{ "cells": [ { "cell_type": "markdown", "id": "008318e7-795e-45bd-b630-00f7c43fb632", "metadata": {}, "source": [ "
PRIME: A CyberGIS Platform for Resilience Inference Measurement and Enhancement
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Authors : Debayan Mandal 1, Dr. Lei Zou1,*, Rohan Singh Wilkho3, Joynal Abedin1, Bing Zhou1, Dr. Heng Cai2, Dr. Furqan Baig4, Dr. Nasir Gharaibeh3, Dr. Nina Lam5
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\n", "\n", " 1 Geospatial Exploration and Resolution (GEAR) Lab, Department of Geography, College of Geosciences, Texas A & M University
\n", " 2 GIResilience Lab, Department of Geography, College of Geosciences, Texas A & M University
\n", " 3 Zachry Department of Civil and Environmental Engineering, College of Engineering, Texas A & M University
\n", " 4 CyberGIS Center for Advanced Digital & Spatial Studies, University of Illinois at Urbana-Champaign
\n", " 5 Department of Environmental Sciences, College of the Coast & Environment, Louisiana State University
\n", " * Corresponding author: lzou@tamu.edu
\n", "\n", "You can checkout the paper here: \t\n", "https://doi.org/10.48550/arXiv.2404.09463" ] }, { "cell_type": "markdown", "id": "8efc0a12-8061-468c-aafc-72bf6f28e07e", "metadata": {}, "source": [ "---" ] }, { "cell_type": "markdown", "id": "1cf03ec6-15e5-42f8-834f-cc4effc2d52a", "metadata": {}, "source": [ "# Introduction" ] }, { "cell_type": "markdown", "id": "3f9f69f7-f318-45e8-a569-ea7ce28e932e", "metadata": {}, "source": [ "Resilience assessment and improvement have become increasingly important in today's world, where natural and man-made disasters are becoming more frequent and severe. Cities, communities, and organizations are recognizing the need to prepare for and mitigate the impacts of disasters and disruptions, and there is a growing body of research and practice on resilience assessment and improvement.\n", "\n", "One significant research gap in this area is the lack of a customizable platform for resilience assessment and improvement. While there are many tools and frameworks available for assessing and improving resilience, they are often limited in their scope and applicability. Many of these tools are designed for specific types of hazards or sectors and may not be easily adapted to other contexts. Furthermore, many of these tools are proprietary and require significant resources to implement and maintain.\n", "\n", "\n", "A customizable platform for resilience assessment and improvement would address these limitations by providing a flexible and adaptable framework that can be tailored to the needs and priorities of different users. Such a platform would allow users to customize the tools and metrics used for resilience assessment, as well as the interventions and strategies for resilience improvement. This would enable users to address specific challenges and opportunities in their context, and to leverage existing resources and knowledge to support resilience. By enabling users to tailor resilience assessment and improvement to their specific needs and priorities, such a platform would help to build more resilient communities, organizations, and systems, and contribute to a more sustainable and resilient future for all." ] }, { "cell_type": "markdown", "id": "94232734-71c8-4171-92e9-13abf46ae9c0", "metadata": {}, "source": [ "## Resilience Inference Measurement Model" ] }, { "cell_type": "markdown", "id": "aafb6641-76c5-4cf5-bfcd-b5b04913f948", "metadata": {}, "source": [ "The Resilience Inference Measurement (RIM) model was developed by Dr. Nina Lam to measure disaster resilience of various units of the community, viz. individuals and organizations. It is based on the idea that resilience is dependent on adaptability as well as vulnerability, i.e., not just the ability to bounce back from adversity, but also the ability to adapt and thrive in the face of ongoing challenges and stressors. The RIM model is unique in that it evaluates resilience using empirical disaster measures such as threat, damage and recovery in line with the Sendai Framework, as well as taking on a holistic approach to measuring resilience, incorporating not only empirical factors but also the broader social and environmental context. This makes it a powerful tool for identifying areas of strength and weakness in resilience and for developing targeted interventions and strategies to build resilience in communities." ] }, { "cell_type": "markdown", "id": "be731cdb-d3e2-476b-9e16-5ca06ce94a2e", "metadata": {}, "source": [ "
\n", " \"Image\"\n", "
" ] }, { "cell_type": "markdown", "id": "5b20f237-5a61-4fb1-a341-2303678d7a01", "metadata": {}, "source": [ "The above figure suggests the preliminary idea that in one resilience cycle vulnerability is dependent on exposure and damage, while adaptability is dependent upon the damage and recovery from the natural hazard. This goes into a feedback loop and updates itself in the next resilience cycle where mitigation procedures from recovery activities reduce exposure to the particular disaster while adaptation measures reduce future disaster damages. " ] }, { "cell_type": "markdown", "id": "a409fa1c-c195-4ab9-b666-f33fcf19ee54", "metadata": {}, "source": [ "## Enhanced Customizable Framework" ] }, { "cell_type": "markdown", "id": "efb5c0e7-3b4f-4291-a3f0-3f0b4d37a03c", "metadata": {}, "source": [ "
\n", " \"Image\"\n", "
" ] }, { "cell_type": "markdown", "id": "55bbcaac-a327-41c4-baa9-10ae49a115e0", "metadata": {}, "source": [ "In formulating the CRIM model, we have based it on the fundamental framework of the RIM and addressed its limitations. Please refer to our paper for detailed breakdown of the enhancements and customizations. The workflow mainly operates using disaster event and socioeconomic datasets. In Step 1 and 2, it calculates resilience scores (adaptability, vulnerability, resilience) based on empirical parameters of hazard threat, damage, and recovery. In Step 3, CRIM uses machine learning regressors to learn the relationships between the resultant scores and socio-economic factors characterizing a community. These relationships are validated using a held-out test dataset. This not only confirms the reliability of the identified relationships but also ensures their generalizability." ] }, { "cell_type": "markdown", "id": "1f61385e-2601-49d3-80b0-ced3814a776e", "metadata": {}, "source": [ "# Prerequisites to Model Implementation" ] }, { "cell_type": "markdown", "id": "125ff7b0-879b-4f9a-bdd7-e25efb153079", "metadata": {}, "source": [ " This code has been tested to run properly for Python 3-0.9.0. Please make sure to choose that kernel so as not to run into any errors." ] }, { "cell_type": "code", "execution_count": 1, "id": "415a8ca4-5544-4f23-9d27-20c01bc357db", "metadata": {}, "outputs": [], "source": [ "import warnings\n", "from sklearn.preprocessing import MinMaxScaler\n", "warnings.filterwarnings(\"ignore\")" ] }, { "cell_type": "code", "execution_count": 2, "id": "9f42c0a7-2779-47b7-ab23-bf9c28495249", "metadata": {}, "outputs": [], "source": [ "!pip install xgboost --quiet" ] }, { "cell_type": "markdown", "id": "b9db7154-b8d8-491b-ad78-dc98006531cd", "metadata": {}, "source": [ "## All the Inputs" ] }, { "cell_type": "markdown", "id": "a5168d42-2667-4459-b139-fe376a562f21", "metadata": {}, "source": [ "This section is only for entering filtering parameters from the whole dataset
\n", "*Sample:*\n", "
\n", " \"Image\"\n", "
" ] }, { "cell_type": "code", "execution_count": 3, "id": "b7693188-0558-41fe-ab9a-338d504e4338", "metadata": {}, "outputs": [ { "data": { "application/vnd.jupyter.widget-view+json": { "model_id": "e8f49b348a9c43c1812a60960af54dce", "version_major": 2, "version_minor": 0 }, "text/plain": [ "HBox(children=(IntText(value=0, description='Initial year:', style=DescriptionStyle(description_width='50%')),…" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "application/vnd.jupyter.widget-view+json": { "model_id": "2179badf66934533964ad30e3287088e", "version_major": 2, "version_minor": 0 }, "text/plain": [ "HBox(children=(VBox(children=(RadioButtons(description='Avalanches:', options=('Yes', 'No'), style=Description…" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "application/vnd.jupyter.widget-view+json": { "model_id": "32af8504841140bca1b8a46b51d6a17b", "version_major": 2, "version_minor": 0 }, "text/plain": [ "HBox(children=(Button(button_style='success', description='Submit:', style=ButtonStyle()),), layout=Layout(jus…" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "import preprocess as prep\n", "widget_dict = prep.create_gui1()" ] }, { "cell_type": "code", "execution_count": 4, "id": "7e8427bc-85bd-4a6f-a177-09d85386a6d9", "metadata": { "tags": [] }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "The inputted parameters are:\n", "Duration to be computed:2000 to 2020 \n", "\n", "The hazards considered in this computation are:\n", "Avalanche, Tornado, Coastal, Flooding, SevereStorm, Wind, Drought, Heat, Earthquake, Fog, WinterWeather, Hail, Landslide, Lightning, Tsunami, Wildfire, Hurricane\n", "\n", "All counties will be evaluated\n" ] } ], "source": [ "prep.print1(widget_dict)" ] }, { "cell_type": "markdown", "id": "5521f211-fb1c-46c5-b337-36b2e4dcef7e", "metadata": {}, "source": [ "## Data Pre-processing" ] }, { "cell_type": "code", "execution_count": 5, "id": "8816407b-b710-4cc4-ba3b-00a9ddaf441b", "metadata": {}, "outputs": [], "source": [ "fn = prep.process_data(widget_dict)" ] }, { "cell_type": "markdown", "id": "7980540e-f788-43b9-8416-b33c70fa35d4", "metadata": {}, "source": [ "# Three Empirical Factor Calculation" ] }, { "cell_type": "markdown", "id": "35eee008-0532-4874-a2ab-26bdeefe3ff7", "metadata": {}, "source": [ "
\n", " \"Image\"\n", "
" ] }, { "cell_type": "markdown", "id": "464610c4-a810-4bd2-b3bb-5e7b2bc4c181", "metadata": {}, "source": [ "To realize these frameworks, we incorporated formulas aimed at quantifying the otherwise abstract concepts of vulnerability and adaptability. In the CRIM framework, we first compute the three empirical parameters: threat, damage, and recovery using the Comprehensive Hazard and Population data per year.\n", "
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Threat (per hazard event) = Duration(days) * Likelihood * Weightage
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(Equation 1)

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Likelihood (per hazard type) = Count / Total Days
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(Equation 2)

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Weight (per hazard type) = Mean Damage per day per capita
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(Equation 3)

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Damage per capita (per hazard event) = (Crop Damage + Property Damage) / Initial Population
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(Equation 4)

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Recovery Rate (per county) = (Final Population - Initial Population) / Initial Population
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(Equation 5)

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\n", "These equations are entirely modifiable as per requirements of the study" ] }, { "cell_type": "markdown", "id": "5d87cbe0-99be-49b4-b75b-420ab68af34f", "metadata": {}, "source": [ "
Equation 1:
\n", "The first component, duration, refers to the length of the historic hazard events, expressed in days. This variable recognizes that the impact of a hazard event typically increases with its duration. The second component is the likelihood, which quantifies the probability frequency distribution of hazard type per day (Equation 2). This factor acknowledges the inherent uncertainty in the occurrence of hazard events. The third component is the weight for each hazard event type. This weightage of each hazard event type is depicted as the mean damage caused per day per capita in a county. This factor recognizes that different hazard types can have different impacts based on its nature. For example, tornadoes might occur more frequently but cause less average damage than earthquakes. To calculate the weight (Equation 3), we assessed the individual damage data for each event to determine the mean damage per day per capita for each hazard event type.\n", "

Equation 4:
\n", "We derive a per capita estimate of the damage by dividing the sum of these damages by the pre-event initial population. Crop damage refers to the harm inflicted on agricultural produce by the disaster, which can impact local economies, particularly in areas heavily dependent on agriculture. Property damage pertains to the destruction of infrastructure (homes, businesses, public facilities) which has direct and immediate impact on urban residents' living conditions and livelihoods. \n", "

Equation 5:
\n", "the recovery variable gives a quantification of the community trying to return back to its original state before disaster. As population change is one prominent factor for quantifying how the community works despite disaster, i.e., if there has been migration to and from the community - this has been chosen as a Recovery factor. The increase in population has been calculated to be the recovery factor. A higher recovery rate for a county signifies an increase in population after the disaster events, indicating successful society rebuilding efforts." ] }, { "cell_type": "code", "execution_count": 6, "id": "a029c7b5-fea5-492e-9dbe-805eff539e08", "metadata": {}, "outputs": [], "source": [ "edr_tot = prep.empfac(fn, widget_dict)" ] }, { "cell_type": "markdown", "id": "0f578b9a-5f92-4bfd-812c-012aa23d1063", "metadata": {}, "source": [ "# Disaster Resilience Indexes" ] }, { "cell_type": "markdown", "id": "124d009c-e9e8-4d72-afd4-acb89d6f93d4", "metadata": {}, "source": [ "
\n", " \"Image\"\n", "
" ] }, { "cell_type": "markdown", "id": "84356487-3450-4ac0-bb53-67791cd65ac4", "metadata": {}, "source": [ "Finally, the resilience indexes are calculated. The calculations and concepts are discussed in the following sections. For normalization technique we have opted for minmax scaling. MinMax Scaling rescales numeric features into a common range, typically 0 to 1, ensuring that no particular feature dominates due to its numeric range. The calculation involves subtracting the minimum value of a feature, then dividing by its range (maximum - minimum). This technique maintains the original distribution's shape but doesn't handle outliers well. In the new scale, the minimum value becomes 0, the maximum 1, and all other values fall proportionally within this range. It is particularly beneficial when the data does not follow a Gaussian distribution, which was the case with several of our parameters.
Users may modify the code to opt for z-score normalization too if the data follows a Gaussian distribution " ] }, { "cell_type": "markdown", "id": "bd4b32e5-df8e-4050-8be6-10657561fc27", "metadata": {}, "source": [ "## Adaptability Calculation" ] }, { "cell_type": "markdown", "id": "1df146c4-cd91-426f-9e0c-fd0255fb2680", "metadata": {}, "source": [ "Adaptability in disaster resilience refers to the ability of a community or system to adjust and respond effectively to changes or disruptions caused by a disaster. This includes the capacity to anticipate, absorb, and recover from the impacts of a disaster, and to learn from the experience in order to better prepare for future events. It is quantified using the Equation 6. Here, the difference is obtained after normalization as both the minuend and subtrahends are of different units. " ] }, { "cell_type": "markdown", "id": "a00363d0-7eb6-48e7-97c6-787d85d99150", "metadata": {}, "source": [ "
Adaptability = Normalized Recovery – Normalized Damage
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(Equation 6)

" ] }, { "cell_type": "markdown", "id": "0dee35dc-bdc6-48d5-b5f0-dea60c70eca8", "metadata": {}, "source": [ "## Vulnerability Calculation" ] }, { "cell_type": "markdown", "id": "bac39707-60d9-4cb3-b8ad-d61107e3eb4c", "metadata": {}, "source": [ "Vulnerability in disaster resilience refers to the susceptibility of a community or system to potential harm or damage caused by natural or human-made hazards. This can be influenced by various factors such as socioeconomic status, physical and environmental conditions, and access to resources and services. Reducing vulnerability is a crucial aspect of building resilience to disasters, as it enables communities to better withstand and recover from the impacts of disasters.\n", "We compute vulnerability as the normalized differential between damage and threat (equation 7). We express both these factors in the same units, and hence, obtain the difference before normalizing. The underlying principle contends that a community enduring equivalent destruction from infrequent disasters would be perceived as more vulnerable compared to a community exposed to more recurrent disasters. " ] }, { "cell_type": "markdown", "id": "cec46350-4ca9-4994-a9b0-c2b5a02c6c14", "metadata": {}, "source": [ "
Vulnerability = Normalized Damage – Normalized Threat
\n", "

