiIiIiISFwpCiIiIiIiIiEhcKAghIiIiIiIiInGhIISIiIiIiIiIxIWCECIiIiIiIiISFwpCiIiIiIiIiEhcKAghIiIiIiIiInGhIISIiIiIiIiIxIWCECIiIiIiIiISFwpCiIiIiIiIiEhcKAghIiIiIiIiInGhIISIiIiIiIiIxIWCECIiIiIiIiISFwpCiIiIiIiIiEhcKAghIiIiIiIiInGhIISIiIiIiIiIxIWCECIiIiIiIiISFwpCiIiIiIiIiEhcKAghIiIiIiIiInGhIISIiIiIiIiIxIWCECIiIiIiIiISFwpCiIiIiIiIiEhcKAghIiIiIiIiInGhIISIiIiIiIiIxIWCECIiIiIiIiISFwpCiIiIiIiIiEhcKAghIiIiIiIiInGhIISIiIiIiIiIxIWCECIiIiIiIiISFwpCiIiIiIiIiEhcKAghIiIiIiIiInGhIISIiIiIiIiIxIWCECIiIiIiIiISFwpCiIiIiIiIiEhcKAghIiIiIiIiInGhIISIiIiIiIiIxIWCECIiIlKsmNlwM3NmNjCBdUg3MxeR1imo17gEVatY1UNERCQ/FIQQEZFiJ3jAystrXILrOzCox/BE1qOwmdn0YL/q53G5+lHO0VYzW25m35nZM2Z2spklFVG99+jzsacGGcKCR5Hn/Q8ze9nMjiyk7ezR51dEpKQrkv/8RURECmhElLSBQD1gPJAekTenaKsj+bQWeDD4d2mgCnAgcCZwLrDAzM52zs2JWO5R4EXg77jUMrpjgTIJ3H52vsYfx7WJrkgMM4Dpwb8rA4cCpwJ9zKyvc+71RFVMREQST0EIEREpdpxzwyPTzKwTPggxzjk3Pb41knxaE+Nc7gPcDQwCPjSzw51zv4bynXMrgBVxq2UU4fUpbpxzm4CFia5HNqZHnnczuwUfXLwXUBBCRKQEU3cMERHZo4WPH2BmJwZdCNaG9+c3b6CZzTSzNWa2xcx+MrNRZpYSZZ1HmdnjZvZ9WPlFZnavmaVFlJ0OPBv8eWtEU/ROQZmM5uNm1trMpprZ6qCeU83swKBcNTP7PzNbGmxznpn1ymbfe5rZ+2a20sy2mdkSM3vYzGpEKZvRtcLMzjOzOWa22cxWmNnzZrZfWNn6wfHrGCQtCdun9FydmGw451Y6584DXgJCAYnwukYdE8LMWgZ1XRwcn5XBOXrSzKqH9pO8nY/DzOwdM1sV3vXEoowJEVGXxmb2WlCHTWb2lZmdEqVctl0HIrcTdMH4JPhzQET9BwZlYnbXMLPqZna/mf1ivivEajObZmbdo5QNdZuZbmZVg2v+r2C5RWY21Mws1jHIo/8L3huaD0KF16NQ77ewsnm5P+qb2RNm9nNwPteY/4wYb2aNCukYiIgIagkhIiJ7j77AicC7+AeeegBmVhp4BegNLAn+vQ44ErgR6G5m7Z1zG8LWdRVwOPBpsL7yQDvgauAk87/crw/KjgPWAD3J3AwdsnYbORS4Lig3FmgBdAXamFk74IOgbq8AaUA/YLKZHemc+zp8RWb2MHAZsAx4C1gOHByk9QyW+SvKcRodbPMt4COgM3AWcIiZHeKc2xbszwh2d4F5KEgj7L0w3AKcDvQws0phxzQLM2uJ74bggLeBxUAFoAFwNvAE/hiMI/fn40hgGP48PwNUA7blot4NgC+BH4ExQA3gNPy5usw592gu1hHLG8H7AGBu2N+QQ7cjM9sfvy91gS+AV/H7dCrwlpnd6Jy7I8qiVYDPge3AZKBcsMx9+GM8Kj87ko0dEX8X+v2Wl/vDzGoCs4FU4D18S40y+OPYI/j7lwLus4iIhDjn9NJLL7300qvYv/APGw7oFJE+PEjfBZwYZbkbg/yxQJkYy94bkd4AsCjrGhmUvy4ifWCQPjxG3UP5DjgrIm9MkL4KHzwpFZZ3ZpD3WsQyZwXp7wIpMbb1aozj9ztQNyw9CZgZ5J0aY5n6eTxX9YPl0nNR9o/I8xp2XgaGpd0XpPWKso6KQHI+z8eFMcqk+69JmdI6hS33QEReU2ADsDXi+OZUl+y2My7GMlHzgXeC9HuinI/l+HukbZTz5ICngdJhec3wwYLVRNw32ZzL0HnLsq/4oJYD5kbJK+z7LU/3Bz4w4YAro6yrLFA5L9e/XnrppZde2b/UHUNERPYWU5xz74UnmFkp4Ar8AH4XO+e2RywzElgJ9A9PdM4tcc5Fa4r/QPB+Qj7r+KlzbmJE2oTgvRzwX+fcrrC8l/C/Th8SscxQ/EPTIJe5BQfOuXH4X8x7mVmlKHW4zTn3e1j5Hexu3n547nel0CwN3rM0kY9hc2SCc26jcy5Lei7Mcc49mY/l1gK3RtRhIT6IVBb/EBxXZlYbOAn4N0rd0vEtYAw4P8rim4ChzrmdYcv8AHyGbyXRJI/V6RR0dRkedA35DN/qZQ0wOLJwEdxv+b0/ol1b25xz6/K4fRERyYa6Y4iIyN7i6yhpjYHqwG/AsBjd27cCtcxsH+fcSgAzq4gPXvQO1lEJ/wAXUjufdZwdJS00A8QiF9EdwTm308z+BeqE0sysAj4osQ64MMY+lcXPRtEY+DYXdfgjeE+LklfUQjsQc/yFwCTgcuANM3sN35XkC+fcjwXYdrRrJjf+F+PBdDq+C0HrfNco/0Lb/ML5gSsjTQve20TJ+znG/uT3uujI7vFEQpbjW7v8EFm4MO+3fN4fU4DbgcfMrCvwPr47y7yIoKCIiBQCBSFERGRv8U+UtNAAePWI+HU4ihRgpZmVAT4GDgN+xverX8busQJuxbdayI9oUyruyCYvlB/+/3Ua/gEtldztU6Q12dShdA7rKwqhB8x/syvknJttZkcBN+DHAzgTwMx+B+53zj2Uj21Hu2YKslwovUo+11sQqRF1iBQaH6RKlLw1MZbJ73Uxwjk3PBjUcl/8dKy3A++Y2WHOueWhgkVwv+X5/nDO/W5mh+Jba3TFX18Ay83sCWBUlFZUIiKSTwpCiIjI3iLaL+lrgvdpzrnjc7menvgHog+Ak8KbqJufQSKnB5uiFgpW/Oyca5zQmhSQmTXBByG2k7XFRhbOD87ZK3hwPQQ4DrgEeNDMdjjnHstjFXJqfRFLzRzS14SlhX5Jj/Wdq0o+6xApdF3EqlutiHJFLuhi8Q9wp5mVw987j+MHvQwp7PstX/eHc+4n4KygC1dL/ICtF+MDExWA/+axHiIiEoPGhBARkb3ZQvzAem3NLDmXy4Sm43s7/IEocHSMZULlirwlQdDHfT7wn2AcgKJU1Pt1W/A+JbLvfnacc9udc187524HzgiS+4QVKep6H2JmlaOkdwrevwtLWx287x9ZOJj6MTUynfzVP7TNI2Jc68cG7zkGe4rInfhBOPuaWfuw9EK93wp6fzjndjnn5jrnHgS6BMl9sllERETySEEIERHZawUPNQ/im2iPiTZQo5lVMrPwARnTg/cOEeXq4Qf3i2Zl8F63IPXNg3vx/4ePM7MsAzqaWfmIB738KpL9MrN9zOxp/LSWK4Hrc7FMuxgP16Ff/sMHFSzq85GKn+0hg5k1BS7CdyMIH3x0Nr41RM/wcxXsy8Mx1p/n+jvnluJng9gXuCmibvXwU5GGZsGIO+fcVna3agi/j9KD98K83/J0f5hZGzOrEmU90a4tEREpIHXHEBGRvd3tQAvgbOAEM/sQP01lGn6Kwg74geh6BeXfAn7B/2L7KfA5vin7yfiHvAZRtvE5sBE4w8y24wfCdMAE59xvhb1DzrnnzOxg4CrgFzN7D/8wVxH/YNYBWAIcXMBNTcM3nX/KzCYD64E1zrlHc7l8FTMbHvy7NP7hvRnQHt/P/3ugv3Pu11ys61rgWDObhd+3dfhf0U/GP/jfE1a2qM/HTGBAMI7ALPzMHqfhj//lEbOP/G1mz+Gnhvyfmb2O//51HPAnfqyGWplXz0/4QSGPNrOJwCL8r/9vOufmZVOvi/AzWtxgZh2AT4Fq+HOYCtzqnPumIDteQM/jz+NRZtbDOfcmRXC/5eP+6A9cFMzi8Qs+yLE/vquIw7fiEBGRQqIghIiI7NWC1hCnmdlpwCD8w18VYBX+Qe8R/MwLofIbzewY/K+wnfCzCSzGBzPuB06Pso01ZtYb/0vv6eweEPJT/ANSUezXUDN7FxiCb7beC/9gvhR4Dni5EDYzFv8wdib+ga4Mfn9yG4QIHxxwGz6I8TvwAvAGMDWYIjQ3Hsc/HB4BHIkPYvwFvAjc55ybHyoYh/OxBD/V5GjgQiAZ3wXgLufc5CjlL8SPjXBWsNzf+GNwG5Bldo9gVpRewF1AN6AffrDFP4GYQYhggMU2+ME7T8ZPVbkZ3wXjoeChP2Gcc7vM7CbgdeAOM3u7qO63PN4fk/DX9lFAq2B9/+DHqXjAOfdZIR0CEREBLPq0zCIiIiIiIiIihUtjQoiIiIiIiIhIXCgIISIiIiIiIiJxoSCEiIiIiIiIiMSFghAiIiIiIiIiEheaHSNOqlWr5urXr5/oapRYGzdupGLFigVez44dO/jtt99Yt24dSUlJ1K5dm6pVq2Yp99dff/H3339TqtTuOF+zZs0oV64cAN9++22mvLS0NHR9SFEprOtfZE+k619KMl3/UpLp+k+sb7/9doVzrnq0PM2OESdt27Z1s2fPTnQ1Sqzp06fTqVOnAq+nX79+7Nq1i7FjxzJnzhy6devG559/TvPmzTOVGz58OL/88gvPP/981PWYGT///DONGjUqcJ1EclJY17/InkjXv5Rkuv6lJNP1n1hm9q1zrm20PHXHEMmljRs3MnnyZEaOHElKSgrt27enR48eTJgwIdFVExERERER2SMoCCGSS4sWLSIpKYnGjRtnpLVq1YoFCxZELf/WW29RtWpVmjdvzhNPPJElv0OHDtSsWZNTTjmF9PT0oqq2iIiIiIhIsaEghEgubdiwgcqVK2dKS01NZf369VnKnnbaafz4448sX76cp556ittuu41JkyZl5M+YMYP09HQWLlxIrVq16N69Ozt27CjyfRAREREREUkkBSFEciklJYV169ZlSlu3bh2VKlXKUrZZs2bUqlWL0qVL065dO6644gpeffXVjPwOHTpQtmxZqlSpwkMPPcSSJUv48ccfi3wfREREREREEklBCJFcaty4MTt27ODnn3/OSJs7d26WQSmjMTOyGwQ2p3wREREREZG9gYIQIrlUsWJFTjnlFG655RY2btzIZ599xpQpU+jfv3+WslOmTGH16tU45/j66695+OGH6dmzJwALFixgzpw57Ny5kw0bNnD11VdTu3ZtDjzwwHjvkoiIiIiISFwlJboCInuSxx9/nEGDBlGjRg322WcfnnjiCZo3b86sWbPo2rUrGzZsAODFF19k0KBBbN26lTp16nDdddcxYMAAAJYtW8aQIUP4888/qVixIu3atePtt9+mTJkyidw1ERERESmgrVu3smrVKtavX8/OnTsTXZ0SLTU1Vd2di0DZsmWpVq0aqamp+V6HqQl4fLRt29bNnj070dUosQo6T3DL8S0LrzL5MH/A/IRuX/ZsmidbSjJd/1KS6fqPr61bt/L777+TlpZG5cqVKVOmDGaW6GqVWOvXr486dpvkn3OOzZs38+eff1K3bl3Kly8fs6yZfeucaxstT90xRERERERECmjVqlWkpaVRrVo1ypYtqwCE7HXMjAoVKlCtWjWWL1+e7/UoCCEiIiIiIlJA69evzzKdu8jeqFKlSmzZsiXfyysIISIiIiIiUkA7d+7UGF9SIiQlJbFjx458L68ghIiIiIiISCFQFwwpCQp6nSsIISIiIiIiIiJxoSCEiIiIiIiIiMSFghAiIiIiIiJSJMyM888/P9HVSIhx48ZhZqSnpye6KsVKUqIrICIiIiIisjerf/07ia4CAOmjuxV4HX///Td33XUX77zzDn/88QcVKlTgkEMO4cILL+S0004rhFrK3k5BCBEREREREcnRN998Q9euXdm8eTPnnnsuBx98MGvXruXll1/m9NNPZ+rUqTz77LMaoFOype4YkierVq2id+/eVKxYkXr16vHCCy9ELTd8+HDKlClDSkpKxmvx4sUZ+XPmzKFNmzZUqFCBNm3aMGfOnDjtgYiIiIiI5NXatWs55ZRTAPj666959NFHOf/887n66qv58ssvueSSSxg/fjwPPPBAgmsa26ZNmxJdBUFBCMmjSy65hLJly7Js2TImTpzIkCFDWLBgQdSyp59+Ohs2bMh4NWzYEIBt27bRs2dPzj77bFavXs2AAQPo2bMn27Zti+euiIiIiIhILo0ZM4Y///yTu+++m+bNm2fKMzPuv/9+GjZsyB133MGWLVuyLP/aa6/RsmVLypcvT9OmTZk4cWKWMk8++SStWrUiJSWFypUr06xZM0aMGJGpzPbt27n99ttp2rQp5cqVo2bNmgwePJhVq1ZlKteiRQu6dOnCzJkzadeuHcnJydxwww2cfPLJ1KxZk507d2bZ/vnnn0+FChXYsGFDRtpHH33EMcccQ6VKlahYsSIdO3Zk1qxZWZb98ssvadeuHeXLl6du3bqMHj0a51z2B7WEUhBCcm3jxo1MnjyZkSNHkpKSQvv27enRowcTJkzI03qmT5/Ojh07uPLKKylXrhyXX345zjk+/vjjIqq5iIiIiIgUxJQpUyhXrhxnnnlm1PyyZcty1llnsXLlSj777LNMeV999RWDBg2iZ8+ejB49mgoVKnD22Wfz0ksvZZR59tlnueiii/jPf/7Dvffey1133cXxxx+f6YHfOUefPn0YNWoUXbp04ZFHHmHgwIFMnDiRY445JkvwY8mSJfTs2ZMjjzyShx9+mM6dO9OvXz+WLVvGJ598kqnstm3beO211zj55JNJSUkB4OWXX+b4448HYOTIkYwaNYo1a9Zw7LHHMnPmzIxlf/jhB7p06cKSJUu46aabuPTSS3n66ad56KGH8nGk934aE0JybdGiRSQlJdG4ceOMtFatWjFjxoyo5d966y2qVq3Kfvvtx6WXXsqQIUMAWLBgAQcddFCmvmIHHXQQCxYs4MQTTyzanRARERERkTz74YcfaNKkCeXLl49Z5uCDD84oe+yxx2akf//993z88cd07twZgMGDB9OqVSuuueYa+vbtS+nSpXnzzTdp3rw5r732Wsz1v/jii7z11lt88MEHHHfccRnpxxxzDCeccAITJkzgggsuyEhfvHgxkydPzuhGAv6H1QoVKjBp0iS6dOmSkf7ee++xevXqjCDLxo0bGTJkCGeccUamVhsXXXQRLVu2ZNiwYRnBlptvvpmtW7fy3XffZTwrnXvuuRxwwAGxD2gJppYQkmsbNmygcuXKmdJSU1NZv359lrKnnXYaP/74I8uXL+epp57itttuY9KkSRnrSU1NzdV6REREREQk8datW5flWSBSKH/dunWZ0g866KCMAARAhQoVGDx4MH/++WfG2HBVqlThjz/+4Isvvoi5/pdeeomGDRtyyCGHsGLFioxX69atSU1NzdKyer/99qN3796Z0ipWrEiPHj147bXXMnUHnzRpElWqVKFr164ATJs2jVWrVnH22Wdn2tbGjRvp0qULX375JZs2bWLnzp289957nHTSSZl+rK1evTpnnXVWtserpFIQQnItJSUlywfKunXrqFSpUpayzZo1o1atWpQuXZp27dpxxRVX8Oqrr+Z5PSIiIiIikniVK1fO8h0+Uig/8nt9kyZNspQNpS1ZsgSA66+/nipVqtCuXTvq1avHoEGDeOuttzKNq7Bo0SIWL15M9erVs7zWrl3Lv//+m2kbDRo0iDpTx5lnnsmaNWt47733AD9g5VtvvUWfPn0oW7ZsxrYATjrppCzbevLJJ9m1axcrV65k+fLlbNq0Kdt9lMzUHUNyrXHjxuzYsYOff/45o2nR3LlzswxME42ZZXyANG/enPvuuw/nXMaHwrx587jkkkuKrvIiIiIiIpJvBx54IN9++y1btmyJ2SVj7ty5ALl6PojUpEkTFi5cyPvvv88HH3zA+++/z7PPPkvXrl15++23KVWqFLt27aJp06Y88sgjUdeRlpaW6e/k5OSo5U488USqVq3KpEmT6NGjB2+++SYbN26kX79+GWV27doFwNixY6lbt27U9VSvXp01a9bkeV9LOgUhJNcqVqzIKaecwi233MLTTz/NnDlzmDJlCp9//nmWslOmTKFDhw5UqVKFb775hocffpg77rgDgE6dOlG6dGkefvhhLrroIp566inA9+USEREREZHip0ePHnz++edMmjSJc889N0v+9u3bmThxIvvssw/t2rXLlPfTTz9lKR9Ka9CgQUZacnIyvXr1olevXjjnGDZsGHfddRezZs2iY8eONGrUiK+++opjjjmGUqXy36i/TJky9OnTh4kTJ7Jx40YmTZrEfvvtl6nLSKNGjQCoVq1aprEjIlWvXp0KFSpku4+SmbpjSJ48/vjjbN68mRo1atCvXz+eeOIJmjdvzqxZszJGkQU/aEyjRo2oVKkS55xzDtdddx0DBgwA/Mi5b7zxBs899xxVqlThmWee4Y033sho+iQiIiIiIsXLhRdeSK1atbjuuutYuHBhpjznHNdccw2//vorw4YNy9ICYd68eZlmo9i0aRNjxoyhdu3aGYNZrly5MtMyZpaRF2ptcMYZZ7BixQoefPDBLPXbuXNnlmk6s3PmmWeyadMmJkyYwHvvvcfpp5+eKbBxwgknUKVKFUaNGsXWrVuzLL98+XIASpcuzQknnMDUqVMzunCE8qNNQypgmrs0Ptq2betmz56d6GrkW/3r30no9tNHdyvQ8tOnT6dTp075Xr7l+JYF2n5BzR8wP6Hblz1bQa9/kT2Zrn8pyXT9x9ePP/7IgQceGDUv0d+lQwr6nfqrr76ia9eubN26lUGDBnHwwQezdu1aXn75Zb766isGDBjAs88+m2kcBjOjRYsW/PHHH1x66aVUq1aNCRMm8N133zFx4sSM2Shat25N9erVOeqoo6hduzZ//PEHjz32GElJSSxcuJDU1FScc5xyyim88cYb9OrVi44dO5KUlMSvv/7K5MmTue222xg4cCAA9erV44ADDuDDDz+Mui+7du2ibt26rFu3jvXr1/PVV19x2GGHZSrzyiuv0K9fPxo2bMhZZ51FrVq1WLp0acbsgKHAyvfff8/hhx9O5cqVufTSSylTpgxjxowhJSWFuXPnsmTJEurXr1+gY1/cZHe9A5jZt865ttHy1B1DRERERESkCBX04b+4OPzww/n+++8ZPXo0U6dO5amnnqJ8+fK0bt2al156idNOOy3mciNGjODWW2/l559/pl69eowfPz4jAAEwZMgQJk2axKOPPsratWvZd9996d69O7fcckvGzHpmxquvvsojjzzCuHHjeO+99yhbtiz16tXj9NNPz1P37lKlSnH66adz//3385///CdLAALg1FNPpXbt2txxxx089NBDbNq0iZo1a3LYYYcxaNCgjHItWrRg2rRpXH311YwcOZIaNWpw8cUXs++++2YqJ55aQsSJWkIUjFpCqCWE5J9+CZOSTNe/lGS6/uMrp1+GJb7Wr1+v2feKUEFaQmhMCBERERERERGJCwUhRERERERERCQuFIQQERERERERkbhQEEJERERERERE4kJBCBERERERERGJCwUhRERERERERCQuFIQQERERERERkbhQEEJERERERERE4kJBCBERERERERGJCwUhRERERERERCQuFIQQERERERERkbhQEEJERERERERkDzJu3DjMjPT09GK9zmgUhBAREREREZFshR5QQ6/SpUtTs2ZNTj/9dH766adEV0/2IEmJroCIiIiIiMhebXhqomvgDV9b4FXcfPPNNG7cmG3btjF37lzGjBnDxx9/zPfff8++++5bCJWUvZ2CECIiIiIiIpIrxx9/PO3bt8/4+8ADD2TIkCE899xz/Pe//01gzWRPoe4YIiIiIiIiki9HH300AL/88ktG2rJly7jwwgupVasWZcuWpVGjRtx5553s2rUr07LOOZ588knatGlDhQoVSEtLo3379kyZMiVTuWeeeYZWrVpRvnx5qlevTv/+/fnzzz8zlRk4cCBJSUn8888/nHrqqdSuXZsaNWpw880345xj2bJlnH766VSpUoW0tDSuvvrqTPVJT0/HzBg1ahTPPvssTZo0ITk5mXbt2jFv3jwAJkyYwIEHHkj58uVp3bo133zzTZbj8euvv3LmmWdSvXp1ypUrR4sWLXjqqacylZk+fTpmxoQJE7jvvvuoV68e5cuX54gjjuC7777Lss4vv/ySdu3aUb58eerWrcvo0aNxzkU9Hx999BHHHHMMlSpVomLFinTs2JFZs2YVaJ2FTS0hREREREREJF9CgxhWrVoVgBUrVnDEEUewZcsWBg8eTK1atfjss8+44YYb+O233/i///u/jGWHDBnCk08+SadOnRg5ciRlypThm2++4f3336dnz54AjB49mmHDhtG+fXvuvvtuli5dysMPP8zMmTP53//+l7Fd8EGNE088kdatWzNixAimTZvGqFGjqFy5MhMmTKBt27bceeedvPXWW9x///00adKEwYMHZ9qf1157jXXr1nHhhReyY8cORo8eTdeuXbntttu48847GTx4MDt37mT06NH07duXX3/9laQk/1i9aNEijjzySKpWrcpVV11FWloa7777LoMHD2blypVcf/31mbb10EMPsXXrVi6//HJ27NjBPffcQ+/evfnll18oU6YMAD/88ANdunShUqVK3HTTTZQtW5YxY8aQkpKS5Vy8/PLL9OvXj44dOzJy5Eicc4wbN45jjz2WDz/8kA4dOuR5nUVBQQgRERERERHJlbVr17JixYqMMSGuvPJKSpUqRd++fQG48cYbWb9+PfPnz2e//fYD4MILL6ROnTqMHj2aoUOH0rhxY2bOnMmTTz7JwIEDeeaZZzCzjG2EfpFfsWIFw4cP5+ijj+bjjz/OeNjv0KED3bt3Z/To0dx9990Zy+3atYvu3bszatQo1q9fz2WXXUb9+vW57rrruOmmm7jtttsAuOCCC6hfvz7PPPNMliDE4sWL+eWXX6hWrRoAVapU4eKLL+baa69l0aJF7LPPPpnSP/zwQ0488UQALrvsMqpVq8Z3331HxYoVAR9oOfPMMxk5ciRDhgwhNXX3+CCrVq1iwYIFJCcnA9CkSRN69+7NBx98QLdu3QA/BsfWrVv57rvvaNy4MQDnnnsuBxxwQKZ6b9y4kSFDhnDGGWcwceLEjPSLLrqIli1bMmzYMD777LM8rbOoqDuGiIiIiIiI5Er37t2pXr06tWvX5qSTTmLjxo288MILtGnTBuccr7zyCieddBJlypRhxYoVGa8TTjgB5xyffPIJAK+88goAt99+e6YABJDx94cffsjWrVu58sorMwIQAN26daNZs2a8/fbbWep34YUXZvw7KSmJtm3b4pzjggsuyJK+ePHiLMv36dMnIwABcOSRRwLQq1evjABEeHpoHatXr2batGmceuqpbN68OdO+d+3alU2bNvHll19m2tbAgQMzAhAAHTt2zLTOnTt38t5773HSSSdlBAsAqlevzllnnZVpXdOmTWPVqlWcffbZmba9ceNGunTpwpdffsmmTZvytM6iopYQIiIiIiIikisPPPAALVq0YP369bz88su88cYbGV0Hli9fzurVq5kwYQITJkyIuvy///4L+DEkqlatSq1atWJuK9TVo2nTplnyogUhSpUqRZ06dTKlValSJWb66tWrs6y3bt26Wcpllx5ax88//4xzjttvv53bb7896v6E9j2kXr16mf5OS0sDfAsJ8Mdz06ZNNGnSJMu6ItMWLVoEwEknnRR12wArV66kTJkyuV5nUVEQQkRERERERHKlbdu2GbNj9O7dm549ezJw4EAOP/xwSpcuDcDpp5/O+eefH3X5hg0bFlndzCxLq4rs0qMNxBjah9ymh9YRGuTy8ssv5+STT45atnnz5nlaZ16Etj927NgsAZOQ6tWrs2bNmjyvu7ApCCEiIiIiIiL5cvfdd9OsWTNGjhzJY489RuXKldm2bRtdunTJdrlGjRrx3nvv8ddff8VsDVG/fn0AFi5cSLNmzTLl/fjjjzRo0KBQ9qEw/Oc//wF8YCGnfc+t6tWrU6FCBX766acseZFpjRo1AqBatWrZbj8v6ywqGhNCRERERERE8iU0mOKzzz6bMT3mm2++GXX6yvXr17N161YATj31VMAPZBn5y3/o7+OOO45y5crx0EMPsWPHjoz8d999lwULFsRscZAI1atX59hjj2Xs2LH89ttvWfKXL1+e53WWLl2aE044galTp2Z0twitK3zwSYATTjiBKlWqMGrUqIxjHG37eVlnUVFLCBEREREREcm3a6+9lsmTJ3Pvvfdy5513Mn36dI4++mgGDRrEQQcdxIYNG1iwYAGvvvoq8+fPp379+nTo0IHzzz+fp59+mvT0dLp37065cuX49ttvqVChAo899hj77LMPw4cPZ9iwYRx77LH07ds3Y4rOunXrct111yV61zN5/PHHOeqoo2jVqhXnn38+jRs3ZtWqVcyZM4c33niDLVu25Hmdt912G++//z4dO3bk0ksvpUyZMowZM4b69eszd+7cjHKVKlVizJgx9OvXj5YtW3LWWWdRq1Ytli5dyowZMwAyBgXN7TqLioIQIiIiIiIikm+HHXYYnTp1YsyYMdx444189dVXjBo1iilTpvD0009TpUoVDjjgAG655RZq1qyZsdyYMWM4+OCDM5arUKECzZs359prr80oc/3111O9enUeeughrrnmGipVqsQpp5zC6NGjqVq1aiJ2N6bGjRvz7bffctttt/Hiiy/y77//Uq1aNQ488EDuu+++fK2zRYsWTJs2jauvvpqRI0dSo0YNLr74Yvbdd18GDRqUqeypp55K7dq1ueOOO3jooYfYtGkTNWvW5LDDDstUNi/rLAqWn0EvJO/atm3rZs+enehq5Fv9699J6PbTR3cr0PLTp0+nU6dO+V6+5fiWBdp+Qc0fMD+h25c9W0Gvf5E9ma5/Kcl0/cfXjz/+yIEHHpjoakhg/fr1VKpUKdHV2GvldL2b2bfOubbR8krMmBBmVtbMRprZ72a2xczmmVm/fKwnzcyWm5kzs7OLoq4iIiIiIiIie6OS1B1jLHAm8DgwDzgFeMHMSjnn8jICxx1AchHUT0RERERERGSvViJaQphZG+BsYKRz7jLn3FPAScCnwL1mViYP67kAH4gQERERERERkTwoEUEI4DTAAY+FEpwfDONxoCbQIacVmJkFy78IfF401RQRERERERHZe5WUIERrIN05Fzk569dh+Tk5H2gBFK95YERERERERET2ECVidgwz+x5Y65w7KiK9ArAReNA5d1U2y1cFFgH3OefuNLNOwCdAf+fc89ksNxgYDLDvvvu2efHFFwu6Kwkzf+nahG6/Ze3UAi2/YcMGUlJS8r38Dyt/KND2C6rZPs0Sun3ZsxX0+hfZk+n6l5JM1398paam0qhRo0RXQwI7d+6kdOnSia7GXuuXX35h7drYz4idO3eOOTtGSRmYMhn4N0r6lrD87NwJrAHuz8tGnXNjgDHgp+jck6dIGpjoKTrP6lSg5Qs6RdVl4y8r0PYLan4fTdEp+acp2qQk0/UvJZmu//j68ccfNSVkMaIpOotW+fLlOeSQQ/K1bEkJQmwGykVJLx+WH5WZHYrvitHLObe1COomIiIiIiIiUiKUlDEh/gZqRUnfL3j/K5tl7wNmA/PNrL6Z1ccPZglQLUgrKcEcERERERERkXwrKQ/P3wHHmln1iMEpDw/Lj6UuUA9YEiXvgeDVAEgvhHqKiIiIiIiI7LVKShDiVeBa4BJgOGRMuXkRsAyYGaSl4ltH/O2cC42yMRioELG+FsBI4EFgBtHHmxARERERERGRMCUiCOGc+8bMXgBuDma6mAecAhwNDHDObQ+K9gaeBc4FxgXLfhC5PjNbE/zzW+fcG0VaeREREREREZG9REkZEwJgEDAaH2h4DNgfONs591xCayUiIiIiIiJ7heHDh+Mb3UssJaIlBEAws8WNwStWmXEELSByWNd0QFeWiIiIiIjkqOX4lomuAgDzB+R/2vdx48Zx7rnnMmvWLNq3b5/nZdetW8fll1+e7+0XJ2vWrOHBBx/kmGOOoUOHDomuzh6nJLWEEBERERERkTgbN24cDz/8cKKrUWjWrFnDiBEjmDlzZpa8m266ic2bNyegVnsOBSFERERERERkj7Np06ZEVyGLpKQkypcvn+hqFGsKQoiIiIiIiEieDBw4kKSkJJYtW8Zpp51G5cqVSUtL4/zzz8/UEqB+/frMmDGDX3/9FTPDzKhfv35G/vbt27n99ttp2rQp5cqVo2bNmgwePJhVq1Zl2l79+vXp0qULM2fOpF27diQnJ3PDDTcAMGfOHLp3786+++5L+fLlqV27NmeffTZ//vlnpnV89NFHHHPMMVSqVImKFSvSsWNHZs2alWXfli1bxiWXXELdunUpV64cderU4cwzz2Tp0qVMnz6dBg0aAHDzzTdn7NPw4cOB2GNCPPPMM7Rq1Yry5ctTvXp1+vfvn6V+uT2me7oSMyaEiIiIiIiIFB7nHCeeeCLNmjXjrrvu4ptvvmHs2LFUr16dO++8E4AHH3yQYcOGsXr1au69914AUlJSMpbv06cP06ZN47zzzuOggw5i8eLFPPLII3z99dd8+eWXmVoVLFmyhJ49ezJo0CDOPfdcatSowfLly+nSpQtpaWkMHTqUatWq8ddffzF16lSWLl1KnTp1AHj55Zfp168fHTt2ZOTIkTjnGDduHMceeywffvhhxtgOy5Yt4/DDD+evv/7i/PPPp1WrVixfvpx33nmHX375hQMPPJAHHniAq666ir59+9KzZ08ADjrooJjHafTo0QwbNoz27dtz9913s3TpUh5++GFmzpzJ//73P6pWrZqnY7qnUxBCRERERERE8mzXrl2ccMIJjB49GoAhQ4awatUqnn766YwH5l69evHggw+yfft2zj777EzLv/jii7z11lt88MEHHHfccRnpxxxzDCeccAITJkzgggsuyEhfvHgxkydP5pRTTslImzJlCitXruTdd9/l0EMPzUi/8sorqVSpEgAbN25kyJAhnHHGGUycODGjzEUXXUTLli0ZNmwYn332GQDDhg3jt99+4+OPP6Zz584ZZW+66Sacc5gZvXr14qqrrqJVq1ZZ9inSihUrGD58OEcffTQff/wxSUn+EbxDhw50796d0aNHc/fdd+fpmO7p1B1DRERERERE8uXiiy/O9HfHjh1ZsWIF69evz3HZl156iYYNG3LIIYewYsWKjFfr1q1JTU3l448/zlR+v/32o3fv3pnSqlSpAsCbb77J1q1bo25n2rRprFq1irPPPjvTdjZu3EiXLl348ssv2bRpE7t27eK1117juOOOyxSACMnP1JsffvghW7du5corr8wIQAB069aNZs2a8fbbb2dZpiDHdE+glhAiIiIiIiKSZ6VKlcro7hCSlpYGwKpVqzJaIsSyaNEiFi9eTPXq1aPm//vvv5n+btCgQZZAQIcOHTjjjDMYNWoUDzzwAO3bt6dbt26cfPLJGdtftGgRACeddFLMuqxcuZKyZcuydu1aWrYsvClV09PTAWjatGmWvGhBiIIe0z2BghAiIiIiIiKSZ2ZGqVLRG9c753JcfteuXTRt2pRHHnkkan7o4TskOTk5ah0mTZrEf//7X9555x0+/PBDrrrqKkaMGMH06dNp0aIFu3btAmDs2LHUrVs36raqV6/O2rVrc6xzUSvoMd0TKAghIiIiIiIiRSZWN4ZGjRrx1Vdfccwxx8R88M6t1q1b07p1a26++WbmzZtHmzZtuO+++3j22Wdp1KgRANWqVaNLly4x11G2bFkqV67M/Pnzs91WXrplhGYCWbhwIc2aNcuU9+OPP2bMtFGSaEwIERERERERKTIVK1ZkzZo1WdLPOOMMVqxYwYMPPpglb+fOnVmm6Yxm9erVWVoIHHjggSQnJ2ds84QTTqBKlSqMGjUq6rgRy5cvB3xXiNBsHZ988kmWcqHtVKxYESDqPkU67rjjKFeuHA899BA7duzISH/33XdZsGABJ598co7r2NuoJYSIiIiIiIgUmTZt2vDOO+9wzTXX0KZNG1JSUjj55JM566yzmDx5MldffTWzZs2iY8eOJCUl8euvvzJ58mRuu+02Bg4cmO26x48fzyOPPELv3r1p1KgRO3bs4MUXX2T9+vX069cPgEqVKjFmzBj69etHy5YtOeuss6hVqxZLly5lxowZABlBhzvuuINp06ZxwgknZEzRuWrVKqZOncqoUaPo2LEj1apVo27durzwwgv85z//IS0tjRYtWtCiRYss9dtnn30YPnw4w4YN49hjj6Vv374ZU3TWrVuX6667rnAP9h5AQQgREREREZEiNH9A9s3793ZDhw5l4cKFjB07lvvuu4969epx8sknY2a8+uqrPPLII4wbN4733nuPsmXLUq9ePU4//XSOOeaYHNfdsWNHZs+ezeTJk/nnn3+oUKECzZs3Z9KkSZx22mkZ5U499VRq167NHXfcwUMPPcSmTZuoWbMmhx12GIMGDcooV7NmTb7++mtuvfVW3njjDZ5++mn23XdfOnbsyAEHHJBRbvz48QwdOpQrr7ySbdu2ceutt0YNQgBcf/31VK9enYceeohrrrmGSpUqccoppzB69GiqVq1agCO7Z7K9ZXCL4q5t27Zu9uzZia5GvtW//p2Ebj99dLcCLT99+nQ6deqU7+Vbji+8EXLzo6T/xyUFU9DrX2RPputfSjJd//H1448/cuCBBya6GhJYv379XjGTRHGV0/VuZt8659pGy9OYECIiIiIiIiISF8U+CGFmVc1spJl9ZmY/m9mRQfo+ZnaLmWWdcFVEREREREREip1iPSaEmdUFPgX2BX4CGgLJAM65lWbWD6gGXJ6wSoqIiIiIiIhIrhTrIARwF1AeOBhYDvwbkT8FKHlzmoiIiIiIiIjsgYp7d4zjgIedcz8C0UbQXALsH98qiYiIiIiIiEh+FPcgREWytn4Ip+FORURERERERPYQxT0I8RNwRDb5XYHv41QXERERERGRmJyL1nhbZO9S0Ou8uAchngTONrNBQOkgzZlZJTN7AOgEPJ6oyomIiIiIiACULVuWzZs3J7oaIkVu8+bNlClTJt/LF+uBKZ1zT5hZc+BpYFOQ/CqQig+gPOycez5R9RMREREREQGoVq0af/75J9WqVaNSpUokJSVhZomulkihcc6xefNmli5dyr777pvv9RTrIASAc+5SM5sInA4cgA8+/AK86Jz7LKGVExERERERAVJTUylXrhzLly9n5cqV7NixI9FVKtG2bNlC+fLlE12NvU6ZMmXYd999qVy5cr7XUeyDEADOuS+ALxJdDxERERERkVjKly/P/vtr8r7iYPr06RxyyCGJroZEUazHhDCznWZ2Zjb5p5vZznjWSURERERERETyp1gHIYCcOlGVBjQErYiIiIiIiMgeoLgHISBGkMHMKgBdgJXxrY6IiIiIiIiI5EexC0KY2c1mts3MtuEDEM+F/g5/AeuBAcBrCa2wiIiIiIiIiORKcRyYch4wEd8V4xzgc2BxRBkHbAS+BTRFp4iIiIiIiMgeoNgFIZxzU4ApAGZWDxjlnPsosbUSERERERERkYIqdkGIcM65zomug4iIiIiIiIgUjmIdhAgxszJAE6AKUcaxcM7NjHedRERERERERCRvin0QwsxGAlcAFbMpVjpO1RERERERERGRfCp2s2OEM7OrgRuBl/AzYRhwPTAE+AH4H3B8wiooIiIiIiIiIrlWrIMQwPnAG865C4B3g7RvnXNjgEOBZKB9oionIiIiIiIiIrlX3IMQDYBpwb93Bu9lAZxzW4DngHMTUC8RERERERERyaPiHoRYx+5xK9YDO4DaEfk14l0pEREREREREcm74h6EWAg0B3DO7QS+Bc4xszJmlgz0B35NYP1EREREREREJJeKexBiCtDdzMoHf48EjgLWAMuBw4E7ElM1SYRVq1bRu3dvKlasSL169XjhhReilrvnnnto0aIFlSpVokGDBrz44otRy82YMQMz46abbirKaouIiIiIiAjFfIpO59x9wH1hf081sw7AqfgxIt4Evk9Q9SQBLrnkEsqWLcuyZcuYM2cO3bp1o1WrVjRv3jxTOecczz33HAcddBC//vorHTt2pFOnTpxxxhkZZbZv384VV1zB4YcfHu/dEBERERERKZGKe0uILJxznzvnrsIHJ3oCvyW4ShInGzduZPLkyYwcOZKUlBTat29Pjx49mDBhQpay1157La1btyYpKYkmTZrQrl07Pvvss0xl7rvvPo4//niaNm0ar10QEREREREp0YplEMLMqpvZ1Wb2hJndbmaHhOXtZ2aPA4uBq4BvElZRiatFixaRlJRE48aNM9JatWrFggULsl3OOcf8+fMztZb47bffeOaZZ7jllluKrL4iIiIiIiKSWbHrjmFmjYFZQDXAguRrzawffnaM8UBF4HXgbuecghAlxIYNG6hcuXKmtNTUVNavX5/tcsOHD2fXrl2ce+7u2Vwvv/zyjBYVIiIiIiIiEh/FLggB3AZUAi7GByMaAA8ADwJpwDTgWufcokRVUBIjJSWFdevWZUpbt24dlSpVirnMo48+ynPPPcfdd99NuXLlAHjrrbdYv349p59+epHWV0RERERERDIrjkGIjsCTzrkng79/MLNdwDvAJOfcWYmrmiRS48aN2bFjBz///DMHHHAAAHPnzs0yKGXIM888w+jRo5k5cya///57RvpHH33E7NmzqVmzJgBr166ldOnSzJ8/nylTphT9joiIiIiIiJRQxXFMiOrA3Ii0OcH7y/GtihQnFStW5JRTTuGWW25h48aNfPbZZ0yZMoX+/ftnKTtx4kRuuOEGpk2bRsOGDTPljRw5kkWLFjFnzhzmzJlDjx49uOCCC3j22WfjtSsiIiIi+ZKX6crPPffcjOnK77nnnoy8f//9l379+lGrVi1SU1M56qij+Oqrr+K1CyJSwhXHIEQpYFtEWujv7Dv/y17v8ccfZ/PmzdSoUYN+/frxxBNP0Lx5c2bNmpVpfIebbrqJlStXcuihh5KSkkLXrl256KKLAKhUqRI1a9bMeCUnJ1OxYkWqVq2aqN0SERERyZXw6conTpzIkCFDog7S7Zxj2LBhrF69mvfee49HH32UF198EfDjbB166KF8++23rFq1igEDBtCtWzc2bNgQ790RkRLInHOJrkMmQdeLEfixH0JS8d0xrgC+jVzGOfd5fGqXf23btnWzZ89OdDXyrf717yR0++nlzyzQ8tObjKDTT7fme/mWDeoWaPsFNX/A/IRuX/Zs06dPp1OnTomuhkhC6PqXvcnGjRtJS0vj+++/z5gtrH///tSuXZvRo0dnKR9+/V9++eU453jkkUeirrty5cp88skntGnTpsjqLxJP+vxPLDP71jnXNlpecRwTAuCW4BXpISA8amLB36XjUSkRERERkUSJNV35jBkzsl3OOcesWbO48MILo+bPmTOHbdu20ahRo0Ktr4hINMUxCHFuzkVEREREREqWwpyuPGTdunX079+fW2+9ldTU1EKtr4hINMUuCOGcG5/oOoiIiIiIFDcFma581qxZGdOVh2zevJmTTz6ZI444gmHDhhVJnUVEIhXHgSlFRERERCRC+HTlIdlNVz516lRGjx7NRx99RJ06dTLlbd26lV69elGnTh2efPLJIq23SGHK7QwxL774Ii1atIg6QwxAeno6nTt3pkKFCjRt2pQPP/wwHtUXFIQQEREREdkj5HW68qeffjrqdOXbt2+nb9++JCcnM378eEqV0iOB7DnyMkPMc889F3WGGIB+/fpxyCGHsHLlSm6//Xb69u3L8uXL47krJZY+cURERERE9hB5ma583bp1GdOVp6SkZExX/vnnn/P222/zwQcfUKVKlYz8WbNmJWq3RHJl48aNTJ48mZEjR5KSkkL79u3p0aMHEyZMyFK2X79+tG7dmqSkJJo0aULPnj357LPPAD/I63fffceIESNITk6mT58+tGzZksmTJ8d7l0qkYjcmRFExs7LAzcAAoAawCLjTOTcph+Xq4AfLPAlojA/cLAQedM69VKSVFhEREZGSa3jWgSKrAm8cDBycBKyFRUNg+BCOBjZcUzpjmSUDYHqTeyOmKJ8EwyfREXC3Vo5cNXzUHT4K3/7awtoTkUJRWDPELFiwgIYNG2YaT6VVq1ZRW1RI4StJLSHGAjcAU4DLgKXAC2Z2Vg7L9QqW+w24FR/I2AK8aGZ3FlltRUREREREJENhzRCzYcOGLLPB5GY9UjhKREsIM2sDnA2McM4ND9KeBmYC95rZy8657TEW/wSo65zL6CBkZo8BHwDXmNk9zrlVRboDIiIiIiIiJVxhzRCTn/VI4SkpLSFOAxzwWCjBOeeAx4GaQIdYCzrnFoQHIMKWfQ0fxGkcdUEREREREREpNHmdIeaZZ56JOkNM8+bNWbx4caaWD9mtRwpXSQlCtAbSI4MJwNdh+XlVK3hfme9aiYiISJ7kdmq2Tz75hM6dO9O9e3fq16+fJX/OnDkcffTRpKamUqdOHUaOHFnENRcRkYLKywwx06ZN44Ybbog6Q0zjxo05+OCDGTFiBFu2bOH1119n3rx59OnTJ167UqKZ/1F/72Zm3wNrnXNHRaRXADbiB5m8Kg/rqwr8CPzpnGuTTbnBwGCAfffdt034lDB7mvlLEzswUctSSwq0/IZytUjZ+le+l/+hbNkCbb+gmu3TLKHblz3bhg0bMo2YLrInGzlyJLt27eLaa6/ll19+YdiwYTzyyCM0aNAgU7kff/yRP/74g3Xr1vHqq68S+X/wwIEDad++Peeeey7//PMPl19+OUOHDuWoozJ9VRBJrL/nFGjxgn7/Yb+DC7R9kQKJcf2v27CRu598kW+/X0TllApccEZ3uhzVhnkLf+W6u8bw7rN3AXD6lXewcuVKyiTtHoHguPZtGHreaQD8s3wVo//vBX785Xf2rVaFKwb2oU3LJrs3pOu/QDp37vytc65ttLySEoT4FfjNOXdMRHopYCfwpHPuolyuqzTwLtAJOMo5901ulmvbtq2bPXt2nupdnNS//p2Ebj+9/JkFWn56kxERo0PnTcsGdQu0/YKaP2B+Qrcve7bp06fTqVOnRFdDpMA2btxIWloa33//fcbI6P3796d27dqMHj066jL33XcfjzzyCOnp6ZnSK1SowOzZs2nWzAd5Tz31VFq3bs2wYcOKdB9E8iTK7Bh5UdDvP5odQxJK1/8ezcxiBiFKSneMzUC5KOnlw/Jz6ymgC3B+bgMQIiIiUnCxpmbLz5RqV155Jc899xzbt2/np59+4osvvqBLly6FWV0RERGJoqQEIf5m9xgO4fYL3nPVTs3M7gPOBf7rnHuukOomIpJree0Pn5qayhlnnJEp7/fffyclJSXTy8y477774rELIvmW36nZounevTuvvvoqycnJNG3alPPOO49DDz20sKoqIiIiMZSUIMR3QD0zqx6RfnhYfrbM7FZgKHCnc07f1EUkIS655BLKli3LsmXLmDhxIkOGDIn6K3DFihUZNGgQ99xzT5a8unXrsmHDhozX/PnzKVWqlAZjkmKvsKZUW7VqFSeeeCK33HILW7Zs4Y8//uD999/n8ccfL8zqioiISBQlJQjxKmDAJaEEMzPgImAZMDNISzWzpmaWqQOSmV0BDAf+zzl3Q7wqLSISbuPGjUyePJmRI0eSkpJC+/bt6dGjBxMmTMhS9rDDDqN///5ZRoOO5rnnnqNDhw5RZxAQKU7yOjVbLIsXL6Z06dKcc845JCUlUadOHc444wymTp1a2FUWERGRCCUiCBGM3fACcLOZPWxm5wPvAEcD1zrntgdFe+NnvegdWtbMegEPAL8DX5jZ2RGvnL/hi4gUgsLsDx/inOO5555jwIABhVFFkSKVl6nZdu3axZYtW9ixYwfOObZs2cK2bdsAH8xwzvHCCy+wa9cu/vnnH1566SUOOuigeO+SiIhIiVMighCBQcBofIDhMWB/4OxcjO1wML4VRV1gPDAh4tWhiOorIpJJYfaHD/n0009ZtmwZffv2LWj1ROLi8ccfZ/PmzdSoUYN+/frxxBNP0Lx5c2bNmpVpKtqZM2eSnJzM9ddfz++//05ycjLHH388AJUrV+a1117jgQceIC0tjYMPPpgWLVpw0003JWq3RERESoyknIvsHZxzW4Ebg1esMuOAcRFpw/FdMUREEqqw+sOHGz9+PH369Mn08CZSrERM0VYVeONg4OAkYC0sGgLDh3A0sOGa0hnlOwHu1soRU7T9LyP/GOCbbkA38JNkvQx3vxxl+5qiTUREpDCVpJYQIiJ7tMLqDx+yefNmXnnlFXXFEBEREZG4URBCRGQPkZ/+8Nu3+yFvwvvDh7z++uukpaXRuXPnuNRfRERERKTEdMcQEdljhTVHf7yeY9CUzdRIe5F9ko0nupSn+SvtmHXvDrpO3MSGG/yYETPTd9B5/KaM5ZKTk+lYrzTTB1bMSBv//Eb61y2NjaiSw/bVHF1ERERECoeCECIie5CqycYbZ1TIkn50vaSMAARAp/pJuFv935n7xO/2/tkVs6SJiIiIiBQldccQERERERERkbhQEEJERERERERE4kJBCBERERERERGJCwUhRERERERERCQuFIQQEcmDVatW0bt3bypWrEi9evV44YUXopb75JNP6Ny5M6mpqdSvXz9LfufOnalevTqVK1emVatWTJkypYhrLlI4dA+IiIhIQSgIISKSB5dccglly5Zl2bJlTJw4kSFDhrBgwYIs5SpWrMigQYO45557oq7noYce4u+//2bdunWMGTOGs88+m7///ruoqy9SYLoHpKQrjEDcv//+S79+/ahVqxapqakcddRRfPXVV3GofcGV9P0XBaOl4BSEEBHJpY0bNzJ58mRGjhxJSkoK7du3p0ePHkyYMCFL2cMOO4z+/fvTsGHDqOs66KCDSErysySbGdu3b+ePP/4o0vqLFJTuAZHCCcRt2LCBQw89lG+//ZZVq1YxYMAAunXrxoYNG+KxCwVS0vdfFIyWglMQQkQklxYtWkRSUhKNGzfOSGvVqlXU/3hzo3v37pQvX57DDz+cTp060bZt28KqqkiR0D0gJV1hBeIaNmzI0KFD2W+//ShdujSDBw9m27Zt/PTTT/HYjXwr6fsvCkaDWgMVBgUhRERyacOGDVSuXDlTWmpqKuvXr8/X+t5++23Wr1/P1KlTOf744ylVSh/JUrzpHpCSrrADcSFz5sxh27ZtNGrUqKBVLFIlff9FwWhQa6DCoP/tRURyKSUlhXXr1mVKW7duHZUqVcr3OsuUKUPXrl354IMPePPNNwtaRZEipXtASrrCDsSBv4f69+/PrbfeSmpqakGrWKRK+v6LgtFqDVQ4ivdZFhEpRho3bsyOHTv4+eefM9Lmzp1L8+bNC7zuHTt28OuvvxZ4PSJFSfeAlHSFHYjbvHkzJ598MkcccQTDhg0rjCoWqZK+/6JgtFoDFQ4FIUREcqlixYqccsop3HLLLWzcuJHPPvuMKVOm0L9//yxld+3axZYtW9i+fTvOObZs2cK2bdsAWLhwIe+++y6bN29m+/btPP/888ycOZOOHTvGe5dE8kT3QOGNCn/zzTfTsmVLkpKSGD58eNFWWgpNYQbitm7dSq9evahTpw5PPvlkYVazyJT0/RcFo9UaqHAkJboCIiJ7kscff5xBgwZRo0YN9tlnH5544gmaN2/OrFmz6Nq1a0ZfvpkzZ9K5c+eM5ZKTk+nYsSPTp0/HOcfw4cP54YcfKF26NAcccAAvvfQSrVu3TtRuicRU//p3Mv29c99erHz3IV5K24dS5SuT1mkw3Saks+WPt/n3leHUHfoqAFt+n8eySTdkLJecnEy5/VtQ88zRbF/xByumPsD2lX+AlaJMWi2qdP8vp7z8N7yceXvp5Yt+H/MivC/wnDlz6NatG61atcryBTzUF7hfv37ccccdWdbTqFEj7r77bv7v//4vXlWXQhAeiHv66aeZM2cOU6ZM4fPPP89SdteuXWzbti1TIK5UqVKULVuW7du307dvX5KTkxk/fnyxb4IeUtL3XwrvGli4cCFLliyhU6dOJCUl8dJLLzFz5kzuvvvuBOxV7qk1UOFQEEJEJAeRD2E0vYDqTS8A4IZ5cMM8n1/t0pcyla133duZFksPX1fnW9gniFEsB676Cq76KmI7oeWK2UOYlGylkytR45SbsqSX379FRgACoHzdg7LcAyFlqu3PfufcX2R1LCqhvsDff/99lr7Ao0ePzlT2sMMO47DDDuPDDz+Muq4BAwYAMHHixCKvt+Rfls9/CicQt+X3+Sx7+20sqRxlK+x+eKlx6nDK798i4+/i+PlfGMH4zz//nLfffpvk5GSqVKmSUebdd9/l6KOPjvcuSQzRrn+IXzC6OF7/4S1BDjjgAECtgfJDQQgREcm1VatWcd555/HBBx9QrVo17rzzTs4888ws5T755BNuu+02vvvuO9LS0khPT8+Un56ezrnnnstXX31F3bp1efTRR+nSpUuc9kIkf2L1BZ4xY0YCayXxVhiBuPJ1W8bMK05ajm8ZPaM3NOztB9u7c/ud3Dn+TgAaPNYg0zItxrXItNhKVmbkR+YBXLz4Yli8++/5A+YXpPpSREpyMFqtgQqHghAiIpJrhdUUvV+/fhx55JFMnTqVqVOn0rdvX37++WeqV68er10RybOi6AssIiLFU6wg3I6jd7B07FIqVa1EUkoS+/bblzNmn8HGiRv57f7faPZkMwA2/LiB9LvSM5ZLTk6mQpMKNBzWkI0LN7Lk7SVYWaNcSrmMMvWG1qNik4rA3h2EUxBCRERypbCaoi9atIjvvvuODz74gOTkZPr06cODDz7I5MmTueiii+K1OyJ5VhSjwouIyJ4lKSWJelfUy5JesUnFjAAEQMqBKVFb/ABUbFoxZl5JULLafYiISL4V1rRUCxYsoGHDhpke3ApjeiuRolaUo8KLiIiUFApCiIhIrhRWU/QNGzZkmYJKTdplT1BYU5QCbN++nS1btrBr1y527NjBli1b2LlzZzx3R0REJCHUHUNERHKlsJqiq0m77Eki+wQXRl9ggD+f+pM1n63JyL/99tupfV5t0o5Oy7S9vblPsIiIlEwKQoiISK4U1rRUzZs3Z/Hixaxfvz4j8DB37tyos2yIFDeF0RcYoM4FdahzQZ0iqaOIiEhxpu4YIiKSK4XVFL1x48YcfPDBjBgxgi1btvD6668zb948+vTpE+9dEhEREZE4U0sIERHJVnhz9MJqir6t7zaeePoJ7n/4fsrsU4Zag2txzNRjom5fzdFFRERE9h4KQoiISK4VVlP0stXLZgQkRERERKTkUHcMEREREREREYkLBSFEREREREREJC4UhBARERERERGRuFAQQkRERERERETiQkEIEREREREREYkLBSFEREREREREJC4UhBARERERERGRuFAQQkRERERERETiQkEIEREREREREYkLBSFEREREREREJC4UhBARERERERGRuFAQQkRERERERETiQkEIEREREREREYkLBSFEREREREREJC4UhBARERERERGRuFAQQkRERERERETiQkEIEREREREREYkLBSFEREREREREJC4UhBARERERERGRuFAQQkRERERERETiQkEIEREREREREYkLBSFEREREREREJC4UhBARERERERGRuFAQQkRERERERETiQkEIEREREREREYkLBSFEREREREREJC4UhBARERERERGRuCgxQQgzK2tmI83sdzPbYmbzzKxfHpbvHyyzxcx+M7MRZlamKOssIiIiIiIisjcpMUEIYCxwAzAFuAxYCrxgZmfltKCZnQc8B/wRLPsWcDPweJHVVkRERERERGQvk5ToCsSDmbUBzgZGOOeGB2lPAzOBe83sZefc9hjLlgdGA9OB7s45F6SvAW4ws4edc/OLfCdERERERERE9nAlpSXEaYADHgslBMGEx4GaQIdslu0MVAMeCwUgAo8DFqxbRERERERERHJQUoIQrYF059zyiPSvw/KzWza8LADOub+AP3NYVkREREREREQClvnH/b2TmX0PrHXOHRWRXgHYCDzonLsqxrKPApcAZSO7bJjZ10AZ59whMZYdDAwO/mwC/FSgHZGCqAasSHQlRBJE17+UZLr+pSTT9S8lma7/xKrnnKseLaNEjAkBJAP/RknfEpaf3bIuxpgRW4DKsRZ0zo0BxuS2klJ0zGy2c65toushkgi6/qUk0/UvJZmufynJdP0XXyWlO8ZmoFyU9PJh+dktazGm4yyfw7IiIiIiIiIiEigpQYi/gVpR0vcL3v/KYVmyWT67ZUVEREREREQkUFKCEN8B9cwssk/K4WH52S0LcGh4opnVAurksKwUH+oWIyWZrn8pyXT9S0mm619KMl3/xVRJGZjyUPzsFiOcc8ODNANmAI2B/Z1z280sFd+64W/n3NqgXHn8LBjzgWNC03Sa2SjgRqCVc25enHdJREREREREZI9TIgamdM59Y2YvADebWVVgHnAKcDQwIGzQyd7As8C5wLhg2S1mNgwfSXvLzN4ADgYuBp5RAEJEREREREQkd0pEECIwCEgHzgEuBBYBZzvnJua0oHPuKTPbBvwXeAw/08YoYGSR1VZERERERERkL1MiumOIiIiIiIiISOKVlIEpRUREREREpIQws9pmttjMuiS6LpJZSeqOISWAmZUGOgCt8dOqJgOb8VOpfgfMdM7tTFwNRRLPzPYHGjjnZia6LiLxZmbJQHXn3O+JrotIYTKzMkB559z6sLSq+DHP0oBvnHMzElU/kcIWzFaYnTpAfaBOqKxz7q+irpfkTN0xZK9hZv2Ae4GagEUp4oBlwH9zMxaIyN7KzG4EbnPOlU50XUQKi5mdiB+vqRmwEpgEjAx/IAvKnQU8p+tf9iZmNhq4DCiPnxHuNKASMBOoGhRzwKvAGU4PALIXMLM8/7Coz/7iQS0hZK9gZmcAE4FPgavx/wH/DWzB/4e8H3AEcBHwnJntdM69mKDqiohIITKzNsDbwArgTXxLuKuBPmZ2snPuh0TWT6QomVl/4Fr8PfA7MBAYG2Q/CbyIbxk6BD9A++AgXWRPZ8AG4ClgXZT8NOBy4CVgYRzrJTlQSwjZK5jZXOBP51y3XJSdCtR2zrUq+pqJxIeZ3ZKH4h2BTvo1QPYWZvYW0BQ43Dm3Kkg7Gt8aogLQzTn3RZCulhCyVzGzL4F/nHO9gr8HAU8D45xzgyLKfor//n9U3CsqUsiCz/nHgBrAMOfcsxH59YAlQC/n3JsJqKLEoJYQsrdoDDycy7KTgUeLsC4iiTAc39Q2WlekaBSBlr1Ja+CBUAACwDk3y8wOBaYC08ysr3PuvYTVUKToNAaeC/v74+D9/Shl3wRuKPIaicRB8Dl/CL61wwNmdhFwuXPuqwRXTXKg2TFkb/Ev0DKXZQ8KyovsTVYAHwD75+J1b4LqKFJUKgOrIxOdc3/jW/78D5hiZqfFu2IicVAW2Br2d2gclOVRyq7Ed1MV2Ss453Y65x4ADgR+AT4zs3Fmtm+CqybZUEsI2Vs8B1xvZiuBx51zKyMLmNk+wCXAxcDoONdPpKh9A7R0zi3NqaCZrY1DfUTiaQlwcLQM59w6MzseeB0/dtBHcayXSDz8g58FIGQTcB/wW5SydfFBa5G9ShB0PsvMxuBbPC8CnkEtP4slBSFkb3EbfgqeEcCtZpaOH5hyK1AOP0hZPXzrnxeC8iJ7k9lAVzOr6Zz7J4eya/CDl4nsLaYDp5rZVc65HZGZzrnNZnYyfoyIU9CXUtm7zMYPvg346x34b4yyHYF58aiUSCI452aY2cHAlcAt5L6bqsSRBqaUvUowQvppwCH4GTGSgc34gMR3wKvOudmJq6FI0TCzikA14C/n3PZE10cknsysLXAdcJ9z7stsypXC/0J8sHOuc7zqJ1KUzKwpsL9zbloO5arjZ8WY5Jx7JS6VE0kgM6uMnyHj3yA4J8WEghAiIiIiIiIiEhcamFJERERERERE4kJBCBERERERERGJCwUhRERERERERCQuFIQQERERERERkbhQEEJERERERERE4kJBCBERERERERGJCwUhRERERERERCQuFIQQERERERERkbhQEEJERERERERE4kJBCBERERERERGJCwUhRERERERERCQuFIQQERERERERkbhQEEJERERERERE4kJBCBERERERERGJCwUhRERERERERCQuFIQQERERERERkbhQEEJERERERERE4kJBCBERkSJiZsPNzJnZwATWId3MXERap6Be4xJUrWJVj0Qzs+nBcaif6LpA8auPZC+/nzPRPhtEROJBQQgRkSIUfDHMy2tcgus7MKjH8ETWo7Dl96HKzOpHOUdbzWy5mX1nZs+Y2clmllRE9d6jz0dJDjKYWSUzWx/s/+uJrk8ihN0/0xOw3QfMbL6ZrTOzzWa22MyeM7Mj4lmXwqAgg4jsbYrkS5OIiGQYESVtIFAPGA+kR+TNKdrqSD6tBR4M/l0aqAIcCJwJnAssMLOznXNzIpZ7FHgR+DsutYzuWKBMArefna/xx3FtoitSBM4CUgAHdDezWs65vxJcp72emQ0GHgHKAl8CY4GtQDPgNKC/mT0MDHXO7UxYRQtXfj9nivNng4jsxRSEEBEpQs654ZFpZtYJH4QY55ybHt8aST6tiXEu9wHuBgYBH5rZ4c65X0P5zrkVwIq41TKK8PoUN865TcDCRNejiFwI7MJfH9cD5wO3JbRGezkzOwN4Eh/U6uGcez8ivyEwBbgc2A5cE/dKFoH8fs4U588GEdm7qTuGiEgxEd7k1sxODLoQrA1vTmveQDObaWZrzGyLmf1kZqPMLCXKOo8ys8fN7Puw8ovM7F4zS4soOx14Nvjz1oguCJ2CMhndA8ystZlNNbPVQT2nmtmBQblqZvZ/ZrY02OY8M+uVzb73NLP3zWylmW0zsyVm9rCZ1YhSNqNrhZmdZ2ZzgubWK8zseTPbL6xs/eD4dQySloTtU3quTkw2nHMrnXPnAS8BoYBEeF2jNqM2s5ZBXRcHx2dlcI6eNLPqof0kb+fjMDN7x8xWWVjXk5yaZJtZYzN7LajDJjP7ysxOiVIu264hkdsx3wXjk+DPARH1HxiUidldw8yqm9n9ZvaL+S4wq81smpl1j1I2o9m/mVUNrvm/guUWmdlQM7NYx6CwmdnhwMHANPw1sQU438xK57yoXWlmPwTXxd/BfVQtSsH6ZvaEmf0cnLc15j8LxptZo8iVmtm5Zva57e6e8L2Z3WJmFXO5T9l2rbGILk/BdbIkyO4Ycf6HRyzbKrgf/gzu/3/N7BUza5WbugXrSMG3CADoHxmAAHDOLQZOAtYBQ83soLDls+06Ymbjwu+9sPSTgryF5rvfbDLfDeQWMysfZT3hn/NHm9lHwTnZYGYfB9dOePl04Nbgz2cjjmP9yHUGf3cK7sV6wd/hy0wPX3eszwYz62Bmr5vZsuCcLDWzZ82sQZSy1c1stJn9GOzHuuC+fcnMDo22fhEp2dQSQkSk+OkLnAi8C/wfu79IlgZeAXrjv9y/gv8yfSRwI77Jd3vn3IawdV0FHA58GqyvPNAOuBo4yfwv9+uDsuOANUBPYAYwPWw96RF1PBS4Lig3FmgBdAXamFk74IOgbq8AaUA/YLKZHemc+zp8ReabRl8GLAPeApbjH+AuA3oGy0Rrxj462OZbwEdAZ3wT+EPM7BDn3LZgf0awuwvMQ0EaYe+F4RbgdKCHmVUKO6ZZmFlLfDcEB7wNLAYqAA2As4En8MdgHLk/H0cCw/Dn+RmgGrAtF/VugG+y/iMwBqiBb7I+2cwuc849mt3COXgjeB8AzA37G3LodmRm++P3pS7wBfAqfp9OBd4ysxudc3dEWbQK8Dn+V+7JQLlgmfvwx3hUfnYkHy4K3sc651abHxOiH/4B+K1slnsA6AS8DLwJHINvUXGMmR3hnFsFYGY1gdlAKvAe8Dq+WX1doEfw9y9h6x2L7za0DJgAbMJ/xozA32MdIz43CsN0/Pm4AvgNfz2H5xHsyxnAc/hWI2/hP9v2x3/OdTezk51zH+Zie33xgcDZzrmYx9g594eZPYX/DBwSvAriNqAy/p6eAlTCn7cRQGcz6xKj20c3/L39Hr71RjP89fFx8Pm1KCj3INALH0idQuZ7Z02MOqUH278Sf42MiMjLlpldDdwDrMefk7+AxsA5+Oulk3NuXlA2GX/PNcJ/Dk/Fn8s6+Gv5C+CbnLYpIiWMc04vvfTSS684vvBfwB3QKSJ9eJC+CzgxynI3BvljgTIxlr03Ir0BYFHWNTIof11E+sAgfXiMuofyHXBWRN6YIH0VPnhSKizvzCDvtYhlzgrS3wVSYmzr1RjH73egblh6EjAzyDs1xjL183iu6gfLpeei7B+R5zXsvAwMS7svSOsVZR0VgeR8no8LY5RJ9//dZ0rrFLbcAxF5TYEN+H70dfNQl+y2My7GMlHzgXeC9HuinI/l+HukbZTz5ICngdJhec2AHcBqIu6bonjhH7w34ZvHlw3SugR1ezvGMqHrcxXQICLvqSDvibC0y4K0K6OsqyxQOezvU4OyC4GqYeml8C14HPBwTvdLLs5ltGVC52V6jGX+A2zG3zv1I/JaBNfh0tBxzOG4jw22dXsuyp4QlP0hD3UdR/TP7f9EKVsKP+aPA06PyBsepO8Ajo3IuzPIeyzGMgNj1C1qPlHuyZzygfb4++t/QLWIvGOBncA3YWknB9t+MMZxqBpr+3rppVfJfak7hohI8TPFOfdeeIKZlcL/orgWuNg5tz1imZHASqB/eKJzbolzzkXZxgPB+wn5rOOnzrmJEWkTgvdywH+dc7vC8l7C/zp9SMQyQ/FfYAe5iF9inXPj8L/69TKzSlHqcJtz7vew8jvY3X3h8Cjli9rS4D1LF5IYNkcmOOc2OueypOfCHOfck/lYbi27m3qH6rAQH0Qqiw8SxZWZ1cb/IvxvlLql41vAGH6MhUibiBhw0Dn3A/AZPjjQpEgqndk5QDIw0fnWOOB/If4N6GpmdbNZ9iHn3JKItBvw10p/M4scRDDaNbTNObcuLOmC4P0mF7SkCMrtwt9/W4FzrYhmeMnBxfjWWdcE5zaDc+57fACmFv7hNyehblh/5KJs6HOjTu6qGZuLMq5CcGwfCv6M9Rn7onPuo4i0McF7Ij6/Qq7C318XOT/WRIagvm8CbS3oehcm2rW4K/yaExEJUXcMEZHi5+soaY2B6vgHmWEWvXv7VqCWme3jnFsJEPT3vgLftLkxvqlw+MK181nH2VHSQiOzL3IR3RGcczvN7F/CvvSbWQV8UGIdcGGMfSqLn42iMfBtLuoQegBJi5JX1EI7EC3oE24SfmC8N8zsNfwD6hfOuR8LsO1o10xu/C/igTVkOr65eut81yj/Qtv8wvmBKyNNC97bRMn7Ocb+5Pq6CPr8d4pIXuOcezCnZQMXBu/PhBKcc6GxFG7FBwVujrHs9MgE59xyM/sBv7+NgQX4Zvm3A4+ZWVfgfXyz93kRwT/YfZyydGlwzi0N1n0IPkCzIBf7V5iOCt6PjPJQC35/wbdmebcItp9lzIa8Mj847X/xgbOG+NZM4WJ9xha3z6+Qo/CfYd2CaytSKMjaDN+Nawa+3teZWVt8d4zPge+iBMtFRAAFIUREiqN/oqTtE7zXI+LX4ShSgJXBr6YfA4cBP+P71S9j91gBt+JbLeRHtCkVd2STF8oP/38nDf/gnkru9inSmmzqkNMAgEUh9LDxb3aFnHOzzewo/C/cPfFdVTCz34H7nXMPZbd8DNGumYIsF0qvks/1FkRqRB0ihcYHqRIlb02MZfJyXXQi6/X4G7unaI3JzDrgH86+c87Njch+Fj92yHlmNiJouRMpV+fDOfd7MODfLfhxUXoG+cvN7AlgVNgDYCqw1Tm3Jsa6/8IHIapks2tFJfS5dkUO5aLd/5FCQdD9c1E2VCbbezUnZlYFP95BA/y4J8/ju+HsYPd4GLE+Y9dEJjjndgTB2ER8foXsg/9cjhUoC0kBcM6tM7Mj8PdMD3zXI4C1ZvYccGNkUFpEREEIEZHiJ9ov6WuC92nOueNzuZ6e+ADEB8BJ4U3Uzc8gkdODf1ELBSt+ds41zrZkMWdmTfBBiO1kbbGRhfODc/YKAkWHAMcBlwAPmtkO59xjeaxCTq0vYqmZQ/qasLTQL+yxvjtUyWcdIoWui1h1qxVRrlA5PxXr8HwuHhqQsnWsWQfw3QZ6AK9FyasJ/BQjHcLOh3PuJ+CsoKtWS/zArBfjAxMV8L/Ogz9OVc2sSoxARG6PZ1Gc/1B9arvog8/mxSz8VLnH48fPyU7oMzS8NUJ+9u98fADiGednyclgZkeSc3ClOFqDH2izfIyufFkE5+5CM7sI33qlEzAYP3bJfvhxSUREMmhMCBGRPcNC/MB6bYPRyHMjNE3f2y7r6OxHx1gmVK7If4kLxoCYD/wnGAegKBX1ft0WvE+JHNsiO8657c65r51ztwNnBMl9wooUdb0PMbPKUdI7Be/fhaWtDt6z/NJsfkrI1Mh08lf/0DaPiHGth8YHyDHYE0/mp9E8Bd8tamyM15tB8QujrYOs3UAwP2VrM2AjsCgyP+h3PzfoLhL6FTr8Ggodp85R1r1f2LqjBT/CZXf+K7O760S4nM7/F8F7hxy2nRuv4sfFaWtmJ8UqFHzWhMYTeSEsK7v9K42fsSdS6DP2jSh5sT5j8yO/nwM7IaP+ufUFvhtcnselcN5Pwfg0R+MHFu2RoPFGRKQYUxBCRGQPEAQRHsR3YRgTbaBGM6sUMcd8evDeIaJcPfzgftGsDN6zGzyvMN2L/79onJllGdDRzMqbWftC2E6R7JeZ7WNmT+OntVwJXJ+LZdrFeLgO/dodPsBbUZ+PVDJP34eZNcX/or8NCB98dDb+1+Ke4ecq2JeHY6w/z/V3zi3F9//fF7gpom718FORhmbBKE7OxTe9n+ycOz/aC/+L8HLgODNrGGUdV5hZg4i0O/ADXU4IdbEwszZBV4BI0a6h0HEaFb5M0ILivqDOz+ai//5CfGuJo8ysWdh6SgP3B3WMtBp/rmJ1kXgEH7S528wOisw072gzK5tD3UJBzcuCPyeaWZfIMsGxnYq/7j/BBy5Cy6/Hj3FQ18wiW5vdRDBVcoT04D3yM/Yg/HVaWPL7OZCf5UKz9/yfmdWPzDSzJDPrHPZ382DK2Ehp+GtrG7tbmYiIAOqOISKyJ7kdP23d2cAJZvYhfpT3NPz0ch3wA9T1Csq/BfwC9DWzT/GDhdXCT6n2Lr4ZcaTP8b+KnmFm2/F94R3+Aei3wt4h59xzZnYwfkT2X8zsPfwX+4r4L84dgCVE/xUyL6bhHwCfMrPJwHr8YIOP5nL5KmY2PPh3afxDTDP8dHblgO+B/tFGyo/iWuBYM5uF37d1+F9UT8Z/Yb8nrGxRn4+ZwIBgfIFZ+EHnTsMf/8sjZh/5O+jjPRD4n5m9jv8ecRzwJ35sgVqZV89P+EHrjjazifhf8ncCbzrn5mVTr4vwM1rcEIyz8ClQDX8OU4FbnXPfFGTHC5P5jvyDgz/HxCrnnNsWDFD536B8ZNBqJv7YvoyfrvMY4FD8mC7hXQz6AxeZ2Wf4e3wl/kG/J/76uDNsmy+bWTf8rB0/BIOhbsLP2nAQfiyDG3LaR+fcdjN7AN9V5TMzewXYgm9hkRSsp1XEMhvM7AugnZm9hW/lsh2Y6Zyb6Zz72czOAZ4L9nsaPtixK9ifw4P3NHaPZZNdHScFAdpHgWlm9jnwVbBsU+BE/P06H+gTZRDPu/BTcU4xs5fw56Ad/vN1OllbqjyHP5fXmFkLYB5+cMqT8a0jTs+pzrn0Mf6YXBkMhBkaI+QR51x23Wim4a+f18xsKj449ZtzbkKsBZxzM8xsKD4Y8ZOZvYu/xsriz8VRwb+rBIscB9wbnOdF+HGH9sV3OSqDn9JXQQgRySzW3J166aWXXnoVzQv/ZTbafPPDyWYu+LBypwHv4X9R3Y7/0jcbuBs4JKLs/vhfs5fiv4AuwD8EJwXbSo+y/uPwD33rgzIZdcU/gDr8F8vI5eoHedNj1DudGHPWB9t8DT+43Db84G5z8b+UHh3j+NWPsp5OQd64iPRS+C4TvwTrj7rv2exT+GtrUL/v8DMg9ACSYiyf5Zzi+6OPDc7FavwD4S/4h5+WhXU+sjvu4ccJPyvC6/gHrs34mTb6xFhXWfwD7u/Bcfwt+Ds51vnFz3YxDd/XfFf48Yh1voK8GvjWP78Gx3wNfiaRHvm49sYR5Z4rxHu6S7D+n3JRtlFwHJYBZSOu6Yb4gNwP+Af8f4AngeoR6zgceAw/he2KoGw6/pf9o6Js04Dz8E3tNwTlfwiuz5Qo5UP1qR9lPdfggyLb8PfrE0DVbJZpGFxfK/ABqCzXKz5AMCY411vwgbmf8DPJnAGUyuP5aBBcOwuC/Q2/f28MHfcYyw7ABylC9/kL+M/RqNcQPhj5Jn6Qy4347i/nx7omyeFzntify/2CdW8K25f62a0TPzbII/j7dXtkfcj+M/lQ/ECbvwfHYnVwzYwFuoWVOxAfsPgaf01vxQcep4aX00svvfQKf5lz+R3LSkRERESk+AtmDbkIGA8Mcvp1XkQkYdQdQ0RERET2dpfiZ7AZAGw3s8FOv8SJiCSEWkKIiIiIyF7PzCrgu7uUAV51zn2f4CqJiJRICkKIiIiIiIiISFxoik4RERERERERiQuNCREn1apVc/Xr1090NQrFli1b+OGHH0hLS6NBgwY45/jnn39Yvnw5O3fuJDU1lXr16lG6dGkAFixYwLZtu2fW2rVrF6mpqTRq1AiANWvWsHTpUrZt20ZycjL16tUjOXn3dOPLli3jn3/+YdeuXaSlpVG3bl1Klcpb/Gzjxo1UrFixEPZeZM+j619KMl3/UpLp+peSTNd/Yn377bcrnHPVo+UpCBEn9evXZ/bs2YmuRqE4/vjjSUtLo169ejz//POMHz+eO++8ky+//JK0tDTOOussqlSpwvjx47Ms65yjYcOGjBgxgnPOOYeff/6ZNm3aMG3aNI444gjuuecexo4dy9y5c0lKSuL999/nnHPOYc6cOdSqVYvevXtzxBFHMHr06DzVefr06XTq1KmQjoDInkXXv5Rkuv6lJNP1LyWZrv/EMrPfYuWpO4bkyYsvvkiVKlU49thjM9LeeustzjvvPPbff39SUlK47rrreOmll9i0aVOW5WfOnMmKFSvo06cPAO+//z5HH3007du3Jykpieuuu46lS5cyY8YMAMaPH895551H8+bNSUtL4+abb2bcuHFx2VcREREREREpXApCSK6tW7eOW265hfvvvz9LXvgAp845tm7dys8//5yl3Pjx4+nTp0+mplGRyzrn+P57P2D1ggULaNWqVUZ+q1atWLZsGStXriyUfRIREREREZH4URBCcu3mm2/mvPPOo06dOpnSTzzxRJ5++mnS09NZu3Ytd911F0CWlhCbNm3i1VdfZeDAgRlpXbp0YcaMGUyfPp1t27Zxxx13sG3btoxlN2zYQGpqakb50L/Xr19fFLsoIiIiIiIiRUhBCMmVOXPm8OGHH3LVVVdlyRs0aBD9+vWjU6dONG/enM6dOwNkCVa89tprVK1alY4dO2akNW3alPHjx3PppZey3377sWLFCpo1a5axbEpKCuvWrcsoH/p3pUqVCn0fRUREREREpGhpYErJlenTp5Oenk7dunUB30Jh586d/PDDD3z33XeMGDGCESNGAPDBBx9Qu3ZtateunWkd48eP55xzzsHMMqX37duXvn37An6mjLFjx3LooYcC0Lx