(Equation 7)

" ] }, { "cell_type": "markdown", "id": "8a36e4bc-2b84-4c15-95ff-ea5dff438a37", "metadata": {}, "source": [ "## Resilience Calculation" ] }, { "cell_type": "markdown", "id": "6f8d6f3b-ed91-4010-8e23-2647f08c619b", "metadata": {}, "source": [ "Resilience Score (equation 8) is a comprehensive measure of a community’s resilience to disasters. We interpret it as the relation between the adaptability and vulnerability of a community, and it is formulated as follows:\n", "
Resilience = Adaptability – Vulnerability
\n", "

(Equation 8)

\n", "It implies that increasing a community's adaptability or reducing its vulnerability would improve the community's overall resilience score to disasters. These thus offer us insights into the dynamics of disaster impact and recovery. " ] }, { "cell_type": "code", "execution_count": 7, "id": "4621d092-9951-49e9-aa80-5a76a6b64c2f", "metadata": {}, "outputs": [], "source": [ "edr_tot,prgr = prep.disres(edr_tot)" ] }, { "cell_type": "markdown", "id": "168778ce-7951-42e0-9087-9ec6a8efce33", "metadata": { "tags": [] }, "source": [ "## Priori Group Visualization" ] }, { "cell_type": "markdown", "id": "c03602ab-fccf-4e00-b26c-98ea264500f6", "metadata": {}, "source": [ "
\n", " \"Image\"\n", "
" ] }, { "cell_type": "markdown", "id": "63b53265-4783-4486-804e-4efb79f7544b", "metadata": {}, "source": [ "For exploratory analysis purposes, we propose that the resultant scores are additive in nature. Under this assumption, we suggest that long-term resilience over the whole study period could be understood as the average of their yearly counterparts. It is a simplified perspective intended to provide an overarching view of the community's disaster resilience over a longer span. A quantile classification function in incorporated that transforms the continuous scores into four categories. This interactive map interface visualizes these resilience, vulnerability, and adaptability categories, in different choropleth layers, across different counties." ] }, { "cell_type": "markdown", "id": "42e3392c-7c9d-4b40-81bc-6e5f6de66e63", "metadata": {}, "source": [ "*Sample:*\n", "
\n", " \"Image\"\n", "
" ] }, { "cell_type": "code", "execution_count": 8, "id": "57bad49c-51b3-44e2-9903-ac6b36839a02", "metadata": {}, "outputs": [ { "data": { "text/html": [ "

This displays the aggregate resilience indexes from 2000 to 2020

" ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "text/html": [ "
Make this Notebook Trusted to load map: File -> Trust Notebook
" ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "final_df = prep.gencpleth(prgr, \"data/counties/geojson-counties-fips.json\", widget_dict['ini'].value, widget_dict['fin'].value)" ] }, { "cell_type": "markdown", "id": "38aa1ca6-28aa-4510-8dbd-11736f65a0dd", "metadata": {}, "source": [ "# Socio-Economic Data Processing" ] }, { "cell_type": "markdown", "id": "509b4b93-acfd-4051-9bcd-6d80be76aeee", "metadata": { "tags": [] }, "source": [ "## Post Groups with Customisable Machine Learning" ] }, { "cell_type": "markdown", "id": "aa369a7c-3403-46d8-8bbe-f6cec0149b67", "metadata": {}, "source": [ "
\n", " \"Image\"/\n", "
" ] }, { "cell_type": "markdown", "id": "5ce0d052-995f-4ceb-a75b-e62a16eee069", "metadata": {}, "source": [ "Our framework integrates a selection of machine learning models, covering both white-box (fully interpretable) and grey-box (partially interpretable) regressor models. These models are applied to validate the resilience scores obtained in relation to socioeconomic factors and develop a predictive model. The framework computes performance error metrics dependent upon the choice of regressors. Ultimately, the choice of the most precise model for such predictive tasks is left to the users. To provide explainability, the framework depicts the relationship between the socio-economic variables and resilience scores using coefficients, importance scores, and directed arcs. " ] }, { "cell_type": "markdown", "id": "d35e52e2-d134-45f1-bc59-87f49f9f816c", "metadata": {}, "source": [ "Our process for each model follows the sequence of hyperparameter tuning, re-training tuned models and model evaluation. We optimize model performance through hyperparameter tuning, selecting models yielding the lowest MAE values in the cross-validation process. After determining the optimized hyperparameters, we initialize the models with these parameters and re-train them on the original training set. Subsequently, we assess the model performance by computing evaluation metrics on the held-out testing set." ] }, { "cell_type": "markdown", "id": "8349731f-f9e9-4fff-9d3c-86e1a57c7246", "metadata": {}, "source": [ "### Variable Correlation" ] }, { "cell_type": "markdown", "id": "0f4624bb-2ae9-4a00-a464-58a1f71ab52f", "metadata": {}, "source": [ "Checking data correlation:" ] }, { "cell_type": "markdown", "id": "38eb7dba-23d2-4901-800b-2f0540c4425e", "metadata": {}, "source": [ "*Sample:*\n", "
\n", " \"Image\"\n", "
" ] }, { "cell_type": "code", "execution_count": 9, "id": "0a90e0b2-9f54-49c8-b5eb-0937353c0684", "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "import corr as corr\n", "X, data, corr_matrix = corr.matrix('data/variables', widget_dict['ini'].value, widget_dict['fin'].value, final_df)" ] }, { "cell_type": "markdown", "id": "4dff7a42-eae2-469e-951a-c6797c7b0347", "metadata": {}, "source": [ "In general, it is desirable to avoid using highly correlated independent variables as inputs to a machine learning model. This is because highly correlated variables can lead to overfitting, where the model fits the noise in the data instead of the underlying relationships between the independent and dependent variables. A commonly used rule of thumb is to avoid using variables with a correlation coefficient above 0.7 or below -0.7. However, the exact threshold for acceptable correlation depends on the specific problem and the nature of the data. It is generally a good idea to examine the pairwise correlation between the independent variables and remove highly correlated variables before fitting a machine learning model.\n", "

\n", "*Sample:*\n", "
\n", " \"Image\"\n", "
" ] }, { "cell_type": "code", "execution_count": 10, "id": "71e0ed79-0ed2-458a-9e44-2ce14d35c02e", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Enter method for dropping columns: \n" ] }, { "data": { "application/vnd.jupyter.widget-view+json": { "model_id": "676aa129819341fc84aaffc7477c6102", "version_major": 2, "version_minor": 0 }, "text/plain": [ "RadioButtons(description='Options:', options=('Remove by selecting names', 'Remove by correlation index'), val…" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "choice = corr.remopt()" ] }, { "cell_type": "code", "execution_count": 11, "id": "d7aea8ce-3cff-4b8a-8c34-fc6bae15ccb5", "metadata": {}, "outputs": [ { "name": "stdin", "output_type": "stream", "text": [ "Enter the correlation index (0.7 is usual): 0.7\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Columns being removed because of high correlation:\n", "\n", "Households with atleast 1 vehicle\n", "General Medical And Surgical Hospitals\n", "Household with no plumbing\n", "Emergency Services Personnel\n", "Living Alone\n", "Geographical Mobility Same House 1 Year Ago\n", "Median Household Income\n" ] } ], "source": [ "columns_to_drop = corr.optionA(data) if choice.value == 'Remove by selecting names' else corr.optionB(data) if choice.value == 'Remove by correlation index' else None" ] }, { "cell_type": "markdown", "id": "8405466e-4f25-437e-84bf-f6ab02e7c1d6", "metadata": {}, "source": [ " Please press Enter after inputting the desired correlation index if the second option is chosen " ] }, { "cell_type": "code", "execution_count": 12, "id": "c7cff2dd-5f51-4000-bedf-4fa7ceec01bb", "metadata": {}, "outputs": [], "source": [ "X = corr.dropcol(X, columns_to_drop)" ] }, { "cell_type": "code", "execution_count": 13, "id": "b9ede5e0-9c7a-4574-af7d-259ead3c6170", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Number of entries with no value: 14655\n" ] } ], "source": [ "save_df,X = corr.makedf(X, prgr)" ] }, { "cell_type": "markdown", "id": "d4292060-609a-4677-9e22-4b9a34ccffba", "metadata": {}, "source": [ "### Feature Scaling" ] }, { "cell_type": "markdown", "id": "60b2e80c-fa73-4541-8cb8-a0a6123024c6", "metadata": {}, "source": [ "

This is done to have an unbiased evaluation. Otherwise Eucledian distance mire the results. If the features are on different scales, the larger ones can have a disproportionately large effect on the model, leading to biased results. By scaling the features to have zero mean and unit variance (using techniques such as StandardScaler or MinMaxScaler), we can ensure that all independent features have a similar impact on the model.