5c+bOnctpp50GwNy5c9l3333ZZ599inR/RUREREREpPCpJYTkyuDBg/n111+ZM2cOc+bM4aKLLqJbt268//77rFq1il9//RXnHD/88ANDhw7llltuyTSN5p9//sknn3zCgAEDsqz722+/ZefOnSxfvpzBgwfTo0cPmjZtCsA555zD2LFj+eGHH1izZg2jRo3K1J1DRERERERE9hwKQkiuVKhQgZo1a2a8UlJSKF++PNWrV2fFihWcdNJJVKxYka5duzJo0CAGDx6cafkJEyZw5JFH8p///CfLuq+44gqqVKlCkyZNSEtL46mnnsrIO/HEE7n22mvp3LkzdevWpV69ehktLkRERERERGTPou4Ykiv1r38nIuVQqHPo7vTe91MjyHn4X3g4S/mD4KiDoqwHaD+Mfdr7f74PNB85PaJAE5YtW1aA2ouIiIiIFL0tW7awfPlytmzZwo4dOxJdnRItNTWVH3/8MdHV2OuUKVOGGjVqULly5XyvQ0EIERERERGRAlq7di3Lli2jevXq1KxZk6SkpCxjoUn8rF+/XoPZFzLnHJs3b2bp0qUA+Q5EqDuGiIiIiIhIAa1YsYI6deqQlpZGmTJlFICQvY6ZUaFCBWrXrs2///6b7/UoCCEiIiIiIlJA27ZtIzk5OdHVEClyycnJbN++Pd/LKwghIiIiIiJSCNT6QUqCgl7nCkKIiIiIiIiISFwoCCEiIiIiIiIicaEghIiIiIiIiBQJM+P8889PdDUSYty4cZgZ6enpia5KsaIpOkVERERERIpQ/evfSXQVAEgf3a3A6/j777+56667eOedd/jjjz+oUKEChxxyCBdeeCGnnXZaIdRS9nYKQoiIiIiIiEiOvvnmG7p27crmzZs599xzOfjgg1m7di0vv/wyp59+OlOnTuXZZ5/VAJ2SLQUhREREREREJFtr167llFNOAeDrr7+mefPmGXlDhw7lsssu47HHHuOggw5i6NChiapmtv6/vTuPs7H8/zj+umbMmGF2M2bso8hOIf2+skcoS7YQZU1oQ0WKjKWSpJTqmzZL0qZCSciashYhS2h8Q9nGPoYZc/3+OGdOc2YzwyyM9/PxOI8z57qu+7qv67jHnPtzriU2NpZChQrldTOue1oTQkRERERERDI0depU9u/fz4QJE9wCEOBY92HSpEnccMMNvPDCC8TFxaU6/ssvv6RatWr4+PhQsWJFZs2alarMO++8Q40aNfDz8yMgIIDKlSszevRotzLx8fE8//zzVKxYkYIFCxIREUG/fv2IiYlxK1e1alWaNm3KypUrqVu3Lr6+vjzzzDO0bt2aiIgILl68mOr8ffv2pVChQpw5c8aV9sMPP9CkSRP8/f0pXLgwDRs2ZNWqVamOXbNmDXXr1sXHx4fSpUszfvx4rLUZv6nXKY2EEBERERERkQzNnTuXggULct9996WZ7+3tTbdu3Rg7diyrV6/mjjvucOWtXbuWL774gkceeYTQ0FBmzJhB9+7dKVCgAJ07dwbgww8/pH///rRr144BAwZgrWXnzp1uN/zWWjp06MDixYvp06cP1atXZ+/evbzxxhusW7eONWvW4OPj4yr/559/0rZtW3r37k2vXr0oWrQoderU4ZtvvmHZsmU0bdrUVfbChQt8+eWXtG7dGj8/PwA+++wzunbtSsOGDRk7dizWWqZNm8Ydd9zBkiVLaNCgAQC///47TZs2xd/fnxEjRuDt7c3UqVNd9Yg7BSFEREREREQkQ7///jsVKlRwu8lP6eabb3aVTR6E2Lp1K0uXLqVx48YA9OvXjxo1avDkk0/SsWNHPD09mTdvHlWqVOHLL79Mt/5PPvmE+fPns2jRIpo1a+ZKb9KkCc2bN2fmzJk8+OCDrvS9e/cyZ84c1zQSgLNnz1KoUCFmz57tFoRYuHAhx48fdwVZzp49y4ABA+jSpYvbqI3+/ftTrVo1hg8fzurVqwEYOXIk58+f55dffuGmm24CoFevXpQvXz79N/Q6pukYIiIiIiIikqFTp04REBCQYZmk/FOnTrmlV69e3RWAAChUqBD9+vVj//79bNq0CYCgoCD++usvfv7553Tr//TTT7nhhhu45ZZbOHr0qOtRs2ZNAgMDWbp0qVv5YsWK0a5dO7e0woUL06ZNG7788ksuXLjgSp89ezZBQUG0bNkSgMWLFxMTE0P37t3dznX27FmaNm3KmjVriI2N5eLFiyxcuJC77rrLFYAACAsLo1u3bhm+X9crBSFEREREREQkQwEBAamCCykl5fv7+7ulV6hQIVXZpLQ///wTgKeffpqgoCDq1q1LmTJl6N27N/Pnz3dbV2HXrl3s3buXsLCwVI+TJ09y+PBht3OULVs2zZ067rvvPk6cOMHChQsBx4KV8+fPp0OHDnh7e7vOBXDXXXelOtc777xDYmIix44d48iRI8TGxmbYR3Gn6RgiIiIiIiKSoUqVKrFx40bi4uLSnZKxefNmgFQLV2ZGhQoV2LFjB99//z2LFi3i+++/58MPP6Rly5Z88803eHh4kJiYSMWKFXnjjTfSrCM4ONjtta+vb5rlWrRoQUhICLNnz6ZNmzbMmzePs2fP0rVrV1eZxMREAN5//31Kly6dZj1hYWGcOHEiy3293ikIISIiIiIiIhlq06YNP/30E7Nnz6ZXr16p8uPj45k1axZFihShbt26bnk7d+5MVT4prWzZsq40X19f7rnnHu655x6stQwfPpyXXnqJVatW0bBhQ8qVK8fatWtp0qQJHh6XP6jfy8uLDh06MGvWLM6ePcvs2bMpVqyY25SRcuXKARAaGuq2dkRKYWFhFCpUKMM+ijtNxxAREREREZEMPfTQQxQvXpxhw4axY8cOtzxrLU8++SR79uxh+PDhqUYg/Pbbbyxbtsz1OjY2lqlTp1KiRAnXYpbHjh1zO8YY48pLGm3QpUsXjh49ymuvvZaqfRcvXky1TWdG7rvvPmJjY5k5cyYLFy6kc+fOboGN5s2bExQUxLhx4zh//nyq448cOQKAp6cnzZs3Z8GCBa4pHEn5aW1DKhoJISIiIiIiIpcQFBTEl19+ScuWLalVqxa9e/fm5ptv5uTJk3z22WesXbuWHj16MGTIkFTHVq1alXbt2rm26Jw5cya7d+9m1qxZeHp6AtCsWTPCwsK4/fbbKVGiBH/99RdvvvkmERERNGrUCIBu3boxZ84cnnjiCdfoiAIFCrBnzx7mzJnDmDFj6NmzZ6b606BBA0qUKMHQoUO5cOGC21QMcKxrMXXqVLp27Uq1atXo1q0bxYsX58CBA6xYsQLAFVgZM2YM33//PQ0bNuSRRx7By8uLqVOnEhkZ6ZqiIv9SEEJERERERCQHRY+/O6+bkC1uu+02tm7dyvjx41mwYAHvvvsuPj4+1KxZk08//ZR777033eNGjx7NqFGj+OOPPyhTpgzTp093bYcJMGDAAGbPns2UKVM4efIk4eHhtGrViueee47AwEDAMTriiy++4I033mDatGksXLgQb29vypQpQ+fOnWnSpEmm++Lh4UHnzp2ZNGkSN954I3Xq1ElVplOnTpQoUYIXXniByZMnExsbS0REBHXq1KF3796uclWrVmXx4sU88cQTjB07lqJFizJw4EDCw8PdyomDSb7aqOSc2rVr2w0bNuR1My5b5NPf5un5r/Q/7uXLl7siqCLXG13/cj3T9S/XM13/uWv79u1UqlQpr5shTqdPn061S4dkn0td78aYjdba2mnlaU0IEREREREREckVCkKIiIiIiIiISK5QEEJEREREREREcoWCECIiIiIiIiKSKxSEEBEREREREZFcoSCEiIiIiIiIiOQKBSFEREREREREJFcoCCEiIiIiIiIiuUJBCBERERERERHJFQpCiIiIiIiIiEiuUBBCRERERERERHLFVRWEMMbUN8ZY56NkirwAY8wUY8w/xphzxpg1xphm6dRzkzFmnjHmlPMx1xhzYzplWxpj1jrr/McY87oxxi+NcsYYM9gY84cx5rwxZpcx5jFjjMme3ouIiIiIiIjkb1dNEMIYUwB4EzibRp4B5gN9gPeBQc6sBcaYhinKFgdWATcDUcBooBaw0hgTlqJsM+Ab4KKzzg+BfsCXaTRxDDAJWAM8DKwHJgPPZK2nIiIiIiIiIpdv2rRpGGOIjo6+qutMS4EcrT1rHgUigHf5N8iQpD3QAOhlrZ0GYIyZDmwFXgFqJys7HAgGqlprdznLfussOwx4MlnZScBuoLG19ryz7B7gXWNMK2vtN8604sBQYLq1tqfz2PeMMRZ41hgz1Vp75ErfABERERERyYeiAvO6BQ5RJy/70GnTptGrVy/Xaw8PD8LCwmjYsCFjxoyhQoUK2dFCuQ5cFSMhjDHFcIxaeAZI6zfjXuAE8FFSgrU2DseoiFopplp0AhYlBSCcZXcAPwCdk52zElAVeDcpAOE0AziTvCzQFvAGpqRo15uAL9AmE90UERERERG5po0cOZKZM2fy7rvv0rlzZ+bNm0e9evU4dOhQXjdNrhFXy0iIicAfwAfAc2nk1wR+tdYmpEhflyx/jzGmBBCeLD1l2TuNMWHOUQs1U9QBgLX2gjFmU7L8pPrjgV9T1LkRSHTmv59u70RERERERPKBO++8k3r16rleV6pUiQEDBjBjxgyeeuqpPGyZXCvyPAjhXNOhK1DPWpuYzjqPxUg7sPC387l4snLJ09MreyQTZaumOP8Ra+3F5IWcAYtjyc7vxhjTD8caE4SHh7N8+fK0il0TnqiWMv6Tu670vTtz5sw1/f6LXAld/3I90/Uv1zNd/7krMDCQ06dPp5nnn8ttSU967cuMuLg4AGJjY93qqVnT8d3t9u3bXemHDx/m+eef57vvvuPYsWOULFmSBx54gMGDB+Ph8e9gfGstH374IdOmTWPnzp0ULFiQihUr8vjjj3P33Xe7ys2cOZO3336bP/74Az8/P5o2bUpUVBQlSpRwlenfvz+ffvopO3bs4KmnnuKHH36gYMGC9OrVixEjRnDkyBGGDh3KDz/8gDGG7t27M27cOFd79u3bR7Vq1RgxYgTFixdn0qRJ7N+/n+rVq/Paa69RtWpVZs+ezSuvvMK+ffuoWLEir732GrVq1XJ7n/bu3cu4ceNYtmwZp0+f5sYbb2TAgAH07NnTVWbVqlXcfffdvPPOOxw9epT//ve/HD58mGrVqjFp0iRuvvlmtzrXrVvHM888w+bNmwkLC6Nv374ULVoUcPyeJ//3WL58ORMnTuSXX34hMTGRW265hZEjR1K3bt3LrjO96+Fy/3/J0yBEssUoZ1lrf8qgqC9wPo30uGT5yZ+zo6xvstfpnT+tsi7W2qnAVIDatWvbRo0apVPF1a/n09/m6fmjuzW6ouOXL1/Otfz+i1wJXf9yPdP1L9czXf+5a/v27fj7Xy3hhrRdSft8fHwAKFSokFs9R444lsYLDw/H39+fo0eP0rRpU+Li4ujXrx/Fixdn9erVjB49mn/++Yf//ve/rmP79+/PO++8Q6NGjRg7dixeXl6sX7+elStX0qVLFwDGjx/P8OHDqVevHhMmTODAgQO8/vrr/Pzzz/z666+EhIQA4OXlhbWWjh07UrNmTUaPHs3ixYt5+eWXCQsLY+bMmdSuXZsXX3yR+fPnM2XKFKpVq0a/fv0A8PNzbJD47bffcurUKR566CESEhIYP348HTt2ZMyYMUyYMIF+/fpx8eJFxo8fT48ePdizZw8FCjhuq3ft2kWTJk0ICQlhyJAhBAcH89133/HYY49x9uxZnn76add7CDB16lTOnz/P448/TkJCAi+//DLdu3dn9+7deHl5AfD777/Ttm1b/P39GTFiBN7e3kydOtXVXj8/P9e/x2effUbXrl1p2LAhY8eOxVrLtGnTaN26NUuWLKFBgwZZrjOj6+GWW27J4lXkkKUghDEmBKgEhDqTjgLbrbUxl3V2eBwoA9x5iXLngIJppPsky0/+nB1lzyV7nd750yorIiIiIiKSL508eZKjR49y4cIFNm/ezKBBg/Dw8KBjx44APPvss5w+fZotW7ZQrJhj8PlDDz1EyZIlGT9+PEOGDOGmm25i5cqVvPPOO/Ts2ZMPPviA5CPirbUAHD16lKioKOrXr8/SpUtdN/sNGjSgVatWjB8/ngkTJriOS0xMpFWrVowbN47Tp0/z6KOPEhkZybBhwxgxYgRjxowB4MEHHyQyMpIPPvjAFYRIsnfvXnbv3k1oqOOWNygoiIEDBzJ06FB27dpFkSJF3NKXLFlCixYtAHj00UcJDQ3ll19+oXDhwgAMGDCA++67j7FjxzJgwAACA/9dpDQmJoZt27bh6+v4TrtChQq0a9eORYsWuUaCjBw5kvPnz/PLL79w0003AdCrVy/Kly/v1u6zZ88yYMAAunTpwqxZs1zp/fv3p1q1agwfPpzVq1dnqc6ccsmFKY0xNxhjxhhjtgKHgZXAV87HSuCIMWabMWZsigUiL1VvIDAKxzoQ3saYSGNMJBDkLFLSGFPS+fPfpD3lIWlKxcFk5cimsgeTvf4bKGqM8UzRB2+gSIqyIiIiIiIi+VKrVq0ICwujRIkS3HXXXZw9e5aPP/6YWrVqYa3l888/56677sLLy4ujR4+6Hs2bN8day7JlywD4/PPPAXj++edJOSU/6fWSJUs4f/48gwYNcgUgAO6++24qV67MN998k6p9Dz30kOvnAgUKULt2bay1PPjgg6nS9+7dm+r4Dh06uAIQAP/5z38AuOeee1wBiOTpSXUcP36cxYsX06lTJ86dO+fW95YtWxIbG8uaNWvcztWzZ09XAAKgYcOGbnVevHiRhQsXctddd7mCBQBhYWF069bNra7FixcTExND9+7d3c599uxZmjZtypo1a4iNjc1SnTkl3ZEQxpgKwDgc22OeAlYAs4G9QAxgcGyFeSNwK/AI8Iwx5ktghLV25yXOHYxjetRjzkdKPwP7gEjgFxyLShZIsTjlbc7nXwGstQeMMYed7UnpNmB/sq00f3E+3+rsW1K/vYGbga+THfsL0Be4BdiQLL02jkDOL4iIiIiIiORzr776KlWrVuX06dN89tlnfP31166pA0eOHOH48ePMnDmTmTNnpnn84cOHAdi9ezchISEUL57m8noAREdHA1CxYsVUeWkFITw8PChZsqRbWlBQULrpx48fT1Vv6dKlU5XLKD2pjj/++ANrLc8//zzPP/98mv1J6nuSMmXKuL0ODg4GHCMkwPF+xsbGprn9acq0Xbscm0PeddddaZ4b4NixY3h5eWW6zpyS0XSMrcBSHEGI76y1FzKqyHnz3hIYCGzBsaVlRg4D7dJI74Jje8y+wF/OtC9wbNPZHZjmPJ8P0BvHrhm7kx3/BfCgMaa8tfYPZ9mKQBPg9aRC1trtxpjfnWXfSLZN5wOAH/B5sjrnAZNxBFp6JksfiGNNiPmX6KuIiIiIiMg1r3bt2q7dMdq1a0fbtm3p2bMnt912G56ejoHjnTt3pm/fvmkef8MNN+RY24wxqUZVZJSeNO0juaQ+ZDY9qY7ExEQAHnvsMVq3bp1m2SpVqmSpzqxIOv/777+fKmCSJCwsjBMnTmS57uyWURDiNmttpr/hdwYp5gJzjTE1M1E+FvfRBgAYY252/vi9tXa/8+c5wI/A28aYcjiCEz1xjJJolqKKF4BOwA/GmFdxjNgYgiPo8VKKsk8A3wJLjTHTnfUNAX4gWWDBOcLiZRwjPTxwjJxoDHQDnrPWHkZEREREROQ6M2HCBCpXrszYsWN58803CQgI4MKFCzRt2jTD48qVK8fChQs5ePBguqMhIiMjAdixYweVK1d2y9u+fTtly5bNlj5khxtvdKxM4Onpecm+Z1ZYWBiFChVi587UkwxSppUrVw6A0NDQDM+flTpzSrprQmQlAJGdx6ZTXyLQCvgQeBB4DfAE7rbWLktR9gBQH/gNGA1E4Zgu0cBaeyhF2YVAaxyjNl4H+gDvAe1s6vDTSOBJoC7wFo7pHYNxTFkRERERERG57iQtpvjhhx/yzz//0KlTJ+bNm8f69etTlT19+jTnzzsGoHfq1AlwLGSZ8tYr6XWzZs0oWLAgkydPJiHh31n53333Hdu2bUt3xEFeCAsL44477uD9999n3759qfKTdhHJCk9PT5o3b86CBQtc0y2S6kq++CRA8+bNCQoKYty4ca73OK3zZ6XOnJLlLTqNMf7A/wFFgSUpb+yvlLU2CkfgIGX6SRzTHwZmoo6dOIIWmTnfAmBBJsolAq84HyIiIiIiIgIMHTqUOXPmMHHiRF588UWWL19O/fr16d27N9WrV+fMmTNs27aNL774gi1bthAZGUmDBg3o27cv7733HtHR0bRq1YqCBQuyceNGChUqxJtvvkmRIkWIiopi+PDh3HHHHXTs2NG1RWfp0qUZNmxYXnfdzVtvvcXtt99OjRo16Nu3LzfddBMxMTFs2rSJr7/+mri4uCzXOWbMGL7//nsaNmzII488gpeXF1OnTiUyMpLNmze7yvn7+zN16lS6du1KtWrV6NatG8WLF+fAgQOsWOFYAjFpUdDM1plTsrpF51AcIwIKAxbHVIhDxphQ4H/AEGvtfzOoQkRERERE5PoSdTKvW5Cj6tSpQ6NGjZg6dSrPPvssa9euZdy4ccydO5f33nuPoKAgypcvz3PPPUdERITruKlTp3LzzTe7jitUqBBVqlRh6NChrjJPP/00YWFhTJ48mSeffBJ/f3/at2/P+PHjCQkJyYvupuumm25i48aNjBkzhk8++YTDhw8TGhpKpUqVeOWVy/suu2rVqixevJgnnniCsWPHUrRoUQYOHEh4eDi9e/d2K9upUydKlCjBCy+8wOTJk4mNjSUiIoI6deq4lc1KnTnBZHbRC2NMX2Aqjh0yFgLTgabW2qXO/E+AItbalGs0CFC7dm27YcOGSxe8SkU+/W2enj96/N1XdPzy5ctp1KhR9jRG5Bqj61+uZ7r+5Xqm6z93bd++nUqVKuV1M8Tp9OnT+Pv753Uz8q1LXe/GmI3W2tpp5aW7JkQaHgfmWWu7kfb0hV8B/daJiIiIiIiISJqyEoQoD3yXQX4MEHplzRERERERERGR/CorQYhTQHAG+Tfh2AZTRERERERERCSVrAQhlgC9jDE+KTOMMaWBvjjWihARERERERERSSUrQYgRQBEcaz88jmN3jNbGmInAZuACMCbbWygiIiIiIiIi+UKmgxDW2r1AXRxbcT4LGBzBiCHABqCetXZ/TjRSRERERERERK59BbJS2Fq7C2hujAnCsVClB7DHWns0B9omIiIiIiIiIvlIpkdCGGOeM8ZUBbDWnrDWrrfWrk0KQBhjqhhjnsuphoqIiIiIiIjItS0ra0JEAdUzyK8KjLqi1oiIiIiIiIhIvpWVIMSlBONYnFJEREREREREJJUM14QwxtQDGiRLamuMiUyjaBBwH7At21omIiIiIiIiIvnKpRamvIN/p1hYoJPzkZb/4dgpQ0REREREROS6ExUVxejRo7HW5nVTrlqXCkK8BkzDsR3nXmAQMDdFGQuctdYey+a2iYiIiIiIXPOqTa+W100AYEuPLZd97LRp0+jVqxerVq2iXr16WT721KlTPPbYY5d9/qvJiRMneO2112jSpAkNGjS49AHiJsM1Iay1J621+6y10UBj4BPn6+SP/ykAISIiIiIiImmZNm0ar7/+el43I9ucOHGC0aNHs3LlylR5I0aM4Ny5c3nQqmvHpUZCuFhrV+RkQ0REREREREQyKzY2lkKFCuV1M9wUKFCAAgUyfZt9Xcr07hjGmKWZePyQk40VERERERGRvNezZ08KFCjAoUOHuPfeewkICCA4OJi+ffu6jQSIjIxkxYoV7NmzB2MMxhgiIyNd+fHx8Tz//PNUrFiRggULEhERQb9+/YiJiXE7X2RkJE2bNmXlypXUrVsXX19fnnnmGQA2bdpEq1atCA8Px8fHhxIlStC9e3f279/vVscPP/xAkyZN8Pf3p3DhwjRs2JBVq1al6tuhQ4d4+OGHKV26NAULFqRkyZLcd999HDhwgOXLl1O2bFkARo4c6epTVFQU4FgTwhiTqs4PPviAGjVq4OPjQ1hYGPfff3+q9mX2Pb3WZSVE44Fj/YfkPIFIoCSwGziQPc0SERERERGRq5m1lhYtWlC5cmVeeukl1q9fz/vvv09YWBgvvvgiAK+99hrDhw/n+PHjTJw4EQA/Pz/X8R06dGDx4sX06dOH6tWrs3fvXt544w3WrVvHmjVr8PHxcZ3vzz//pG3btvTu3ZtevXpRtGhRjhw5QtOmTQkODmbIkCGEhoZy8OBBFixYwIEDByhZsiQAn332GV27dqVhw4aMHTsWay3Tpk3jjjvuYMmSJa61HQ4dOsRtt93GwYMH6du3LzVq1ODIkSN8++237N69m0qVKvHqq68yePBgOnbsSNu2bQGoXr16uu/T+PHjGT58OPXq1WPChAkcOHCA119/nZUrV/Lrr78SEhKSpff0WpeV6RiN0sszxrQF/gs8ng1tEhERERERkatcYmIizZs3Z/z48QAMGDCAmJgY3nvvPdcN8z333MNrr71GfHw83bt3dzv+k08+Yf78+SxatIhmzZq50ps0aULz5s2ZOXMmDz74oCt97969zJkzh/bt27vS5s6dy7Fjx/juu++49dZbXemDBg3C398fgLNnzzJgwAC6dOnCrFmzXGX69+9PtWrVGD58OKtXrwZg+PDh7Nu3j6VLl9K4cWNX2REjRmCtxRjDPffcw+DBg6lRo0aqPqV09OhRoqKiqF+/PkuXLnVN1WjQoAGtWrVi/PjxTJgwIUvv6bUu09MxMmKtnQvMxrGbhoiIiIiIiFwHBg4c6Pa6YcOGHD16lNOnT1/y2E8//ZQbbriBW265haNHj7oeNWvWJDAwkKVLl7qVL1asGO3atXNLCwoKAmDevHmcP38+zfMsXryYmJgYunfv7naes2fP0rRpU9asWUNsbCyJiYl8+eWXNGvWzC0AkSStaRaXsmTJEs6fP8+gQYPc1oq4++67qVy5Mt98802qY67kPb0WZOeKGTuAh7KxPhEREREREblKeXh4uKY7JAkODgYgJibGNRIhPbt27WLv3r2EhYWlmX/48GG312XLlk0VCGjQoAFdunRh3LhxvPrqq9SrV4+7776b1q1bu86/a9cuAO66665023Ls2DG8vb05efIk1apl35aq0dHRAFSsWDFVXlpBiCt9T68F2RmEuAs4mY31iYiIiIiIyFXKGIOHR9qD661NuZxgaomJiVSsWJE33ngjzfykm+8kvr6+abZh9uzZPPXUU3z77bcsWbKEwYMHM3r0aJYvX07VqlVJTEwE4P3336d06dJpnissLIyTJ/P+dvZK39NrQaaDEMaY59LJCgIaATcDY6+4RSIiIiIiIpJvpDeNoVy5cqxdu5YmTZqke+OdWTVr1qRmzZqMHDmS3377jVq1avHKK6/w4YcfUq5cOQBCQ0Np2rRpunV4e3sTEBDAli1bMjxXVqZlJO0EsmPHDipXruyWt337dtdOG9eTrPxLR6Xz6AHEA32dr0VEREREREQAKFy4MCdOnEiV3qVLF44ePcprr72WKu/ixYuptulMy/Hjx1ONEKhUqRK+vr6uczZv3pygoCDGjRuX5roRR44cARxTIZJ261i2bFmqcknnKVy4MECafUqpWbNmFCxYkMmTJ5OQkOBK/+6779i2bRutW7e+ZB35TVZ2x8iWRSxFRERERETk+lGrVi2+/fZbnnzySWrVqoWfnx+tW7emW7duzJkzhyeeeIJVq1bRsGFDChQowJ49e5gzZw5jxoyhZ8+eGdY9ffp03njjDdq1a0e5cuVISEjgk08+4fTp03Tt2hUAf39/pk6dSteuXalWrRrdunWjePHiHDhwgBUrVgC4gg4vvPACixcvpnnz5q4tOmNiYliwYAHjxo2jYcOGhIaGUrp0aT7++GNuvPFGgoODqVq1KlWrVk3VviJFihAVFcXw4cO544476Nixo2uLztKlSzNs2LDsfbOvAdm5JoSIiIiIiIiksKVHxsP787shQ4awY8cO3n//fV555RXKlClD69atMcbwxRdf8MYbbzBt2jQWLlyIt7c3ZcqUoXPnzjRp0uSSdTds2JANGzYwZ84c/vnnHwoVKkSVKlWYPXs29957r6tcp06dKFGiBC+88AKTJ08mNjaWiIgI6tSpQ+/evV3lIiIiWLduHaNGjeLrr7/mvffeIzw8nIYNG1K+fHlXuenTpzNkyBAGDRrEhQsXGDVqVJpBCICnn36asLAwJk+ezJNPPom/vz/t27dn/PjxhISEXME7e20y+WVxi6td7dq17YYNG/K6GZct8ulv8/T80ePvvqLjly9fTqNGjbKnMSLXGF3/cj3T9S/XM13/uWv79u1UqlQpr5shTqdPn84XO0lcrS51vRtjNlpra6eVl+5ICGPMn0BWIxTWWntjFo8RERERERERketARtMxVpD1IISIiIiIiIiISJrSDUJYa3vmYjtEREREREREJJ/TjhciIiIiIiIikiuytDuGMaYA0BdoBZR1Jv8JzAM+sNYmpHesiIiIiIiIiFzfMj0SwhgTCPwMvAXUBc46H/8B/gv85CwjIiIiIiIiIpJKVqZjPA/cAjwChFtr61hr6wDhwMPOvHHZ30QREREREZGrn7Va11/yvyu9zrMShGgHvG2tfctaG5+sAQnW2reBd4D2V9QaERERERGRa5C3tzfnzp3L62aI5Lhz587h5eV12cdnJQhRBPg9g/xtzjIiIiIiIiLXldDQUPbv309MTAzx8fEaFSH5jrWW2NhYDhw4QNGiRS+7nqwsTBkNNAfeTie/hbOMiIiIiIjIdSUwMJCCBQty5MgRjh07RkKC1uzPS3Fxcfj4+OR1M/IdLy8vwsPDCQgIuOw6shKE+AAYb4yZCUwEdjrTKwJDcOyYMeyyWyIiIiIiInIN8/HxoVSpUnndDAGWL1/OLbfcktfNkDRkJQjxMnAD0A+4L0WeAd6x1k7MroaJiIiIiIiISP6S6SCEdUxq6m+MeQPHqIdIZ1Y08I21dlu2t05ERERERERE8o2sjIQAwBlsUMBBRERERERERLIk00EIY4wv4G+tPZwsrSjwEBAEfGatXZvtLRQRERERERGRfCErIyGmAlWAmgDGmELAGv6dlvGoMaaxtXZ1trZQRERERERERPIFjyyUrQ/MS/a6C44AREugOLADeCbbWiaSwvnz5+nTpw9lypTB39+fm2++me+++w6A33//ndq1axMcHExwcDBNmzbl999/dx07bNgw/Pz8XA9vb2+qVavmym/cuDFhYWEEBARQo0YN5s6d68r7+++/adOmDcWLF8cYQ3R0dK71WUREREREJD/JShCiKPC/ZK9bAeustd9ba/8BPsQ5SkIkJyQkJFCqVClWrFjByZMnGTduHPfeey/R0dEUL16cL774gpiYGI4ePUqbNm3o0qWL69iXXnqJM2fOuB5169alU6dOrvzJkyfz999/c+rUKaZOnUr37t35+++/AfDw8KBFixbMmTMn1/ssIiIiIiKSn2QlCBEL+AMYYzyARsDiZPlncKwNIZIjChcuTFRUFJGRkXh4eNCqVSvKli3Lxo0bCQoKIjIyEmMM1lo8PT3ZvXt3mvVER0ezatUqHnjgAVda9erVKVDAMTvJGEN8fDx//fUXAOHh4QwcOJBbb7015zspIiIiIiKSj2VlTYjfgO7GmJlAByAQ+C5ZfiRwOI3jRHLEoUOH2LVrF1WqVHGlBQUFcebMGRITExkzZkyax82YMYP69esTGRnplt6qVSuWLFnC+fPnad68ObVr187J5ouIiIiIiFx3shKEGAt8Cxxxvl5hrf0pWX4rYF12NUwkI/Hx8XTr1o0ePXpQsWJFV/qJEyc4e/Ys06dPp0yZMmkeO2PGDEaMGJEq/ZtvviE+Pp4lS5awfft2PDyyMlBIRERERERELiXTd1nW2mU41nwYDPTCsSAlAMaYEGApMCW7GyiSUmJiIvfffz/e3t5MmZL6kitcuDD9+/fngQce4PBh98E5P/74I//88w8dO3ZMs24vLy9atmzJokWLmDdvXpplRERERERE5PJkZSQE1todOHbBSJkegyM4IZKjrLX06dOHQ4cOsWDBAry8vNIsl5iYSGxsLAcOHKBo0aKu9OnTp9O+fXv8/PwyPE9CQgJ79uzJ1raLiIiIiIhc77IUhAAwxtwE3A2UdSb9CSyw1u7MzoaJpGXAgAFs376dJUuW4Ovr60pfvHgxoaGhVK9enbNnzzJixAiCg4OpVKmSq8y5c+f47LPP+Oqrr9zq3LFjB3/++SeNGjWiQIECfPrpp6xcuZIJEya4ysTFxXHx4kXAsVVoXFwcPj4+OdxbERERERGR/CXT0zGMMZ7GmDeB34FXgEecj1eA340xbxljPHOmmSKwb98+3nnnHTZt2kRERAR+fn74+fkxa9YsTpw4QdeuXQkMDOTGG29kz549LFy40C1Q8PXXXxMUFETjxo3d6rXWEhUVRdGiRQkLC2Py5Ml8+umn1Kz5746zvr6+rtETFStWdAuAiIiIiOSG8+fP06dPH8qUKYO/vz8333wz333nWCf+woULdOzY0bVb2PLly92OjYqKwsvLy/X5yc/Pj71797ry58+fT9WqVfHz86Nu3br8/vvvrjxrLSNGjKBEiRIEBgbSqFEjtm3blit9FpH8JysjIUYDA4CPgdeApJEPFYFBwENADJB6xT+RKxUVSBnAjgpInffHQAA6dQHwBC4AP8KX9eFLZ5kKo+m6cxRdewGjg9wOrwSsbQm09AAssAs293Q8nKy12dgZERERkaxLSEigVKlSrFixgtKlS7NgwQLuvfdetmzZQvHixalXrx6DBg2iU6dOaR7fuXNnPvroo1Tpf/zxB926dWPBggX83//9Hy+//DJt2rRhx44dFChQgM8//5wPPviAH3/8kTJlyjBixAjuv/9+fvnll5zusojkQ1lZ/r838JW1tru1doO19rTzsd5a2w2Y6ywjIiIiIiLZrHDhwkRFRREZGYmHhwetWrWibNmybNy4EW9vbwYNGkS9evXw9Mza4OTvv/+e+vXrU69ePQoUKMCwYcM4cOAAK1asAODPP/+kXr163HDDDXh6etK9e3e3kRIiIlmRlSBEALA4g/zFzjIiIiIiIpLDDh06xK5du6hSpUqmys+fP5+QkBCqVKnC22+/7ZaXfNSntRZrLVu3bgWgS5cu7Nmzh127dhEfH8/06dNp0aJF9nVERK4rWZmOsR6olUF+LWDdlTVHREREREQuJT4+nm7dutGjRw8qVqx4yfL33nsv/fr1Izw8nLVr19KhQweCgoLo2rUrTZs2ZdiwYSxfvpy6devy0ksvceHCBWJjYwEoVqwY9erVo0KFCnh6elKqVCmWLl2a010UkXwqKyMhHgbuMsY8Z4wJSko0xgQZY0YBLXAsVCkiIiIiIjkkMTGR+++/H29vb6ZMmZKpYypXrkzx4sXx9PSkbt26PP7443zxxReAY9Ht6dOn88gjj1CsWDGOHj1K5cqVKVmyJABjxoxh/fr1/PXXX8TFxTFq1CiaNGniClKIiGRFukEIY8yu5A/gaxyr/o0Cjhpj/jHG/AMcBZ7DMariq/TqExERERGRK2OtpU+fPhw6dIg5c+bg5eV1WfUYY9ymYHTs2JGtW7dy7NgxRo8eTXR0NLfeeisAmzZtonPnzpQsWZICBQrQs2dPjh8/rnUhJNdltEMMwA8//EDFihUpVKgQgwcPZt++fW7H9u7dm4CAACIiIpg0aZJb3bGxsQwcOJDQ0FACAwNp0KCBK+/ll1+matWq+Pv7U7ZsWV5++eWc72w+ltFIiIPAgRSP7cBKYJXz5+3On1c6fz6Yk40VEREREbmeDRgwgO3btzN//vxUW4afP3+euLg4wLFl54ULF1yBhrlz53L8+HGstaxbt47XX3+dtm3buo7duHEjFy9e5MiRI/Tr1482bdq4pnnceuutfP755xw6dIjExERmzpxJfHw85cqVy6Veizgk3yHm5MmTjBs3jnvvvZfo6GiOHj1K+/btGTt2LDExMVSoUIHOnTu7jo2KiuKPP/5g3759LFu2jAkTJrBw4UJXfr9+/YiJiWH79u3ExMTw6quvuvKstcyYMYPjx4+zcOFCpkyZwieffJKrfc9P0l0TwlrbKBfbISIiIiIiGdi3bx/vvPMOBQsWJCIiwpX+zjvv0K1bNypUqOD65rd58+aAY2eLyMhIPvnkE3r37s358+cpWbIkw4YNo0ePHq46Hn/8cTZv3oyXlxedOnVy+5Z42LBhHD58mJtvvpmzZ89Srlw55syZQ1BQUO50XMQpaYeYJMl3iDl27BhVqlRxbVHbo0cP2rdvz44dO1xTjqZNm0ZwcDDBwcE8+OCDTJs2jRYtWrBjxw7mzZvH/v37CQhw7LVQq9a/yyEOHTrU9XOFChVo27Ytq1evpkuXLrnT8XwmKwtTZsgYUwToYq19M7vqFBERERG5bkUFur0sA9hRaWxG98dAiBpIdE9Ivlnd8gqjiZxWA4DZFYAK4Jhd/TfEjISoka6yPzYFmnoAF4FP4OVPIOokAD4+Prz55pu8+aY+5svVJfkOMW+//TY1atRw5fn6+nLjjTeybds2wsPD+fvvv93ya9Sowddffw3AunXrKFOmDKNGjWLmzJkUK1aMqKgoOnTokOqc1lpWrVrFQw89lOP9y6+ysjBlKsYYb2NMR2PMXBxTMV7PwrG3GmNeN8ZsMcacMcYcNMZ8Y4ypnUbZAGPMFOc6FOeMMWuMMc3SqfcmY8w8Y8wp52OuMebGdMq2NMasddb5j7M9fmmUM8aYwcaYP4wx553rZDxmjDGZ7a+IiIiIiIhkj5Q7xJw5c4bAQPfAXWBgIKdPn+bMmTOu1ynzAPbv38/WrVsJDAzk4MGDTJkyhR49erB9+/ZU542KiiIxMZFevXrlYO/yt8sKQhhj6htjpgL/AJ8CtwDvAS2zUM0woDOO9SQGA68BlYC1xpi7kp3LAPOBPsD7wCBn1gJjTMMU7SqOY42Km4EoYDSOrUNXGmPCUpRtBnyDI9w7CPgQ6Ad8mUZbxwCTgDU4dglZD0wGnslCf0VEREREROQKpbVDjJ+fH6dOnXIrd+rUKfz9/fHz83O9TpkHjlETXl5ejBgxAm9vbxo2bEjjxo1ZtGiRW31TpkxhxowZfPvttxQsWDAnu5ivZXo6hjHmJuB+oBuO0WAngEDgscucgjEJuM9aeyHZOd4HfgfGAQucye2BBkAva+00Z7npwFbgFSD5yInhQDBQ1Vq7y1n2W2fZYcCTKc6/G2hsrT3vLLsHeNcY08pa+40zrTgwFJhure3pPPY9Y4wFnjXGTLXWHrmM/ouIiIiIiEgWJN8hZsGCBa4dYqpUqcL06dNd5c6dO8eePXuoUqUKwcHBFCtWjM2bN9OsmWNA/ebNm6lSpQoA1atXT3WelIPeP/jgA8aPH8/KlStd29fK5clwJIQxJtQY84gxZi2O3S8eAZYCzYD/AAb4+3JObK39KXkAwpl2DFgOVE6WfC+OgMdHycrF4RgVUSvFVItOwKKkAISz7A7gBxyjLpL6VQmoCrybFIBwmgGcSV4WaAt4Ayk3YX4T8AXaXLq3IiIiIiIicqXS2yGmXbt2bN26lTlz5hAXF8eMGTOoXr26a5eXBx54gHHjxnH8+HF27NjBu+++S8+ePQFo0KABpUuX5sUXXyQhIYHVq1ezbNky1wKvs2bN4plnnmHx4sXccMMNud7n/OZS0zEOAC8B+4COQLi1tq+1dimOaQw5oThwLNnrmsCv1tqEFOXWJcvHGFMCCE+WnrJsyWRTMmqmqAMAZ1BkU7L8pLLxwK8p6twIJKYoKyIiIjlkypQp1K5dm4IFC7o+OILjw6Gfn5/rUahQIYwxbNy4EXBsW9i/f3/Cw8MJCQmhdevWHDhwIFX9f/zxBz4+PnTv3t0t/ciRI9x3330EBgYSHBxMt27dcrSfIiKStqQdYjZt2kRERITr//1Zs2YRFhbGnDlzePbZZwkODmb79u1u22iOHj2aG2+8kTJlytCwYUOeeuopWrRoAYCXlxdz585lwYIFBAYG8uCDDzJjxgxXAGPEiBEcO3aMW2+91XXO/v3758l7kB+YpL2D08w0JhHHgpOzgI+ttZuT5d0I/AF0tNamtY5C1htjTH1gBfCqtfYJZ9oZYK61tluKspWBbcAga+1k54KW64F+1tp3U5QdiGPkws3W2s3GmCeBl4GbrLV/pCj7GdDMWhvsfP0NcIu1tkQa7T0MrLbWtkunP/1wrDNBeHh4rWt5L9ktB07m6fmrefx5RcefKVgcv/MHL7+CYjdf0flF8tKZM2dccyFFrmUrV67Ew8OD9evXc/78eZ5++uk0yy1cuJCZM2fy0UcfcfbsWebPn8+SJUt4+eWX8fPzY+LEicTFxTFmzBi345566inOnz9PeHg4zz77rCv9scceo0KFCvTo0QMfHx/+/PNPypcvn6N9FQHg701XdLg+/8g1Tdf/Na1x48YbrbWpNp2AS68JUQvHOhAPAE8aY3bgmBbxcfY2EYwxxYDZwP9wLASZxBc4n8Yhccnykz9nR1nfZK/TO39aZd1Ya6cCUwFq165tGzVqlF7Rq17Pp7/N0/NH+4y6ouOXVxhNo51XUEfXvA3CiFyJ5cuXcy3//yOSJOk6HjFiBPv370/3uh49ejT9+vWjcePGLF++HA8PDzp06ED79u0Bx4rqQ4YMcTv+k08+oWzZslSuXJndu3e78hYtWsSpU6f45JNP8PT0zMHeiaQhqu0VHa7PP3JN0/Wfb2U4HcNa+6u1dghQAmgFbAZGAHuBrwFLBjfhmWWMCcSxEKUf0Npam/xf/ByQ1tKjPsnykz9nR9lzyV6nd/60yoqIiEge2rdvHytXruSBBx5wpfXp04fVq1dz8OBBYmNjmTVrFi1b/ruh16lTp3juueeYNGlSqvrWrFnjGgVRpEgRbr31VlasWJErfREREcmPMrVFp7U20Vr7nbX2PhzrLvQBDuEIQkw3xqw1xjxjjKmW1QYYYwrh2CqzAtDKWrslRZG/cawTkVIx5/PBZOXIprLJx+38DRQ1xrh9/WGM8QaKpCgrIiIieWjGjBnUr1+fsmXLutLKly9PqVKlKFGiBAEBAWzfvp3nnnvOlT9y5Ej69OmT5mrn+/fvZ9GiRTRu3Jh//vmHJ554grZt23L06NFc6Y+IiEh+k6kgRHLW2jPW2mnW2qY4tup8FiiEY1vNTVmpy3kj/yXwf0Ana+2PaRT7BbjZGJNy6shtzudfne06ABwGbk2jjtuA/cm20vzF+exW1tmem5PlJ5UtANySos7aON6/XxARyQXpLcoHEBsby8CBAwkNDSUwMJAGDRq48oYNG+a2aJ+3tzfVqrnHjCdPnkzZsmUpXLgwlSpVYtcuxyZDy5Yto1q1agQFBVGkSBHatWuX5oJ+IleLGTNm0KNHD7e0hx9+mPPnz3Ps2DHOnj1L+/btXSMhNm3axJIlSxg8eHCa9fn6+hIZGUmfPn3w8vKiS5culCpVitWrV+d4X0RERPKjLAchkrPWHrDWvmStrYZj/YjXMnusc2TBxzi2+3zAWpveogNfAEGAa6lqY4wP0BvHrhm7U5S90xhTPlnZikAT4PNk7d4O/A48aIxJPtXiARxTQj5PljYPx+4Yj6Ro10Aca0LMv1RfRUSyQ/HixRkxYgS9e/dOldevXz9iYmLYvn07MTExvPrqq668l156iTNnzrgedevWpVOnTq789957j/fff59vv/2WM2fO8M033xAaGgpA5cqV+f777zlx4gQHDx6kfPnyDBgwIOc7K3IZkqZcdOzY0S1906ZN9OzZk5CQEAoWLMijjz7KunXrOHr0KMuXLyc6OprSpUsTERHBxIkTmTNnDjVrOja/ql69eqq94lO+FhERkcy71MKUmWat/ZXU21hmZCLQAVgMeBpjuqfI/8paexaYA/wIvG2MKQf8BfQEInEEMJJ7AegE/GCMeRUwwBAcIyReSlH2CeBbYKkxZrqzviHADyQLLFhrDxhjXgaeMcZ44Ni9ozHQDXjOWns4C30WEblsSYvqbdiwgf3797vSd+zYwbx589i/fz8BAQEA1KpVK806oqOjWbVqFdOmTQMgMTGR0aNHM23aNCpXrgzAjTfe6CofHh7udrynpye7d+9GJC8kJCSQkJDAxYsXuXjxInFxcRQoUIACBRwfZ6ZPn06HDh3w9/d3O+7WW29lxowZNGrUiEKFCvHWW29RvHhxQkND6devH126dHGVnThxItHR0bz99tuAY9/5J598kunTp9O9e3e++uor9u/fz+233557HRcREclH0h0JYYyZaIwJTy8/g+MijDETM1E0aXpDM2BmGo8wcKxHgWNRzA+BB3GMtvAE7rbWLkteoXNKRn3gN2A0EIVjukQDa+2hFGUXAq0Bb+B1HOtcvAe0s6n3LR0JPAnUBd7CMb1jMI4pKCIieWrdunWUKVOGUaNGERoaSrVq1ZgzZ06aZZPmy0dGRgKO+e779+9n69atlCpVirJlyzJq1CgSExNdx/zvf/8jKCgIX19fJk6cyNChQ3OjWyKpjBs3Dl9fX8aPH89HH32Er68v48Y5/hTHxcXx2WefpZqKAY7Ago+PD+XLlycsLIwFCxbw1VdfAVCoUCEiIiJcDz8/P3x8fAgLCwMgJCSEefPmMXHiRAIDAxk/fjxz5851jRYSERGRrMloJERDYKAx5mscW2f+YK2NTaugMcYfaAp0AdrgCAJkyFrbKLONdO6WMdD5uFTZnTiCFpmpdwGOXTkuVS4ReMX5EBG5qiQFETp06MDBgwf5+eefufvuu6lcuTKVKlVyKztjxgxGjBjhdiw4tiHcsmULJ06c4M4776RkyZI8+OCDAJQuXZoTJ04QExPDu+++S8WKFXOvcyJRgf/+CESNCkhR4FWIehUf4MQgYFV7WJUsu8Joiixvy6zygGuy5hZY0CzNTwBRAOWSnTfqJPXr12fLlpTrZouIiMjlSHckhLX2VhxrJNwIzAVOGmO2GmPmGWOmG2NmGGPmG2N+B47jmDYRCXS31t6WXr0iIpK9fH198fLyYsSIEXh7e9OwYUMaN27MokWL3Mr9+OOP/PPPP27z5X19HbssDx06lKCgICIjI3nooYdYsCD13VlISAg9evSgbdu2JCQk5GynRERERCRfynBNCGvtF8AXxpiqQHsc0xFqAEljEI8C23GMlPg6je01RUQkh1WvXj1VWloL502fPp327dvj5+fnSqtQoQLe3t5u5TNadC8hIYHDhw9z6tQpQkJCrrDlIiIiInK9ydTuGNbardbaMdbaFtbaMtbaws5HGWfaWAUgRERyVkJCAnFxcW6L8iUkJNCgQQNKly7Niy++SEJCAqtXr2bZsmU0b97cdey5c+f47LPPUm3tWahQITp37syECRM4ffo0+/fvZ+rUqbRq5ZjV9uWXX7Jz504SExM5cuQIQ4YM4ZZbblEAQkREREQuS7btjiEiIjnEOTd93PI4Rq+44Er+6KOPGNXQm6hGPsy98yJ9p45m/NjnKBPowYy7ClLxE+fMuAqj+br7XQSZOBqvuAdWuo90mFLC0u+XcxQPDSDIx/BgTW96/28wRA3hwNoLPLEjgsOHD+Pv70+jRo1cC/qJiIiIiGSVghAiIteIqEY+RDXySTOvSlFPfu5TON1ju1bzoms1rzTzAgoaPulYKM28R2/z5tHv/sx6Y0VERERE0pCp6RgiIiIiIiIiIldKQQgRERERERERyRUKQoiIiIiIiIhIrlAQQkRERERERERyhYIQIiIiIiIiIpIrMh2EMMYEGWP2GmP+k5MNEhERkavTlClTqF27NgULFqRnz56u9DVr1tCsWTNCQkIICwujU6dO/P333678li1b4ufn53p4e3tTrVo1AP73v/+55fn5+WGM4ZVXXgHAWsvzK89T+tXTBLx4ii5fxHLqvM3VfouIiEj2yTAIYYxJvp+bJxAJ+DrzFJQQkevK5d6ARUVF4eXl5XaTtXfvXgB27dpF27ZtCQsLIyQkhObNm7Nz5840z3/HjLOY0adISNQNmOSN4sWLM2LECHr37u2Wfvz4cfr160d0dDT79u3D39+fXr16ufK/++47zpw543rUrVuXTp06AVC6dGm3vC1btuDh4UGHDh0AmLE5npm/xbO6d2EOPuHPuQR49Lu43Ou0SDKX+3fg1Vdf5YYbbiAgIIDixYszePBgEhISXPk//fQTderUwd/fn+rVq/Pjjz+6nffjLfGUee00hV84xT2fxBJzTn8HJG/kxGchgH79+lGhQgU8PDyYNm2a2zn7f3MOvxdOuR4Fx53C/8VTOd1VyUGXGglx2hjzkzHmVaAjYJ0PSBGUEBHJ7y73Bgygc+fObjdaN9xwAwAnTpygTZs27Ny5k0OHDlGnTh3atm2b6tyzfosn/mLO9U0kM9q3b88999xDkSJF3NJbtmxJp06dCAgIoFChQjzyyCOsXr06zTqio6NZtWoVDzzwQJr5M2bMoEGDBkRGRgIwf1cCfW7xolSgB37ehmG3e/Pp1nhi43UTJrnvcv8OtGnThl9++YVTp06xdetWNm/ezOuvvw5ATEwMrVu35qmnnuLEiRMMHTqU1q1bc/z4cQC2Hb7IQ9+cY2Y7Xw496U8hLxj47bnc67RIMjnxWQigRo0avPXWW9SsWTPVOf/bypczzwS4Hl2retGpsleqcnLtuFQQoiuwCqgFTHKmfWiMeR/ogntQQiTfSy/6e+HCBTp27EhkZCTGGJYvX+523Pnz5+nfvz/h4eGEhITQunVrDhw44Mrv3r07xYoVIyAggJtuuon33nvP7fj33nuPcuXK4efnR4sWLTh48GBOdlPSkR03YCnVqVOHPn36EBISgpeXF4MHD2bnzp0cO3bMVeZknGX0ivNMaFYwW/sjklNWrlxJlSpV0sybMWMG9evXdwUZkrPWMmPGDHr06OGe7lYGzl+EP44lZmOLRTLncv8O3HjjjQQFBQGO69zDw4Pdu3cDjlEQERERdOrUCU9PT7p3705YWBhffvklALO2xNP6pgI0KFMAP2/D2MY+fLk9gdOaliR5ICc+CwE8/PDD3HHHHfj4+GRY7uwFy5zt8fSooSDEtSzDIIS19itr7TBrbQPgBsAAS4GiwPPOYtONMR8bYx4xxqQOXYnkI+lFfwHq1avHRx99RERERKq8yZMn8/PPP/Pbb79x8OBBgoODefTRR135w4cPJzo6mlOnTjFv3jxGjBjBxo0bAVi+fDnPPPMMc+fOJSYmhrJly9K1a9ec66RcsbRuwObPn09ISAhVqlTh7bffzvDYiIgItz/uz/wQx4DaXkT4aS1hufr99ttvjBkzhpdffjnN/BkzZrgFcZP78ccfOXToEB07dnSltShXgPd+iSf6RCIn4ywvrb4AoJEQclVL6+/Axx9/TEBAAKGhoWzevJmHHnrIlWet+/VsrWXr1q0AbDuSSI1wT1fejSEeeHvCLgXi5Cp2JZ+FMjJnezxhhQwNynheurBctS61JkQzY0yA82XSxLWPrLWtgZtwBCW+cz4/BazPqYaKXA3Si/56e3szaNAg6tWrh6dn6v8U//zzT5o3b054eDg+Pj507tyZbdu2ufKrVKlCwYKOb7mNMRhj2LNnDwDffPMNnTp1okqVKnh7ezNy5EhWrlzpyperS1o3YPfeey/bt2/nyJEjvPvuu4wZM4bZs2enOnb//v08/PDDTJo0yZW2YcMGVv91kUdv886V9otcid27d9OyZUsmT55M/fr1U+X/+OOP/PPPP25BhuSmT59Ohw4d8PPzc6X1vsWLrlUL0GjaWaq8dYbGkY7/Y0sGKCgnV6f0AnH33Xcfp06dYteuXa7RkQD/+c9/OHjwILNnzyY+Pp7p06ezZ88eYmNjAThzwRLoY9zqCvQxnL6gQJxcna7ks9ClTN8czwM1vDDGXLqwXLUu9Rd8IRBjjNkGvIFjRGRRZ17S7ORPrbVdrbVlgFI500yRa1ufPn1YvXo1Bw8eJDY2llmzZtGyZUu3MgMHDqRQoUJUrFiRYsWKcdddd7nykn9DkvRz0jckcvVI7wascuXKFC9eHE9PT+rWrcvjjz/OF1984XbskSNHuPPOOxk4cKBrpEtiYiIDBw5kcgsfCnjoj61c3fbt20fTpk0ZOXIk999/f5plpk+fTvv27d2CDEnOnTvH559/nmoqhocxjG7sQ/Qgf/YP8adKUU9K+BtKBOh3Qq4+lwrEAZQvX54qVaowcOBAAIoUKcLcuXOZNGkS4eHhLFy4kKZNm1KyZEkA/LxNqh1hTp23+Hvrd0CuPlfyWehS/ncykeXRF3mghr6YudZdKggRAtwFfAwE4BjxMMsY8xfwXxxBCdfYc2utJqqLpKF8+fKUKlWKEiVKEBAQwPbt23nuuefcyrz11lucPn2aVatW0b59e9fIiBYtWvDZZ5/x22+/ce7cOcaMGYMxxvUNiVwdMnMDlsQY4xZYOn78OHfeeSdt2rTh2WefdaWfOnWKDRs20PmLc0RMPM2t754FoOSkM6zal5CqXpGclpCQQFxcHBcvXuTixYvExcWRkJDAgQMHaNKkCY888gj9+/dP89hz587x2WefpTsV46uvviI4OJjGjRu7pcecs+yJScRay+9HLjLk+ziea1gQD30LJleZrPwdSEhIcBvR2LBhQ9avX09MTAwzZ85kx44d1KlTB4AqYR5sPvTvysR7jydyPgFuKqLRQHJ1uZLPQpkxc3M8t5fy5IZgXfvXugIZZVprTwKLgEXGmFDgMPCI87hmOIISM40xrwNrgNXW2hdztski156HH36Y8+fPc+zYMQoXLsyECRNo2bIla9eudSvn6enpWlvi7bff5rHHHqNp06aMHj2aDh06cOrUKQYNGoS/v7/rGxLJPQkJCSQkJLjdgBUoUIBDhw5leAM2d+5cGjRoQFBQEOvXr+f111/nhRdeAByBhubNm3P77bczfvx4t+MCAwMdi5BOLA/AXyctdd47y8Z+hQkrrBswyR2RT3/r+vnEj7M4ufrf4bMfffQRgbd3BQwn9+5l6DMjGfrMSFd+6SH/fst19vcVnKUgvb6PxSz6t84khz6dSMHi/0fZ4Qvc0hfFJtJ69jn+OplIWGHD47d506+WvgWTvHG5fwfee+892rRpQ9GiRfn999958cUXad68uSv/119/pWrVqpw7d47nnnuOUqVKOfJ/hm7VvPjP+2dZtS+BmsU8eW7ZedpXKoB/Qf0dkNyXE5+FwLHIe2KiI+AcHx9PXFwc3ta6BZxn/BbPsNv1/39+YDIbgTLGFAGOAE2ttUuTBSX64Vgv4nagrrU27eWwr3O1a9e2GzZsyOtmXLbkH0LzQrTPfVd0/PIKo2m0c9TlVxB10u3liBEj2L9/f6p9jAFKlizJRx99RKNGjVxpVatW5fnnn3dtvXjixAmCg4M5cuQIoaGhqero27cvhQsXZvLkyanydu3axS233ML+/fsJDg6+/D5JpiVd/ylvwIB/b8BWf4zxcl/ROekG7Mi8CcT9+Sv2Yjye/qH433IXAbXbAHBmyw8cW/AqxqsgjriuQ/G+b1EgwDH7Len6jz6RSNnJZ4gf6Z+l6RnZff3L9UX//+v6l39FRUUxevRot7RRo0ZhjCEqKorChQu75Z05cwaAXr16sWDBAs6cOUNYWBidOnVi7Nixrp0AunbtyoIFjgBcixYteOONNyhatChEBQLw8ZZ4nl4Sx7FzlqY3FODDtr6E+F7674Cuf7kSaf3/nxOfhQD++fhpzv/lPtV4WY9CNIp0fGf+818JNJ0Zyz9P+Gc6AKfrP28ZYzZaa2unlZfhSIgU4oEVwHHn66ToxV5r7VJg2mW3UOQakV70t0CBApw/f941rOzChQvExcVRsGBBjDHceuutzJgxg0aNGlGoUCHeeustihcvTmhoKIcPH2bp0qW0atUKX19flixZwuzZs12L9cTFxbF7926qVKnCX3/9Rb9+/Xj88ccVgMgDQfW6EVSvWzp56d8ohbUZmm6eX7U78Kt2R6bOHxnkgR0VcOmCIiKSLVLfhN1KmWHfuKVMi3M8p0x3Oz68I769OuLrTP8c+Dzqh38LlulO8IDuAKwF6kxyrPUe7byfu6+aF/dV05aEkvdy4rMQQMR941OlNUoWhP5PqQKcfUafgfKLTE+osdaestY2ttb+6kxKGZQQyffGjRuHr68v48eP56OPPsLX15dx48YBUKFCBXx9fTlw4ADNmzfH19eXffv2ATBx4kR8fHwoX748YWFhLFiwgK+++gpwzIl7++23KVmyJMHBwTz55JO89tprtGnjiA7HxcVx33334efnR506dfjPf/7D2LFj8+YNEBERERERuQJZGQnhxlp7Cmh8yYIi+UC16dUcP5SFqtOquuXNYQ5zps/Bf7Q/VXHPa72itSNUB3AnhN/p2I7rJCfps70PbHfm9YZSyTaXeZ3XeX36667XW37bkq39ERERERERyQtaWlREREREREREcoWCECIiIiIiIiKSKxSEEBEREREREZFcoSCEiIiIiIiIiOQKBSFEREREREREJFcoCCEiIiIiIiIiuUJBCBERERERERHJFQpCiIiIiIiIiEiuUBBCRERERERERHKFghAiIiIiIiIikisUhBARERERERGRXKEghIiIiIiIiIjkCgUhRERERERERCRXKAghIiIiIiIiIrlCQQgRERERERERyRUKQoiIiIiIiIhIrlAQQkRERERERERyhYIQIiIiIiIiIpIrFIQQERERERERkVyhIISIiIiIiIiI5AoFIUREREREREQkVygIISIiIiIiIiK5QkEIEREREREREckVCkKIiIiIiIiISK5QEEJEREREREREcoWCECIiIiIiIiKSKxSEEBERERGRSzp//jx9+vShTJky+Pv7c/PNN/Pdd9+58mNjYxk4cCChoaEEBgbSoEGDVHVcuHCBSpUqUbJkSbf0fv36UaFCBTw8PJg2bVpOd0XksmT0OxAdHY0xBj8/P9dj7NixrmOffPJJypcvj7+/PxUrVmTGjBludS9dupSaNWsSEBDADTfcwNSpU3O1b7lJQQgRERGRTMjow+eaNWto1qwZISEhhIWF0alTJ/7++2/XsSdOnKBHjx4ULVqUokWLEhUVleY5VqxYgTGGESNG5EaXRLIkISGBUqVKsWLFCk6ePMm4ceO49957iY6OBhyBhJiYGLZv305MTAyvvvpqqjpefvllwsLCUqXXqFGDt956i5o1a+Z0N0Qu26V+B8Dx//2ZM2c4c+YMI0eOdKUXLlyY+fPnc/LkSaZPn87jjz/OTz/9BEB8fDzt2rXjoYce4uTJk3z66acMGTKEzZs353YXc4WCECIikikZ3YBduHCBjh07EhkZiTGG5cuXux1rrWXYsGEUKVKEIkWKMGzYMKy1AOzatYu2bdsSFhZGSEgIzZs3Z+fOnbndPZFLyujD5/Hjx+nXrx/R0dHs27cPf39/evXq5Tp28ODBxMbGEh0dzbp165g5cyYffvihW/3x8fE8/vjj3HbbbbndNZFMKVy4MFFRUURGRuLh4UGrVq0oW7YsGzduZMeOHcybN4+pU6cSFhaGp6cntWrVcjv+zz//5KOPPmL48OGp6n744Ye544478PHxya3uiGRZRr8DlzJ69GgqVqyIh4cHt912G/Xr1+fnn38GICYmhlOnTnH//fdjjOHWW2+lUqVK/P777zndpTyhIISIiGTKpaL/9erV46OPPiIiIiLVsVOnTuXrr79m8+bN/Pbbb8yfP5933nkHcHxj0KZNG3bu3MmhQ4eoU6cObdu2zc2uiWRKRh8+W7ZsSadOnQgICKBQoUI88sgjrF692nXs/PnzGTp0KIUKFSIyMpI+ffrwwQcfuNX/yiuvcOedd1KxYsXc7prIZTl06BC7du2iSpUqrFu3jjJlyjBq1ChCQ0OpVq0ac+bMcSv/6KOP8sILL+Dr65tHLRbJXsl/B5KUKVOGkiVL0qtXL44ePZrmcefOnWP9+vWu48LDw+natSsffvghFy9e5Oeff2bfvn3Uq1cvV/qR2xSEEBGRTMnoBszb25tBgwZRr149PD09Ux07ffp0nnjiCUqWLEmJEiV44oknXHN+69SpQ58+fQgJCcHLy4vBgwezc+dOjh07lss9FMmatD58Jlm5cmWq9KTRP0k/b9261fV63759fPDBBzz33HM512CRbBQfH0+3bt3o0aMHFStWZP/+/WzdupXAwEAOHjzIlClT6NGjB9u3bwfgq6++4uLFi7Rr1y6PWy6SPVL+DoSGhrJ+/Xr27dvHxo0bOX36NN26dUvz2P79+1OjRg2aN2/uSuvatStjxoyhYMGC1K9fn+eff55SpUrlVndyVYG8boCIiFybMroBS2nbtm3UqFHD9bpGjRps27YtzbIrV64kIiKCIkWKZFtbRbJbyg+fyf3222+MGTOGuXPnutJatGjB+PHjmT59OocOHeKDDz4gNjbWlf/YY48xduxY/Pz8cq0PIpcrMTGR+++/H29vb6ZMmQKAr68vXl5ejBgxggIFCtCwYUMaN27MokWLKF26NEOHDmXBggV53HKR7JHW74Cfnx+1a9cGHCMbpkyZQrFixTh9+jT+/v6uY5966im2bt3KsmXLMMYAsGPHDrp06cKXX35Js2bN+OOPP2jVqhXFixfn7rvvzv0O5jCNhBARkSzL6AYsLWfOnCEwMND1OjAwkDNnzrh9Mwywf/9+Hn74YSZNmpTtbRbJLml9+Eyye/duWrZsyeTJk6lfv74r/fXXX8fX15fy5cvTtm1bunbt6todYP78+Zw+fZrOnTvnaj9ELoe1lj59+nDo0CHmzJmDl5cXANWrV09VNukG648//iA6Opr69esTERFB+/bt+fvvv4mIiHBb0E/kWpDe70BKSdd/YmKiK23UqFF89913LFq0iICAAFf61q1buemmm2jevDkeHh5UqFCBu+++2233mfxEQQgREcmSjG7A0uPn58epU6dcr0+dOoWfn5/rDzTAkSNHuPPOOxk4cCBdu3bN9naLZIeMPnzu27ePpk2bMnLkSO6//36340JCQpg1axb//PMP27ZtIzExkTp16gDwww8/sGHDBiIiIoiIiODTTz/ltdde09ooclUaMGAA27dvZ/78+W5rOzRo0IDSpUvz4osvkpCQwOrVq1m2bBnNmzenatWq/PXXX2zatIlNmzbx3nvvER4ezqZNm1zDzS9cuEBcXBzWWuLj44mLi3O7eRO5WqT3O7B27Vp27txJYmIix44d47HHHqNRo0auL2FefPFFPv74Y5YsWZJqtOctt9zCH3/8wdKlS7HWsmfPHr755ps0g3v5gaZjiIhIpiW/AVuwYEG60f+UqlSpwubNm103XZs3b3abxnH8+HHuvPNO2rRpw7PPPpsjbRfJDkkfPpcsWeL24fPAgQM0adKERx55hP79+6c6bs+ePQQFBREUFMSiRYuYOnUqK1asAGDs2LE8/fTTrrKPP/44xYsXd9vaTSQvVJteze31haMX2PXOLkwBQ2Dov6PbivcoTlDdIExvw4sfvMiocaPwDvUmvFc4ndZ2grXu9Z7ZfoYjcUdo9n0zV9reF/cSu9MxRemnn36iX79+LFu2jEaNGuVY/0QykvL6h4x/B/CAQ18cIuFUAp6+nvhV8SP83nBXPVuf2YopYCgRWcJ1XGirUIq2LgpASI8Q7nrgLuKPxePh68GQB4fQt2/fHO5l3lAQQkREMi29GzBwbOGZNL0i6RutggULYozhgQceYNKkSdx1110YY3jllVd49NFHAceoiObNm3P77bczfvz4XO+TSEaSfwjN6MPnhcMXOLz3MMNGDGPYiGGuvMrvVAbg5LqT/P3x31yMvUjB8IKE9wyny4YusCH1Ofcf2I/XOS+WzF/Clh5bcq5zIlnkHepN1WlV0833KeHDjSNvvGQ9fpX8qPiq+1S+G4bfkKqcAhBytbnU70DQ/wWlm5fRcQCBdQIJrPPv35aXeryU5fZdKxSEEBGRDCXdhF3qG7CdT+wk/lg8gGu155tevgnvMG+sj+Vo2aOUqVAGgOAGwUzxmcKb09/k+I/HObD+ABs2b+Dt99521VvuhXJ4F/HWTZhcNS714bPoPUXTzUv54TIjJR8smeW2iYiIXCsUhBARkUy51A1YhVcqpJtnjCGicwQRnSNS5QXXCya4XnC2tFFERERErm5amFJEREREREREcoWCEJlkjPE2xow1xvzPGBNnjPnNGKPl20VEREREREQySdMxMu994D7gLeA3oD3wsTHGw1o7K09bJiIiIiIiInIN0EiITDDG1AK6A2OttY9aa98F7gJ+BCYaYzK3R52IiIiIiIjIdUxBiMy5F7DAm0kJ1rEP3VtABNAgj9olIiIiIiIics1QECJzagLR1tojKdLXJcsXERERERERkQwYxxf6khFjzFbgpLX29hTphYCzwGvW2sFpHNcP6Od8WQHYmdNtlXSFAkfzuhEieUTXv1zPdP3L9UzXv1zPdP3nrTLW2rC0MrQwZeb4AofTSI9Llp+KtXYqMDWnGiWZZ4zZYK2tndftEMkLuv7leqbrX65nuv7leqbr/+ql6RiZcw4omEa6T7J8EREREREREcmAghCZ8zdQPI30Ys7ng7nYFhEREREREZFrkoIQmfMLUMYYk3JOy23J8uXqpmkxcj3T9S/XM13/cj3T9S/XM13/VyktTJkJxphbceyEMdpaG+VMM8AK4CaglLU2Pu9aKCIiIiIiInL108KUmWCtXW+M+RgYaYwJAX4D2gP1gR4KQIiIiIiIiIhcmkZCZJIxpiDwHPAAUBTYBYy31s7K04aJiIiIiIiIXCMUhBARERERERGRXKGFKUVEREREREQkV2hNCMlXjDGeQAOgJo5tVX2Bczi2Uf0FWGmtvZh3LRQRERERkZxmjCkBrAL6WWuX5HV75F8KQki+YYzpCkwEIgCTRhELHDLGPKW1POR6ZowpBZS11q7M67aI5DZjjC8QZq39X163RSQ7GWO8AB9r7elkaSFAOyAYWG+tXZFX7RPJbsaY4pcoUhKIBEomlbXWHszpdsmlaTqG5AvGmC7ALGAP0A0oBxQGPJ3P5YD7gd3ADGd5kevVA8CyvG6ESHYyxrQwxmwwxsQaY/4yxkwwxvinUbQ98Gdut08kJxljxgMngBPGmJ+NMaWMMZVxLKT+LjABWGqM+dS5zbxIfvDXJR4/4fgS8v1kaXIV0MKUki8YYzYD+621d2ei7AKghLW2Rs63TOTqY4x5FhhjrfXM67aIZAdjTC1gLXAUWI5jOt7tQDTQ2lr7e7Ky3YAZuv4lvzDG3A9MB74B/gf0xHHzBbAe+ATH9NQBOILQA6217+R+S0WylzEmETiDI9B2Ko0iwcBjwKfADgBr7ehca6CkS0EIyReMMeeAR6y172eibB9girXWN+dbJpI7jDHPZaF4Q6CRbsIkvzDGzAcqArdZa2OcafWB2UAh4G5r7c/OdAUhJF8xxqwB/rHW3uN83Rt4D5hmre2douyPOD7/357rDRXJZs7/598EigLDrbUfpsgvg2Pk2z3W2nl50ERJh9aEkPziMFAtk2WrO8uL5CdROIYcZnaYrSLQkp/UBF5NCkAAWGtXGWNuBRYAi40xHa21C/OshSI55yZgRrLXS53P36dRdh7wTI63SCQXOP+fvwXHaIdXjTH9gcestWvzuGlyCVoTQvKLGcDDxpiRxpgiaRUwxhRxfls8EPc/1iL5wVFgEVAqE4+JedRGkZwSABxPmWit/RvHyJ9fgbnGmHtzu2EiucAbOJ/sddLClEfSKHsM8MnxFonkEmvtRWvtq0AlHGu/rTbGTDPGhOdx0yQDGgkh+cUYHKvfjgZGGWOigb9x/FEuiGN+cBkcgbePneVF8pP1QDVr7YFLFTTGnMyF9ojkpj+Bm9PKsNaeMsbcCXyFYwHjH3KxXSK54R8cuwAkiQVeAfalUbY0jqC1SL7iDDp3M8ZMBabgWJT1AzTy86qkkRCSL1hr46219wO34vjDuxcIwhGYCMKxa8ZEoI61tru1Nj5vWiqSYzbg2IIqIhNlT+BYvEwkv1gOdDTGpPnlirX2HNAamAvcmYvtEskNG4D/S3phrT1nrX3KWrsnjbINgd9yrWUiucy5De3NOL5w7E3mp6lKLtLClCIi+YAxpjAQChxUkE2uN8aY2sAw4BVr7ZoMynngCFTfbK1tnFvtE8lJxpiKQClr7eJLlAsD3gFmW2s/z5XGieQhY0wAjh0yDjuD0XKVUBBCRERERERERHKFpmOIiIiIiIiISK5QEEJEREREREREcoWCECIiIiIiIiKSKxSEEBERkSwxxthMPqJysU1Rxpg2uXW+K2WM6WmMeSyv2yEiIpLbtDCliIiIZIkxpnuKpH7A7UCPFOm/WWtzZTtAY4wF3rfW9s2N810pY8xyoKS1tlxet0VERCQ3pbmftoiIiEh6rLUfJX9tjGkK1E2ZnpIxprC19myONk5ERESuapqOISIiItnOOT3CGmOqGWM+MMYcBfYny7/DGLPUGHPaGHPWGLPCGFM/RR1ljDFTjDHbnWVOGWOWGGPqJisT6RwFAdAn2VSQaSnaUdkY864x5pgx5oQx5h1jjLcxxs/58xFjzBljzHRjjG8a/elkjFljjIl1tuNbY0y1FGWmGWMSjDHhxpjPnOWOG2PeS16nMSYaaAjcmKy90Vf8pouIiFwDNBJCREREctJsHMGHUYAfgDHmXmf6CmAkYICewA/GmKbW2pXOY28FGgNfAvuAUKAPsNQYU9tauxU4AtwPzASWA+87j92Toh0fAdHACKAejikkZ4GqwBngORxTSh4ADgDPJB1ojHkSeBn4ynkeP2AAsNrZjl3JzmOAhcDvwDBnH/o42zncWWYQ8CIQDDzpTDuT0ZsoIiKSX2hNCBEREbkizlEH3a21BZKlReEIPMwD7rHODxzGmMLA/4CF1tpuycr7AluAQ9ba25PSrLXnUpwrBNgBzLXWPpgsPc01IZK1Y5a1tnuy9LU4AgQfWWsfSJFexlob4XxdCtgLTLDWPpusXDiwHfguqR/O96EH8JK19ulkZb8GbrfWhiVLW47WhBARkeuQpmOIiIhITnrbun/j0QwIAT4yxoQmPYDCwBLg/4wxhQCSByCMMb7GmCI4PrusA2plsR3vpHj9M45RC++mkR6e1AagA46Ro7NTtPeis2yTNM71VorXK4BQY4x/FtssIiKS72g6hoiIiOSklNMibnI+L8jgmCJArDHGG8cohvuBUinK/JnFdvwvxesTl0gPBmL5t71b0qk3MY3X+1OkHXc+hwCnL9FOERGRfE1BCBEREclJ51K8ThqF2YfUAYAkR5zPk3Gs3fAmsBrHzXwijrUVbsxiOy5mMd04n5Pa2wo4n4nzWGttysBEyjpFRESuWwpCiIiISG7a7Xw+aq1dcomyXYAZ1trHkicaY8bkSMvSltTev6y1v2VjvVqUS0RErktaE0JERERy0/c4pjyMMMYUTJlpjAlL9jKRFJ9VnNt4/l8a9Z4FgrKtlf+aAyQAo40xqT43pWhvVuRUe0VERK5qGgkhIiIiucZae9oY0w/HFp1bjDGzgINACaChs1hj5/NcoIcx5gywCagE9AW2ASkXedwI3GmMGQz8DfxprV2bDe390xgzFJgErDPGfAkcBUoDLYCtOLYXzaqNwN3GmInOn89Ya+dfaXtFRESudgpCiIiISK6y1n5ujDkAPAM8DhQC/sGx68UHyYo+DsQB7YFeOBaH7AjcBzRKUe0jwNvA84AvMB244iCEs72vGmN2AU8AT+P4/HQQ+BH472VWOwmoiGNtjCeAfYCCECIiku8Z912zRERERERERERyhtaEEBEREREREZFcoSCEiIiIiIiIiOQKBSFEREREREREJFcoCCEiIiIiIiIiuUJBCBERERERERHJFQpCiIiIiIiIiEiuUBBCRERERERERHKFghAiIiIiIiIikisUhBARERERERGRXPH/AmGDHRSEooQAAAAASUVORK5CYII=\n"
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"_ = evaluator.get_distribution_by_threshold(eval_set,thresh=0.015)"
]
},
{
"cell_type": "markdown",
"id": "c08bb97c-4348-406b-8042-6406b33e4e0a",
"metadata": {},
"source": [
"These charts describe the distribution of assigned treatments among three different groups:\n",
"\n",
"- `Observed`: The actual treatments assigned to the observations composing the evaluated dataset. This distribution is not affected by the choice of the specific threshold.\n",
"- `Recommended`: The distribution of the recommendations of the the policy $\\pi(\\boldsymbol{x},q^{*}) = h_{q^{*}}(x)$ corresponding to the selected threshold.\n",
"- `Intersection`: The distribution of actions in the intersection set between the observed actions and the ones recommended by the model, i.e where the recommendation of the model $h_{q^{*}}(x)$ goes hand-in-hand with the observed treatment.\n",
"\n",
"The upper subplot describes the density distribution, and the lower describes the distribution in absolute quantities. Thus, the bars associated with the `Intersection` group, on the lower chart (absolute quantities) will always be lower (or equal)in height than the `Recommended` group. \n",
"As explained and demonstrated later in this tutorial, much of the evaluted performance measure relies on the statistics of the *Intersections* set. Therefore, it is important to verify that the distribution of assignments in the *Intersections* set is not significantly different from the \"hypothetical\" distribution of assignments (`Recommended`). If that is not the case, and the distributions are very different, we won't be able to \"project\" the performance we evaluated (based on the intersection set), and expect similar performance when the model will be deployed, and act on(assign treatments to) new instances."
]
},
{
"cell_type": "markdown",
"id": "ca7c1705-421a-4364-98b6-d68e16f5264f",
"metadata": {
"tags": []
},
"source": [
"## Visualize Evaluated Performance Using `Evaluator.visualize()`"
]
},
{
"cell_type": "markdown",
"id": "02f37ed1-5804-4edc-b71b-91bcea21948c",
"metadata": {},
"source": [
"Now, we can use the `evaluator` for visualizing the results of the evaluation, using the method `Evaluator.visualize()`. \n",
"\n",
"*Note*: A dedicated method, `Evaluator.eval_and_show()`, can be used for combining the steps of *evaluation* and *visualization* with a single call."
]
},
{
"cell_type": "markdown",
"id": "06bcb381-f054-42d6-9618-15e57db77ec2",
"metadata": {},
"source": [
"The `Evaluator` class provides a set of charts for the visualization of the evaluated performance, listed under:"
]
},
{
"cell_type": "code",
"execution_count": 24,
"id": "c36e6482-c6df-4ea6-9900-729f8eb33400",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": "['uplift',\n 'fractional_lift',\n 'gain',\n 'avg_response',\n 'acceptance_region',\n 'rejection_region',\n 'agreements',\n 'score_distribution']"
},
"execution_count": 24,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"list(evaluator.visualization_methods().keys())"
]
},
{
"cell_type": "markdown",
"id": "58ef70cd-a0f7-422b-9c1e-ddbe8b616b33",
"metadata": {},
"source": [
"All the charts listed above, except for `score_distribution`, share the same *x-axis*. As explained earlier, the performance of the uplift model is a function of the exposure rate, expressed by $q=q^{*} \\in (0,1)$, which denotes the upper $q^{th}$ quantile of scores according to which observations (with scores in this range) will be exposed to the treatments recommended by the model. \n",
"Accordingly, each signal/measure depcited in these charts is a function of the upper $q^{th}$ quantile, and as we move from the left side of the chart towards the right, the *acceptance-region* gets wider, observations with lower scores enter the *acceptance-region*, and the performance, or the values of the specific metric depicted, might change. Of course, as the *acceptance-region* grows wider, and $q$ grows bigger, the *rejection-region* shrinks accordingly (as it complements the acceptance-region). \n",
"As an auxiliary notation, we denote the observed treatment assignment for the $i^{th}$ observation as $t^{(i)}$."
]
},
{
"cell_type": "markdown",
"id": "71907d86-d9d6-45a2-8338-680587d9e4b4",
"metadata": {},
"source": [
"The created charts yield different visualizations, dependening on:\n",
"\n",
"- whether the evaluated set is associated with multiple treatments or just a single binary treatment.\n",
"- whether the associated response is represented by a binary variable or a contrinuous variable.\n",
"- whether they are created for a single `EvalSet` object, or a collection of such (as will be demonstrated later in this tutorial)."
]
},
{
"cell_type": "markdown",
"id": "c57a83a0-a685-41e9-ade5-51a32e41afba",
"metadata": {},
"source": [
"Moreover, in the case of calling `Evaluator.visualize()` with a single `EvalSet` object, the user can set the keyword argument `show_random` and `num_random_rep` for benchmarking the depicted measure/metric relative to the average of the same metric over a collection of corresponding `EvalSet` objects that were randomly scored."
]
},
{
"cell_type": "markdown",
"id": "e39e936a-2bb4-48d9-971c-1148eb4c6853",
"metadata": {},
"source": [
"When calling `Evaluator.visualize()` all these charts will be provided, one after the other. However, the user can use the keyword argument `specify`, for *specifying* the list of charts desired. For explaining the content depicted in each chart, we'll use this option, to show each chart separately."
]
},
{
"cell_type": "markdown",
"id": "2af7b23b-73c1-4b15-82ec-348bd282bc3e",
"metadata": {},
"source": [
"Let us start with the first chart:"
]
},
{
"cell_type": "markdown",
"id": "d2606f40-111b-4234-ae81-3bc0bc79856b",
"metadata": {},
"source": [
""
]
},
{
"cell_type": "markdown",
"id": "b055d252-8c43-49db-9b56-6f010ca845b7",
"metadata": {},
"source": [
"### Uplift Curve "
]
},
{
"cell_type": "code",
"execution_count": 25,
"id": "172db35c-def1-442c-b64f-fb03052be345",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": "
",
"image/png": 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\n"
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"evaluator.visualize(eval_res,show_random=True,num_random_rep=4,specify=['uplift'])"
]
},
{
"cell_type": "markdown",
"id": "400ff969-2a68-42a5-be16-ff454a2c81a1",
"metadata": {},
"source": [
"This chart describes several curves, but the primary one is the one labeled as `Intersection Uplift`, quantifying the **differnce**, within the *acceptance region* defined according to $q^{*}$, between :\n",
"\n",
"- the **average response** for the group of observations for which the observed actions intersect with the treatments recommended by the model, i.e. $\\mathop{\\mathbb{E}} \\left[ y_i | \\hat{u}_i \\geq Thresh(q^{*},\\boldsymbol{\\hat{u}}) \\hspace{0.2cm},\\hspace{0.2cm} h_{q^{*}}(x^{(i)}) = t^{(i)}\\right]$, which is estimated as: \n",
"$$\n",
"\\begin{align}\n",
"\\frac{\\sum_{i} y_i \\mathbb{1} \\left[\\hat{u}_i > Thresh(q^{*},\\boldsymbol{\\hat{u}}) \\right] \\cdot \\mathbb{1} \\left[h_{q^{*}}(x^{(i)}) = t^{(i)} \\right]}{\\sum_{i} \\mathbb{1} \\left[\\hat{u}_i \\geq Thresh(q^{*},\\boldsymbol{\\hat{u}}) \\right] \\cdot \\mathbb{1} \\left[h_{q^{*}}(x^{(i)}) = t^{(i)} \\right]}\n",
"\\end{align}\n",
"$$\n",
"\n",
"- the **average response** for the group of observations which were assigned with the neutral action $t_0$, i.e. $\\mathop{\\mathbb{E}} \\left[ y_i | \\hat{u}_i \\geq Thresh(q^{*},\\boldsymbol{\\hat{u}}) \\hspace{0.2cm},\\hspace{0.2cm} t^{(i)} = t_0 \\right]$, which is estimated as: \n",
"$$\n",
"\\begin{align}\n",
"\\frac{\\sum_{i} y_i \\mathbb{1} \\left[\\hat{u}_i \\geq Thresh(q^{*},\\boldsymbol{\\hat{u}}) \\right] \\cdot \\mathbb{1} \\left[t^{(i)} = t_0 \\right]}{\\sum_{i} \\mathbb{1} \\left[\\hat{u}_i \\geq Thresh(q^{*},\\boldsymbol{\\hat{u}}) \\right] \\cdot \\mathbb{1} \\left[t^{(i)} = t_0 \\right]}\n",
"\\end{align}\n",
"$$"
]
},
{
"cell_type": "markdown",
"id": "c1120549-c7b8-463c-9afe-2334ec09f66f",
"metadata": {},
"source": [
"As long as this uplift curve is positive, it implies higher average response for the intersection group, compared to the untreated group, within the acceptance region. The left edge on the curve describes the difference when a very small fraction of the score distribution is exposed to the decisions of the model, and the right edge describes a scenario in which the entire population is exposed to the recommendation."
]
},
{
"cell_type": "markdown",
"id": "c3fc2eb8-d7a6-4643-b77b-0a1888dd9baa",
"metadata": {},
"source": [
"The label attached to the curve also indicates the area under the curve which is often used as an aggregate performance metric. The area under the curve is also color-filled (green will be the fill color for positive values, and red for negative ones)."
]
},
{
"cell_type": "markdown",
"id": "f0804858-b157-4c12-99f6-4fbb0b1aa49d",
"metadata": {},
"source": [
"The curve labeled as `Random` depicts the average uplift curve computed for `num_random_rep` randomly scored evaluation sets, and can be used as a benchmark for understanding whether the performance observed in our primary evaluated set is coincidential or not."
]
},
{
"cell_type": "markdown",
"id": "256e6c64-3a17-4fe1-83fd-edd672da63e9",
"metadata": {},
"source": [
"Although analyzing uplift models usually regards response statistics calculated *inside* the acceptance region, we also need to consider the perfromance of the uplift model in the *rejection region* - i.e. what are the implications of the policy $h_{q^{*}}$ intending to assign the neutral treatment $t_0$ for observations with $\\hat{u}_i < Thresh(q^{*},\\boldsymbol{\\hat{u}})$. \n",
"To answer that, the curve labeled as `UnexposedResponseDiff`, depicts for each $q^{*}$, the difference, in the rejection region between:\n",
"\n",
"- the **average response** for the untreated group of observations, i.e. $\\mathop{\\mathbb{E}} \\left[ y_i | \\hat{u}_i < Thresh(q^{*},\\boldsymbol{\\hat{u}}) \\hspace{0.2cm},\\hspace{0.2cm} t^{(i)} = t_0\\right]$, which is estimated by: $\\frac{\\sum_{i} y_i \\mathbb{1} \\left[\\hat{u}_i < Thresh(q^{*},\\boldsymbol{\\hat{u}}) \\right] \\cdot \\mathbb{1} \\left[t^{(i)} = t_0 \\right]}{\\sum_{i} \\mathbb{1} \\left[\\hat{u}_i < Thresh(q^{*},\\boldsymbol{\\hat{u}}) \\right] \\cdot \\mathbb{1} \\left[t^{(i)} = t_0 \\right]}$.\n",
"- the **average response** for the treated (with a non-neutral treatment) group of observations, i.e. $\\mathop{\\mathbb{E}} \\left[ y_i | \\hat{u}_i < Thresh(q^{*},\\boldsymbol{\\hat{u}}) \\hspace{0.2cm},\\hspace{0.2cm} t^{(i)} \\neq t_0\\right]$, which is estimated by: $\\frac{\\sum_{i} y_i \\mathbb{1} \\left[\\hat{u}_i < Thresh(q^{*},\\boldsymbol{\\hat{u}}) \\right] \\cdot \\mathbb{1} \\left[t^{(i)} \\neq t_0 \\right]}{\\sum_{i} \\mathbb{1} \\left[\\hat{u}_i < Thresh(q^{*},\\boldsymbol{\\hat{u}}) \\right] \\cdot \\mathbb{1} \\left[t^{(i)} \\neq t_0 \\right]}$. \n",
"\n",
"Accordingly, as the values of `UnexposedResponseDiff`, for a certain $q^{*}$, are positive it implies the associated average response for the untreated group is higher than the treated one, when considering only observations with scores lower than $Thresh(q^{*},\\boldsymbol{\\hat{u}})$. But, when `UnexposedResponseDiff < 0`, it means that even among the lower uplift scores, the average response is higher for the treated instances, and that the model will \"*lose*\", w.r.t response statistics in this region, by abstaining from treating instances in this region."
]
},
{
"cell_type": "markdown",
"id": "f4ab58e1-9825-4d33-8c58-d64fe31e33e2",
"metadata": {},
"source": [
"The dashed black line in this chart, corresponds to the *right y-axis*, and it quantifies the fraction of the treated observations ($t^{(i)} \\neq t_0$) in general, that can be found inside the acceptance region, for each $q^{*}$. Thus, it must always start from zero (where the acceptance region width is negligible), to one (where the acceptance region is spread over the entire distribution of scores). When this line goes up, from zero to one, in a linear fashion, it implies that the uplift scores for the treated group, is distributed similar to the entire population. On the other hand, if this line goes up in a non-linear fashion, it implies that the distribution of scores associated with the treated group is different - e.g. if uplift scores for treated instances are higher (in general) than the scores of the non-treated ones, it might indicate a leakage of information related to the treatment assignment into the model, which should output the scores regardless of the observed treatment that was assigned. In addition, it might indicate that the assignment of treatments during the controlled randomized experiment, is not necessarily completely random, and that observations with certain characteristics (expressed by their covariates) tend to get treated more often. This aspect of controlling our randomized data collection process is also crucial, for our ability to draw conclusions from the evaluation."
]
},
{
"cell_type": "markdown",
"id": "669196dc-6771-47a8-b722-2863314516d7",
"metadata": {},
"source": [
"As we can see in the chart above, there are two more curves that are worth inspecting: `Treated Uplift` and `Realized Vs Unrealized`. Both of these curves are relevant only in case the evaluated set is associated with multiple actions. When the treatment is binary (a single non-neutral action), both of these curves will be identical to the `Intersection Uplift` curve, and they will not be displayed because they do not add any information."
]
},
{
"cell_type": "markdown",
"id": "edd1c772-8074-44f0-8cd1-477d20a49010",
"metadata": {},
"source": [
"**`Treated Uplift`** describes a scenario in which all the non-netural actions, $t \\neq t_0$, are treated as a single treatment, and quanitifies the associated uplift, i.e. $\\mathop{\\mathbb{E}} \\left[ y_i | \\hat{u}_i \\geq Thresh(q^{*},\\boldsymbol{\\hat{u}}) \\hspace{0.2cm},\\hspace{0.2cm} t^{(i)} \\neq t_0\\right] - \\mathop{\\mathbb{E}} \\left[ y_i | \\hat{u}_i \\geq Thresh(q^{*},\\boldsymbol{\\hat{u}}) \\hspace{0.2cm},\\hspace{0.2cm} t^{(i)} = t_0\\right]$, which is estimated by: \n",
"$$\n",
"\\begin{align}\n",
"\\frac{\\sum_{i} y_i \\mathbb{1} \\left[\\hat{u}_i \\geq Thresh(q^{*},\\boldsymbol{\\hat{u}}) \\right] \\cdot \\mathbb{1} \\left[t^{(i)} \\neq t_0 \\right]}{\\sum_{i} \\mathbb{1} \\left[\\hat{u}_i \\geq Thresh(q^{*},\\boldsymbol{\\hat{u}}) \\right] \\cdot \\mathbb{1} \\left[t^{(i)} \\neq t_0 \\right]} - \\frac{\\sum_{i} y_i \\mathbb{1} \\left[\\hat{u}_i \\geq Thresh(q^{*},\\boldsymbol{\\hat{u}}) \\right] \\cdot \\mathbb{1} \\left[t^{(i)} = t_0 \\right]}{\\sum_{i} \\mathbb{1} \\left[\\hat{u}_i \\geq Thresh(q^{*},\\boldsymbol{\\hat{u}}) \\right] \\cdot \\mathbb{1} \\left[t^{(i)} = t_0 \\right]}\n",
"\\end{align}\n",
"$$ \n",
"The gap, or the difference between this curve and the `Intersection Uplift` curve, in the multiple actions scenario, can be used to justify (or de-justify) the need in treating each treatment separately, instead of an approach in which the model is used to map which instances to treat, and the treatments are chosen randomly for these instances. As the gap between the curves grows bigger (for the benefit of the `Intersection Uplift` curve), the advantage of using a multi-treatment approach is more prominent."
]
},
{
"cell_type": "markdown",
"id": "ae7fd969-011a-427a-a36b-3065b0afd396",
"metadata": {},
"source": [
"**`Realized Vs Unrealized Uplift`** describes the difference in average response between the intersection set - where the recommendation of the model matches the observed action assigned, and the complement set - where the recommended action by the model is different from the one assigned during the collection of the data. It means that the curve represents the difference: $\\mathop{\\mathbb{E}} \\left[ y_i | \\hat{u}_i \\geq Thresh(q^{*},\\boldsymbol{\\hat{u}}) \\hspace{0.2cm},\\hspace{0.2cm} h_{q^{*}}(x^{(i)}) = t^{(i)} \\right] - \\mathop{\\mathbb{E}} \\left[ y_i | \\hat{u}_i \\geq Thresh(q^{*},\\boldsymbol{\\hat{u}}) \\hspace{0.2cm},\\hspace{0.2cm} h_{q^{*}}(x^{(i)}) \\neq t^{(i)} \\right]$ estimated by: \n",
"$$\n",
"\\begin{align}\n",
"\\frac{\\sum_{i} y_i \\mathbb{1} \\left[\\hat{u}_i \\geq Thresh(q^{*},\\boldsymbol{\\hat{u}}) \\right] \\cdot \\mathbb{1} \\left[h_{q^{*}}(x^{(i)}) = t^{(i)} \\right]}{\\sum_{i} \\mathbb{1} \\left[\\hat{u}_i \\geq Thresh(q^{*},\\boldsymbol{\\hat{u}}) \\right] \\cdot \\mathbb{1} \\left[h_{q^{*}}(x^{(i)}) = t^{(i)} \\right]} - \\frac{\\sum_{i} y_i \\mathbb{1} \\left[\\hat{u}_i \\geq Thresh(q^{*},\\boldsymbol{\\hat{u}}) \\right] \\cdot \\mathbb{1} \\left[h_{q^{*}}(x^{(i)}) \\neq t^{(i)} \\right]}{\\sum_{i} \\mathbb{1} \\left[\\hat{u}_i \\geq Thresh(q^{*},\\boldsymbol{\\hat{u}}) \\right] \\cdot \\mathbb{1} \\left[h_{q^{*}}(x^{(i)}) \\neq t^{(i)} \\right]} \n",
"\\end{align}\n",
"$$ \n",
"Such difference can also be used to assess the benefit in learning the optimal treatment to assign to each instance, over the naive approach according to which all treatments are just considered as a *single treatment*."
]
},
{
"cell_type": "markdown",
"id": "f1020e9c-654c-4f6f-86ad-61261874e9b0",
"metadata": {},
"source": [
"### Fractional Lift Curve"
]
},
{
"cell_type": "code",
"execution_count": 26,
"id": "f3542a69-2213-4e72-a4bc-99e95859155c",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": "
",
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\n"
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"evaluator.visualize(eval_res,show_random=True,num_random_rep=4,specify=['fractional_lift'])"
]
},
{
"cell_type": "markdown",
"id": "e8e2e47f-5294-49a0-b467-f1f7f0cb68eb",
"metadata": {},
"source": [
"In some use-cases, especially these in which the response variable is continuous, telling the difference in average response between groups might not be enough. In such cases, telling the percentage increase in average response in one group compared to another can be more useful. The ***fractional lift*** chart provides visualization of average response ratios, which reflect the percentage increase/decrease associated with treatment assignment (or the avoidance of which). This chart replaces the difference/substraction opeartion used for the calculation of the curves depicted in the [uplift chart](#Uplift-Curve), and computes the ratio of average responses between the same \"*confronted*\" sections. For a detailed explanation of the quantities used to compute every curve in this chart, refer to the explanation for the [uplift chart](#Uplift-Curve)."