" ] }, { "cell_type": "code", "execution_count": 14, "id": "9d8905cb-6cb9-459a-820d-0bcccd624ac0", "metadata": {}, "outputs": [], "source": [ "X = MinMaxScaler().fit_transform(X)" ] }, { "cell_type": "markdown", "id": "5132995f-418b-4c32-aaed-7f55376e8902", "metadata": { "tags": [] }, "source": [ "### Test-train split" ] }, { "cell_type": "markdown", "id": "57268143-dc6b-4ee4-80a4-e1e0090f827f", "metadata": {}, "source": [ "It divides the entire dataset into a user-inputted split. The training set is used to perform training and hyperparameter tuning, and the testing set to compare the tuned models’ performances. Please click \"Submit\" after entering the parameters. The input will also be printed in the console log for verification if needed." ] }, { "cell_type": "markdown", "id": "367f50fa-2c94-40a1-8a23-40d0fefbdf88", "metadata": {}, "source": [ "*Sample:*\n", "
\n", " \"Image\"\n", "
" ] }, { "cell_type": "code", "execution_count": 15, "id": "019855f0-d6ef-44aa-b535-a4275beabf1d", "metadata": {}, "outputs": [ { "data": { "application/vnd.jupyter.widget-view+json": { "model_id": "2e4ffb5545774f37854eecb433cceeaa", "version_major": 2, "version_minor": 0 }, "text/plain": [ "FloatSlider(value=0.2, description='Test Split', max=0.9, min=0.1)" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "application/vnd.jupyter.widget-view+json": { "model_id": "c2dc75f12eea40958d486be27afe6acf", "version_major": 2, "version_minor": 0 }, "text/plain": [ "IntText(value=42, description='Random State')" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "application/vnd.jupyter.widget-view+json": { "model_id": "cafb0c9fd0ec4b039a1f5998df61ba05", "version_major": 2, "version_minor": 0 }, "text/plain": [ "Button(description='Submit', style=ButtonStyle())" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "import ML\n", "test_split, random_state = ML.split()" ] }, { "cell_type": "code", "execution_count": 16, "id": "551ad695-5ac5-4d70-bb39-5bab9ca61b97", "metadata": {}, "outputs": [], "source": [ "splits = ML.split_data(X, save_df['Y_Class'], save_df['YV_Class'], save_df['YA_Class'], save_df['YV_Value'], save_df['YA_Value'], save_df['YR_Value'], test_split, random_state)" ] }, { "cell_type": "markdown", "id": "dcbbd2ec-9c18-4428-980f-bc9f1cc972bc", "metadata": {}, "source": [ "# Regressors" ] }, { "cell_type": "markdown", "id": "d56faf4f-c78b-4932-bf63-8e06a2a56deb", "metadata": {}, "source": [ "## Choose your model\n", "- [Linear Regression](#Linear-Regression)\n", "- [Ridge Regression](#Ridge-Regression)\n", "- [Support Vector Regression](#Support-Vector-Regression)\n", "- [Random Forest Regression](#Random-Forest-Regression)\n", "- [XGBoost Regression](#XGBoost-Regression)\n", "- [Bayesian Network](#Bayesian-Network)" ] }, { "cell_type": "markdown", "id": "14636b3d-21eb-419a-b0ae-b3641b69fe67", "metadata": {}, "source": [ "## Linear Regression" ] }, { "cell_type": "markdown", "id": "dd01b153-e7a9-4751-9bac-ed592e265040", "metadata": {}, "source": [ "Linear regression is a statistical method used to study the relationship between two continuous variables by fitting a linear equation to the observed data. The goal of linear regression is to find the best-fit line that can predict the value of the dependent variable (Y) based on the value of the independent variable (X).