]
},
{
"cell_type": "markdown",
"id": "9cf5439d-1c39-4918-a79c-46881bd7eb12",
"metadata": {},
"source": [
"### Gain Curve"
]
},
{
"cell_type": "code",
"execution_count": 27,
"id": "7e34d0db-f5db-4a3d-a139-d624c3c09754",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": "
",
"image/png": 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\n"
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"evaluator.visualize(eval_res,show_random=True,num_random_rep=4,specify=['gain'])"
]
},
{
"cell_type": "markdown",
"id": "39d18456-77bf-4d71-95f5-026ad1bebec6",
"metadata": {},
"source": [
"In the `uplift-analysis` framework, we use the term `gain`, to describe the absolute quantitative result / benefit implied by the calculated uplift for the evaluated set. It can be interpreted differently in the case of a binary response variable, or a continuous one. \n",
"Assuming the estimate of the uplift signal is reliable, and for the evaluated set we have $N_{t_0}(q^{*})$ untreated instances falling inside the acceptance region (defined by $\\hat{u}_i \\geq Thresh(q^{*},\\boldsymbol{\\hat{u}})$). If we were to apply the uplift model using the threshold $Thresh(q^{*},\\boldsymbol{\\hat{u}})$ on the same specific evaluated set, the question will be:\n",
"\n",
"- In the case of a binary response variable: how many instances can we expect to change their response from $0$ to $1$?\n",
"- In the case of a continuous variable: what will be the total increase in the response for these $N_{t_0}(q^{*})$ instances, if they were exposed to the recommendations of the model?"
]
},
{
"cell_type": "markdown",
"id": "1558d5f2-9345-4230-b29e-63517423a101",
"metadata": {},
"source": [
"For calculating this we multiply the uplift signal (estimated and shown in the [uplift chart](#Uplift-Curve)) by the quantity of untreated instances, for each $q^{*}$, and the corresponding threshold $Thresh(q^{*},\\boldsymbol{\\hat{u}}) = p_{q^{*}}$:\n",
"$$\n",
"\\begin{align}\n",
"Gain(q^{*}) =\n",
"\\end{align}\n",
"$$\n",
"$$\n",
"\\begin{align}\n",
"\\left( \\frac{\\sum_{i} y_i \\mathbb{1} \\left[\\hat{u}_i > p_{q^{*}} \\right] \\cdot \\mathbb{1} \\left[h_{q^{*}}(x^{(i)}) = t^{(i)} \\right]}{\\sum_{i} \\mathbb{1} \\left[\\hat{u}_i \\geq p_{q^{*}} \\right] \\cdot \\mathbb{1} \\left[h_{q^{*}}(x^{(i)}) = t^{(i)} \\right]} - \\frac{\\sum_{i} y_i \\mathbb{1} \\left[\\hat{u}_i \\geq p_{q^{*}} \\right] \\cdot \\mathbb{1} \\left[t^{(i)} = t_0 \\right]}{\\sum_{i} \\mathbb{1} \\left[\\hat{u}_i \\geq p_{q^{*}} \\right] \\cdot \\mathbb{1} \\left[t^{(i)} = t_0 \\right]} \\right) \\cdot\n",
"\\left(\\sum_{i} \\mathbb{1} \\left[\\hat{u}_i \\geq p_{q^{*}} \\right] \\cdot \\mathbb{1} \\left[t^{(i)} = t_0 \\right] \\right)=\n",
"\\end{align}\n",
"$$\n",
"$$\n",
"\\begin{align}\n",
"Uplift(q^{*})\\cdot N_{t_0}(q^{*})\n",
"\\end{align}\n",
"$$"
]
},
{
"cell_type": "markdown",
"id": "75507801-0f12-41f4-9e40-bf4218d474f2",
"metadata": {},
"source": [
"Although in the specific chart shown above, the depicted curve seems to rise almost for the entire range of $q^{*}$, in practice this curve might be shaped differently in other scenarios. For example, if the uplift curve is descending, but positive, as a function of $q^{*}$, then although $N_{t_0}(q^{*})$ is monotonically increasing w.r.t $q^{*}$, the decrease in the uplift signal might shape the gain curve as a bell-shaped curve. \n",
"Here comes in to the picture the choice of the [*operating point*](#Inspect-Operating-Point-Treatment-Assignment-Distribution). One might want to set the operating point, with a threshold that corresponds to the maximal gain. Thus, this chart highlights the maximal gain point with a marker, labeled with the corresponding score threshold value, in order to facilitate the choice of operating point."
]
},
{
"cell_type": "markdown",
"id": "25314772-2e43-49fe-99a0-49c68312fd6e",
"metadata": {},
"source": [
"As for the previous charts, the curve labeled as `Random` depicts the average gain curve computed for `num_random_rep` randomly scored evaluation sets, and can be used as a benchmark for understanding whether the performance observed in our primary evaluated set is coincidential or not."
]
},
{
"cell_type": "markdown",
"id": "55ec0d48-4fea-4a34-a948-6c42b2cf9a66",
"metadata": {},
"source": [
"Another curve displayed in this chart is labeled as `Treated Gain`. It is relevant only in the case where the evaluated set is associated with multiple treatments. It is used to describe and quantify the gain associated with a scenario in which all the non-neutral actions, $t \\neq t_0$, are treated as a single treatment. Just like in the [uplift chart](#Uplift-Curve), the gap between `Intersection Gain` and `Treated Gain`, can emphasize the need in considering each treatment separately. The maximal point for this gain curve is also highlighted and labeled with the corresponding score threshold value."
]
},
{
"cell_type": "markdown",
"id": "b7eda6de-7917-48ad-b991-1644138117cc",
"metadata": {},
"source": [
"### Expected Response"
]
},
{
"cell_type": "code",
"execution_count": 28,
"id": "c54db41d-69c0-4b7c-b675-64a58528c49f",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": "
",
"image/png": 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\n"
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"evaluator.visualize(eval_res,show_random=True,num_random_rep=4,specify=['avg_response'])"
]
},
{
"cell_type": "markdown",
"id": "2c2faf95-4078-4881-8509-c543951acbe0",
"metadata": {},
"source": [
"Although the analysis of uplift models focuses primarily on statistics computed inside the acceptance region, what we would like to achieve eventually is a model (and a corresponding operating point) which will maximize the expected value of the response for the entire population. \n",
"For doing so, we assume that the distribution of uplift scores and response values observed in the evaluated set, provides a good representation and reflection of the distribution the model will meet upon deployment. In such a case, the expected response can be seen as a weighted average between two factors:\n",
" \n",
"- the **average response** for the group of observations for which the observed actions intersect with the treatments recommended by the model, in the acceptance region: $\\frac{\\sum_{i} y_i \\mathbb{1} \\left[\\hat{u}_i \\geq Thresh(q^{*},\\boldsymbol{\\hat{u}}) \\right] \\cdot \\mathbb{1} \\left[h_{q^{*}}(x^{(i)}) = t^{(i)} \\right]}{\\sum_{i} \\mathbb{1} \\left[\\hat{u}_i \\geq Thresh(q^{*},\\boldsymbol{\\hat{u}}) \\right] \\cdot \\mathbb{1} \\left[h_{q^{*}}(x^{(i)}) = t^{(i)} \\right]}$. This curve is labeled as `AvgResponseIntersectedTreatments`.\n",
"\n",
"- the **average response** for the untreated group of observations,which fall in the rejection region: $\\frac{\\sum_{i} y_i \\mathbb{1} \\left[\\hat{u}_i < Thresh(q^{*},\\boldsymbol{\\hat{u}}) \\right] \\cdot \\mathbb{1} \\left[t^{(i)} = t_0 \\right]}{\\sum_{i} \\mathbb{1} \\left[\\hat{u}_i < Thresh(q^{*},\\boldsymbol{\\hat{u}}) \\right] \\cdot \\mathbb{1} \\left[t^{(i)} = t_0 \\right]}$. This curve is labeled as `AvgResponseUntreated`."
]
},
{
"cell_type": "markdown",
"id": "71ab530c-19e1-45f4-adc2-72641ceef98d",
"metadata": {},
"source": [
"As can be seen in the chart, both of these curves are bounded by uncertainty sleeves. These sleeves represent a $95\\%$ confidence interval associated with the standard error of either the mean estimator (when the response variable is continuous), or the proportion estimator (when the response variable is binary)."
]
},
{
"cell_type": "markdown",
"id": "750add40-6b9b-4447-92ff-78ac432c0f3d",
"metadata": {},
"source": [
"For estimating the expected response associated with the operating point $q^{*}$, we weigh these two curves by the following:\n",
"$$\n",
"\\begin{align}\n",
"q^{*} \\cdot AvgResponseIntersectedTreatments(q^{*}) + \\left( 1-q^{*} \\right) \\cdot AvgResponseUntreated(q^{*})\n",
"\\end{align}\n",
"$$\n",
"As this curve takes into account an aggregation of the performance of the model across the entire distribution of scores, and just like the [gain curve](#Gain-Curve), it might not (and it probably won't) be monotonically increasing, it can also be used for setting the optimal [operating point](#Inspect-Operating-Point-Treatment-Assignment-Distribution)."
]
},
{
"cell_type": "markdown",
"id": "ff02cbeb-2a75-44f4-8c3b-56289aa1ab93",
"metadata": {},
"source": [
"For benchmarking purposes, this chart also displays:\n",
" \n",
"- `TreatedExpectedResponse` - The same logic applied for the computation of `IntersectionExpectedResponse`, but when all the non-neutral treatments are considered as a single treatment.\n",
"- `Random` - The same logic as in `IntersectionExpectedResponse`, applied to a set of randomly scored evaluation sets, and then averaged.\n",
"- `OverallAvgResponse` - The average response observed across the entire evaluation set (fixed value, not affected by a specific choice of operating point).\n",
"- `UntreatedAvgResponse` - The average response observed across the untreated observations in the evaluation set (fixed value, not affected by a specific choice of operating point)."
]
},
{
"cell_type": "markdown",
"id": "b56f542c-2eb0-4938-be31-b1f5000d35ce",
"metadata": {},
"source": [
"### Acceptance and Rejection Regions"
]
},
{
"cell_type": "markdown",
"id": "5267dbf8-3bb0-4dbd-93f8-34c93367ce10",
"metadata": {},
"source": [
"Recall that the uplift signals depicted in the [uplift chart](#Uplift-Curve) are subtractions of mean/proportion estimators of the response in the acceptance region. Therefore it could be useful to examine these source signals directly."
]
},
{
"cell_type": "code",
"execution_count": 29,
"id": "3a8e63fe-8cec-4b5c-a3b6-0ab32eaeb78e",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": "
",
"image/png": 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\n"
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"evaluator.visualize(eval_res,show_random=True,num_random_rep=4,specify=['acceptance_region'])"
]
},
{
"cell_type": "markdown",
"id": "62f14cb2-096b-48e6-baa0-e430b5a94cea",
"metadata": {},
"source": [
"In this chart we can see a few mean/proportion estimate signals, as a function of $q^{*}$, all of which are computed for observations with $\\hat{u}_i \\geq Thresh(q^{*},\\boldsymbol{\\hat{u}})$:\n",
"\n",
"- `Intersections`: where $h_{q^{*}}(x^{(i)}) = t^{(i)}$.\n",
"- `Untreated`: where $t^{(i)} = t_0$.\n",
"- `Treated`: where $t^{(i)} \\neq t_0$ (relevant only in multiple actions scenario).\n",
"- `Unrealized`: where $t^{(i)} \\neq h_{q^{*}}(x^{(i)})$ (relevant only in multiple actions scenario).\n",
"\n",
"Because all these signals, for a certain $q^{*}$, are estimators of mean response / response proportion (depending on the type of response variable), all of them are accompanied by an uncertainty sleeve, depicting a $95\\%$ confidence interval associated with the corresponding standard error. As we move along the curves towards the right side of the chart, the acceptance region goes wider, and these curves (mean/proportion estimators) include more observations for computing the statistics, the uncertainty decreases, and the sleeves go narrower."
]
},
{
"cell_type": "markdown",
"id": "1801f6d9-f000-458e-9f18-fa3cf61b8f13",
"metadata": {},
"source": [
"In addition, this chart depicts the result of a statistical hypothesis test for the difference in average response between the `Intersections` group and the `Untreated` group. The null hypothesis used for this test is that the average response for the two groups is equal, and the alternative hypothesis is that it is different (a two-tailed test). When the response variable is continuous a [t-test](https://stattrek.com/hypothesis-test/difference-in-means.aspx?tutorial=AP) is used for testing the difference in means, and when the response variable is binary a [proportion test](https://stattrek.com/hypothesis-test/difference-in-proportions.aspx) is used. As a result of the test performed for each $q^{*}$, we get a corresponding `p-value`, which quantifies the probability that similar findings will be found in case the null hypothesis is true. The `p-value` associated with each $q^{*}$ is depicted and associated with the right *y-axis* ; as it goes lower it implies that the difference between the estimators is more significant."
]
},
{
"cell_type": "markdown",
"id": "3c89406b-bdf5-49bb-8140-8e487709fcb6",
"metadata": {},
"source": [
"Again, just as in the [*Expected Response* chart](#Expected-Response), the values of `OverallAvgResponse` and `UntreatedAvgResponse` are shown as a reference for comparison as well. "
]
},
{
"cell_type": "markdown",
"id": "9e382db1-7071-4806-a25a-da15ba7ec932",
"metadata": {},
"source": [
"For the complete picture, one can also examine the estimators of average response in the rejection region:"
]
},
{
"cell_type": "code",
"execution_count": 30,
"id": "bdbaa26b-f152-409c-867f-1a5b14fb0ca6",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": "
",
"image/png": 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\n"
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"evaluator.visualize(eval_res,show_random=True,num_random_rep=4,specify=['rejection_region'])"
]
},
{
"cell_type": "markdown",
"id": "f56798f9-d3c1-459f-8955-b24186e97db4",
"metadata": {},
"source": [
"In this chart we can see two mean/proportion estimate signals, as a function of $q^{*}$, both of which are computed for observations, in the rejection region, with $\\hat{u}_i < Thresh(q^{*},\\boldsymbol{\\hat{u}})$:\n",
"\n",
"- `Untreated`: where $t^{(i)} = t_0$.\n",
"- `Treated`: where $t^{(i)} \\neq t_0$."
]
},
{
"cell_type": "markdown",
"id": "7b6f0225-92a4-40e7-95f1-3d316ac262fb",
"metadata": {},
"source": [
"As opposed to the previous chart, here the uncertainty sleeves get wider as we consider a higher value of $q^{*}$, because a higher value of $q^{*}$ implies a narrower rejection region, so these estimates end up relying on less observations."
]
},
{
"cell_type": "markdown",
"id": "4d5586a5-0356-4dab-b3f9-722ce2a90fd2",
"metadata": {},
"source": [
"Similarly to the previous chart, a statistical hypothesis test is applied for testing the difference in average response between the groups mentioned above, and its outcomes, the p-values, are shown (corresponding to right *y-axis*)."
]
},
{
"cell_type": "markdown",
"id": "a007c466-6b99-4bce-a6fc-f828fefeca81",
"metadata": {},
"source": [
"### Agreement Statistics"
]
},
{
"cell_type": "markdown",
"id": "a6bce7c8-20f7-4d45-9af6-4910425a4e1a",
"metadata": {},
"source": [
"As explained earlier, our ability to *interpolate* the observed tuples structured as $(context, treatment, response)$, and estimate the response for an unseen combination of $context$ and $treatment$, depends, among the rest, on the controlled randomization in the data collection phase. \n",
"The evaluated performance shown on the previous chart, relies heavily on the instances for which the recommendation of the model *matches* the assigned treatment during the data collection phase. \n",
"If these intersections occur in significantly different rates along the distribution of uplift scores, it might imply that:\n",
"\n",
"- The assignment of treatments was not completely random - some information, that is also contained in the covariates the model is exposed to, affected the probability of treatment assignment per instance.\n",
"- Or that some leakage of treatment-assignment-related information finds its way, through the covariates, to the model, and affects the distribution of uplift scores for the treated group."
]
},
{
"cell_type": "code",
"execution_count": 31,
"id": "ed20b76f-3c83-4b18-88e9-864cf1455183",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": "
",
"image/png": 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\n"
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"evaluator.visualize(eval_res,show_random=True,num_random_rep=4,specify=['agreements'])"
]
},
{
"cell_type": "markdown",
"id": "d04e2d28-05b4-4912-9635-5a488a49a26c",
"metadata": {},
"source": [
"This chart depicts `AgreementRate`, which shows the rate in which these agreements / intersections occur, as a function of acceptance region width (controlled by $q^{*}$):\n",
"$$\n",
"\\begin{align}\n",
"\\frac{1}{N_{q^{*}}} \\sum_{i} \\mathbb{1} \\left[\\hat{u}_i \\geq Thresh(q^{*},\\boldsymbol{\\hat{u}}) \\right] \\cdot \\mathbb{1} \\left[ h_{q^{*}}(x^{(i)}) = t^{(i)} \\right]\n",
"\\end{align}\n",
"$$\n",
"where $N_{q^{*}}$ denotes the total quantity of observations in the acceptance region. \n",
"In the displayed curve, the rate seems to be almost perfectly uniform w.r.t to $q^{*}$ (except for the noise in the narrow acceptance region, associated with smaller $q^{*}$ values). In the scenario brought here in the tutorial, the generated data is synthetic, and the simulated treatment assignment can be easily randomized, but in practice, this will not always be the case, and this figure can be used to point out imperfections in the randomization of treatment assignment. \n",
"Also displayed in the chart is the curve labeled as `# of Agreements` which is the cumulative count of agreements found as $q^{*}$ grows bigger. Non-linear growth in this monotonically increasing curve might also imply the same leakage or imperfect randomization mentioned above."
]
},
{
"cell_type": "markdown",
"id": "d205d8f6-608c-4ebf-8940-123f52a77fc8",
"metadata": {},
"source": [
"As a benchmark, one can also refer to the curves:\n",
"\n",
"- `Random`: The average agreement rate observed across (possibly multiple) randomly scored evaluation sets.\n",
"- `BinaryAgreementRate`: The agreement rate computed where the set of non-neutral treatments ($t^{(i)} \\neq t_0$), are treated as a single treatment:\n",
"$$\n",
"\\begin{align}\n",
"\\frac{1}{N_{q^{*}}} \\sum_{i} \\mathbb{1} \\left[\\hat{u}_i \\geq Thresh(q^{*},\\boldsymbol{\\hat{u}}) \\right] \\cdot \\mathbb{1} \\left[ t^{(i)} \\neq t_0 \\right]\n",
"\\end{align}\n",
"$$\n",
"It will be displayed only in case the evaluated set is associated with multiple treatments."
]
},
{
"cell_type": "markdown",
"id": "bc8b3718-5d06-4da8-84bc-c0c914962f62",
"metadata": {},
"source": [
"## Compare Evaluated Performance Between `EvalSet`s"
]
},
{
"cell_type": "markdown",
"id": "7230446e-a6fc-43b5-8c54-b7306538d846",
"metadata": {},
"source": [
"The visualizations shown above do provide a lot of performance-related information. However, it visualizes the performance for a single `EvalSet` object. In practice, we may want to compare the performance of multiple experiments at once. \n",
"For demonstration, let us create a dictionary of evaluation sets, corresponding to the *T-learner* models associated with the continuous response variable:"
]
},
{
"cell_type": "code",
"execution_count": 32,
"id": "4453513d-dae4-4520-9ed6-deb77587904e",
"metadata": {},
"outputs": [],
"source": [
"compare_eval_sets = {} # will contain the two evaluation sets\n",
"\n",
"for model_name,field_name in zip(['t_gbdt','t_linear'],['t_learner_gbdt_cont','t_learner_linear_cont']):\n",
" # create `Scorer` object\n",
" scorer = scoring.Scorer({'name': model_name,\n",
" 'scoring_field': field_name,\n",
" 'reference_field': field_name,\n",
" 'reference_idx': 0,\n",
" 'scoring_func': 'cont_score_calc'})\n",
" \n",
" \n",
" ranking, recommended_action, score, action_dim = scorer.calculate_scores(dataset=valid_set)\n",
" scored_df = pd.DataFrame(\n",
" {\n",
" 'recommended_action': recommended_action,\n",
" 'score': score,\n",
" 'observed_action': valid_set['treatments'],\n",
" 'response': valid_set['response']\n",
" }\n",
" )\n",
" compare_eval_sets[model_name] = data.EvalSet(df=scored_df,\n",
" name=model_name,\n",
" observed_action_field='observed_action',\n",
" response_field='response',\n",
" score_field='score',\n",
" proposed_action_field='recommended_action',\n",
" control_indicator=0)"
]
},
{
"cell_type": "markdown",
"id": "fa9d589d-975f-4225-9a3e-48ac4392333a",
"metadata": {},
"source": [
"Notes:\n",
"- In this demonstration the evaluation sets we compare represent different models applied to the same dataset. However, there is no such restriction, and we can use the following comparison flow, for evaluation sets representing different datasets, if it makes sense. For example, we might want to inspect the performance of a single model, applied to different datasets, which can be associated with different population segments, or different time periods.\n",
"- There is no limitation on number of evaluation sets to compare."
]
},
{
"cell_type": "code",
"execution_count": 33,
"id": "8d285222-4a42-4c3a-bbf7-55140cc69bb0",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": "
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\n"
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"e,s = evaluator.eval_and_show(avg_eval_sets,average=True,specify=['fractional_lift','avg_response'])"
]
},
{
"cell_type": "markdown",
"id": "72024b31-a90e-4f1a-a2a1-266fdd0c2144",
"metadata": {},
"source": [
"In that case, the wide gray line represents the average performance across the seeds."
]
},
{
"cell_type": "markdown",
"id": "357ed942-493d-4198-9279-680f87964169",
"metadata": {},
"source": [
"## Evaluation Summaries"
]
},
{
"cell_type": "markdown",
"id": "7a2f32e0-af51-4499-b04a-8dfd9c6b01e4",
"metadata": {},
"source": [
"When applying the evaluation procedure using an `Evaluator` object, we get in return a summary of the aggregate performance measured as part of the evaluation."
]
},
{
"cell_type": "code",
"execution_count": 36,
"id": "0d3f3378-30ee-4238-ad1b-5219d0c3af71",
"metadata": {},
"outputs": [],
"source": [
"_, single_summary = evaluator.evaluate_set(eval_set)\n",
"_, multi_summary = evaluator.evaluate_multiple(compare_eval_sets)"
]
},
{
"cell_type": "markdown",
"id": "c92fa370-0a37-40b7-af25-3a667c7d452a",
"metadata": {},
"source": [
"The `single_summary` is a `dict`:"
]
},
{
"cell_type": "code",
"execution_count": 37,
"id": "78fa554a-cb70-4ed7-aaa0-9cdc01cb8a39",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"intersect_AUUC : 0.23\n",
"intersect_max_avg_resp : 0.52\n",
"max_relative_lift_intersect : 0.18\n",
"intersect_max_gain : 9063.24\n",
"treated_AUUC : 0.06\n",
"treated_max_avg_resp : 0.38\n",
"max_relative_lift_treated : 0.03\n",
"treated_max_gain : 1739.44\n"
]
}
],
"source": [
"for k,v in single_summary.items():\n",
" print(f\"{k} : {v:.2f}\")"
]
},
{
"cell_type": "markdown",
"id": "21e2a3c6-1933-47ce-90de-eadb0a4acc91",
"metadata": {},
"source": [
"while the `multi_summary` is a pandas dataframe, allowing to observe the aggregate performance across multiple evaluation sets:"
]
},
{
"cell_type": "code",
"execution_count": 38,
"id": "faab7646-e86e-4c00-a94a-99bd6abb06d1",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": " intersect_AUUC intersect_max_avg_resp max_relative_lift_intersect \\\nt_gbdt 0.546067 5.068639 0.440621 \nt_linear 0.610636 5.080676 0.452659 \n\n intersect_max_gain treated_AUUC treated_max_avg_resp \\\nt_gbdt 21939.330516 0.107946 4.695551 \nt_linear 22538.792154 0.112413 4.691894 \n\n max_relative_lift_treated treated_max_gain \nt_gbdt 0.067534 3355.064437 \nt_linear 0.063876 3174.949781 ",
"text/html": "
\n\n
\n \n
\n
\n
intersect_AUUC
\n
intersect_max_avg_resp
\n
max_relative_lift_intersect
\n
intersect_max_gain
\n
treated_AUUC
\n
treated_max_avg_resp
\n
max_relative_lift_treated
\n
treated_max_gain
\n
\n \n \n
\n
t_gbdt
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0.546067
\n
5.068639
\n
0.440621
\n
21939.330516
\n
0.107946
\n
4.695551
\n
0.067534
\n
3355.064437
\n
\n
\n
t_linear
\n
0.610636
\n
5.080676
\n
0.452659
\n
22538.792154
\n
0.112413
\n
4.691894
\n
0.063876
\n
3174.949781
\n
\n \n
\n
"
},
"execution_count": 38,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"multi_summary"
]
},
{
"cell_type": "markdown",
"id": "8b70dccd-7b21-480e-bc0d-f06334ff1edc",
"metadata": {},
"source": [
"The measures listed in these summaries are:\n",
"\n",
"- `intersect_AUUC`: The area under the uplift curve (i.e. its integral), shown in the [uplift chart](#Uplift-Curve).\n",
"- `intersect_max_avg_resp`: The maximal expected response computed, corresponding to the [expected response chart](#Expected-Response).\n",
"- `max_relative_lift_intersect`: The maximal difference between the expected response curve, and the average response observed for the untreated group (across the entire dataset), which is labeled as `UntreatedAvgResponse` in the [expected response chart](#Expected-Response).\n",
"- `intersect_max_gain`: The maximal gain computed, corresponding to the [gain chart](#Gain-Curve).\n",
"\n",
"The other metrics will be included in the summary only for evaluation sets associated with multiple actions. Their names will include the replacement of `intersect` with `treated`, and they reveal the same logic explained above, applied in the case where the set of the multiple non-neutral actions are considered as a single treatment."
]
}
],
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