\n", "\n", "Pros:\n", "- Simple and easy to understand.\n", "- Fast and computationally efficient.\n", "- Works well when the relationship between variables is linear.\n", "\n", "Cons:\n", "- Assumes a linear relationship between variables, which may not always hold true.\n", "- Sensitive to outliers, as they can significantly impact the fit of the model.\n", "- Cannot handle non-linear relationships or interactions between variables." ] }, { "cell_type": "markdown", "id": "6ebd0107-600c-48e4-a1cb-b6baae2781bc", "metadata": {}, "source": [ "### Adaptability" ] }, { "cell_type": "code", "execution_count": 17, "id": "45f0f973-0085-40b9-9c33-f9e9ce7c6353", "metadata": {}, "outputs": [ { "data": { "image/png": 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3nVp778COY/jdUd0rnRBCCCFEz0SdGIQQQggh2gwpcEIIIYQQbYYUOCGEEEKINqNoDJwQor1Y4+I1vtW/d+2oa7/VvyeEEGMLssAJIYQQQrQZXVbgzGwGM1sx3/c3swm6TywhhBBCCDEmuqTAmdnWwOXAablrEHBVN8kkhBBCCCG+gK5a4HYElgDeBnD3vwJTdJdQQgghhBBizHRVgfvA3T+sNsysD1+xqbwQQgghhPh26KoC9wcz2xfob2YrAZcBSh8TQgghhChAVxW4vYE3gEeBbYn2V/t3l1BCCCGEEGLMdLUOXH/gbHc/A8DMeue+97tLMCGEEEII0TldtcDdSihsFf2BW759cYQQQgghxJfRVQVuXHd/t9rI9wO6RyQhhBBCCPFFdFWBe8/MFqw2zGwh4L/dI5IQQgghhPgiuhoD9yPgMjN7JbenBjboFomEEEIIIcQX0iUFzt3vM7PZgdkAA55y94+6VTIhhBBCCNEpXbXAASwMDM7fWcDMcPfzu0UqIYQQQggxRrqkwJnZBcDMwEPAJ7nbASlwQgghhBAN01UL3FBgTndX+ywhhBBCiMJ0NQv1MWCq7hRECCGEEEJ0ja5a4CYDnjCze4EPqp3uvma3SCWEEEIIIcZIVxW4g7tTCCGEEEII0XW6WkbkD90tiBBCCCGE6BpdioEzs0XN7D4ze9fMPjSzT8zs7e4WTgghhBBCfJ6uJjGcCIwC/ko0st8q9wkhhBBCiIbpciFfd3/WzHq7+yfAOWb2p26USwghhBBCjIGuKnDvm1k/4CEzOxJ4FRiv+8QSQgghhBBjoqsu1E3y2J2A94DpgHW6SyghhBBCCDFmuqrAreXu/3P3t939EHffFVi9OwUTQgghhBCd01UFbrNO9m3+LcohhBBCCCG6yBfGwJnZKOD7wExmdk3towmAt7pTMCGEEEII0TlflsTwJyJhYTLg6Nr+d4BHuksoIYT4Oqxx8Rrf6t+7dtS13+rfE0KIb4svVODc/UUzexl4T90YhBBCCCF6Bl8aA5d13943swkbkEcIIYQQQnwJXU1i+B/wqJmdZWbHV69v+uVmtqqZPW1mz5rZ3p18bvldz5rZI2a2YFd/VwghhBDiu0pXC/lel69vDTPrDZwErAS8DNxnZte4+xO1w4YDQ/I1DDgFGNbF3xVCCCGE+E7SJQXO3c/LTgyz5q6n3f2jb/jdiwDPuvvzAGZ2CTASqCthI4Hz3d2BP5vZRGY2NTC4C78rhBBCCPGdxEI3+pKDzJYFzgNeAIzoxLCZu//xa3+x2feAVd19q9zeBBjm7jvVjvkt8DN3vzO3bwX2IhS4L/zd2t/YBtgGYPrpp1/oxRdf/LoiCyHEN6KnZ8lKvq9PT5YNJN83pZR8ZvYXdx/a2WdddaEeDazs7k/nH5wVuBhYqIu/36lcnexr1SbHdExXfjd2up8OnA4wdOjQL9dWhRBCCCF6OF1V4PpWyhuAuz9jZn2/4Xe/TFjyKgYBr3TxmH5d+F0hhBBCiO8kXc1CvT8zUJfN1xnAX77hd98HDDGzGTO+bkPgmpZjrgE2zWzURYH/uPurXfxdIYQQQojvJF21wG0P7Aj8kHBf/hE4+Zt8sbt/bGY7ATcCvYGz3f1xM9suPz8VuB4YATwLvA9s8UW/+03kEUIIIYRoF7qahfqBmZ0I3Ap8SmShfvhNv9zdryeUtPq+U2vvnVAcu/S7QgghhBBjA11S4MxsNeBU4DnCAjejmW3r7jd0p3BCCCGEEOLzfJUs1OXc/VkAM5uZKOwrBU4IIYQQomG6msTweqW8Jc8Dr3eDPEIIIYQQ4kvoqgXucTO7HriUqLe2HtG+ah0Ad7+im+QTQgghhBAtdFWBGxd4DVgmt98AJgHWIBQ6KXBCCPElfNvV4YUQYy9dzULdorsFEUIIIYQQXaOrWagzAjsTPUg/+x13X7N7xBJCCCGEEGOiqy7Uq4CzgGuJOnBCCCGEEKIQXVXg/ufux3erJEIIIYQQokt0VYH7pZkdBNwEfFDtdPcHukUqIYQQQggxRrqqwM0DbAIsT4cL1XNbCCGEEEI0SFcVuLWBmb6N/qdCCCGEEOKb0VUF7mFgItR9QQghvrOoTp0Q7UNXFbgpgafM7D5Gj4FTGREhhBBCiIbpqgJ3ULdKIYQQQgghukxXOzH8obsFEUIIIYQQXeMLFTgze4fINv3cR4C7+8BukUoIIYRoQTF6QnTwhQqcu0/QlCBCCCGEEKJrdDUGTgghhBBjQNZB0TS9SgsghBBCCCG+GlLghBBCCCHaDClwQgghhBBthhQ4IYQQQog2QwqcEEIIIUSbIQVOCCGEEKLNkAInhBBCCNFmSIETQgghhGgzpMAJIYQQQrQZUuCEEEIIIdoMKXBCCCGEEG2GFDghhBBCiDZDCpwQQgghRJshBU4IIYQQos2QAieEEEII0WYUUeDMbBIzu9nM/po/Jx7Dcaua2dNm9qyZ7V3bv56ZPW5mn5rZ0OYkF0IIIYQoTykL3N7Are4+BLg1t0fDzHoDJwHDgTmBUWY2Z378GLAO8MdmxBVCCCGE6DmUUuBGAufl+/OAtTo5ZhHgWXd/3t0/BC7J38Pdn3T3p5sQVAghhBCip1FKgZvS3V8FyJ9TdHLMtMBLte2Xc58QQgghxFhNn+76w2Z2CzBVJx/t19U/0ck+/xpybANsAzD99NN/1V8XQgghhOhxdJsC5+4rjukzM3vNzKZ291fNbGrg9U4OexmYrrY9CHjla8hxOnA6wNChQ7+yAiiEEEII0dMo5UK9Btgs328GXN3JMfcBQ8xsRjPrB2yYvyeEEEIIMVZTSoH7GbCSmf0VWCm3MbNpzOx6AHf/GNgJuBF4ErjU3R/P49Y2s5eBxYDrzOzGAv+DEEIIIUQRus2F+kW4+1vACp3sfwUYUdu+Hri+k+OuBK7sThmFEEIIIXoq6sQghBBCCNFmSIETQgghhGgzpMAJIYQQQrQZUuCEEEIIIdoMKXBCCCGEEG2GFDghhBBCiDZDCpwQQgghRJshBU4IIYQQos2QAieEEEII0WZIgRNCCCGEaDOKtNISQgghRHNcO+ra0iKIbxlZ4IQQQggh2gwpcEIIIYQQbYYUOCGEEEKINkMKnBBCCCFEmyEFTgghhBCizZACJ4QQQgjRZqiMiBBCCCGKojInXx1Z4IQQQggh2gwpcEIIIYQQbYYUOCGEEEKINkMKnBBCCCFEmyEFTgghhBCizZACJ4QQQgjRZkiBE0IIIYRoM6TACSGEEEK0GVLghBBCCCHaDClwQgghhBBthhQ4IYQQQog2QwqcEEIIIUSbIQVOCCGEEKLNkAInhBBCCNFmSIETQgghhGgzpMAJIYQQQrQZUuCEEEIIIdqMIgqcmU1iZjeb2V/z58RjOG5VM3vazJ41s71r+39hZk+Z2SNmdqWZTdSY8EIIIYQQhSllgdsbuNXdhwC35vZomFlv4CRgODAnMMrM5syPbwbmdvd5gWeAfRqRWgghhBCiB1BKgRsJnJfvzwPW6uSYRYBn3f15d/8QuCR/D3e/yd0/zuP+DAzqXnGFEEIIIXoOpRS4Kd39VYD8OUUnx0wLvFTbfjn3tfID4IYxfZGZbWNm95vZ/W+88cY3EFkIIYQQomfQp7v+sJndAkzVyUf7dfVPdLLPW75jP+Bj4KIx/RF3Px04HWDo0KE+puOEEEIIIdqFblPg3H3FMX1mZq+Z2dTu/qqZTQ283slhLwPT1bYHAa/U/sZmwOrACu4uxUwIIYQQYw2lXKjXAJvl+82Aqzs55j5giJnNaGb9gA3z9zCzVYG9gDXd/f0G5BVCCCGE6DGUUuB+BqxkZn8FVsptzGwaM7seIJMUdgJuBJ4ELnX3x/P3TwQmAG42s4fM7NSm/wEhhBBCiFJ0mwv1i3D3t4AVOtn/CjCitn09cH0nx83SrQIKIYQQQvRg1IlBCCGEEKLNkAInhBBCCNFmSIETQgghhGgzpMAJIYQQQrQZUuCEEEIIIdoMKXBCCCGEEG2GFDghhBBCiDZDCpwQQgghRJshBU4IIYQQos2QAieEEEII0WZIgRNCCCGEaDOkwAkhhBBCtBlS4IQQQggh2gwpcEIIIYQQbYYUOCGEEEKINkMKnBBCCCFEmyEFTgghhBCizZACJ4QQQgjRZkiBE0IIIYRoM6TACSGEEEK0GVLghBBCCCHaDClwQgghhBBthhQ4IYQQQog2QwqcEEIIIUSbIQVOCCGEEKLNkAInhBBCCNFmSIETQgghhGgzpMAJIYQQQrQZUuCEEEIIIdoMKXBCCCGEEG2GFDghhBBCiDZDCpwQQgghRJshBU4IIYQQos2QAieEEEII0WYUUeDMbBIzu9nM/po/Jx7Dcaua2dNm9qyZ7V3bf6iZPWJmD5nZTWY2TXPSCyGEEEKUpZQFbm/gVncfAtya26NhZr2Bk4DhwJzAKDObMz/+hbvP6+7zA78FDmxEaiGEEEKIHkApBW4kcF6+Pw9Yq5NjFgGedffn3f1D4JL8Pdz97dpx4wHefaIKIYQQQvQs+hT63ind/VUAd3/VzKbo5JhpgZdq2y8Dw6oNMzsc2BT4D7DcmL7IzLYBtgGYfvrpv7nkQgghhBCF6TYLnJndYmaPdfIa2dU/0cm+zyxt7r6fu08HXATsNKY/4u6nu/tQdx86+eSTf7V/QgghhBCiB9JtFjh3X3FMn5nZa2Y2dVrfpgZe7+Swl4HpatuDgFc6Oe5XwHXAQd9EXiGEEEKIdqFUDNw1wGb5fjPg6k6OuQ8YYmYzmlk/YMP8PcxsSO24NYGnulFWIYQQQogeRakYuJ8Bl5rZlsDfgfUAshzIme4+wt0/NrOdgBuB3sDZ7v549ftmNhvwKfAisF3j/4EQQgghRCGKKHDu/hawQif7XwFG1LavB67v5Lh1u1VAIYQQQogejDoxCCGEEEK0GVLghBBCCCHaDClwQgghhBBthhQ4IYQQQog2QwqcEEIIIUSbUaqMiBBCCCFEW3DtqGtLi/A5ZIETQgghhGgzpMAJIYQQQrQZUuCEEEIIIdoMKXBCCCGEEG2GFDghhBBCiDZDCpwQQgghRJshBU4IIYQQos2QAieEEEII0WZIgRNCCCGEaDOkwAkhhBBCtBlS4IQQQggh2gwpcEIIIYQQbYYUOCGEEEKINkMKnBBCCCFEm2HuXlqGxjCzN4AXv8U/ORnw5rf4975tJN/XpyfLBpLvmyL5vhmS7+vTk2UDyfdN+bblm8HdJ+/sg7FKgfu2MbP73X1oaTnGhOT7+vRk2UDyfVMk3zdD8n19erJsIPm+KU3KJxeqEEIIIUSbIQVOCCGEEKLNkAL3zTi9tABfguT7+vRk2UDyfVMk3zdD8n19erJsIPm+KY3Jpxg4IYQQQog2QxY4IYQQQog2Qwpcm2Jm45WWQQghhBBlkALXCWbWr/beSsrSGWY2IXCYma1XWhYhRNcxs+nMbLX6GNMT6YnjnvjuY2ZDzez3peUYE2Y2jZnNWFqOCilwLZjZRMBSZjaFmW0LDC8sUmcMAJ4DljezEaWFaUWD/3eX6tqa2axmNmVpebpCD7sfFwIOB1Yxs3FLC9NK7VxNlts9ao6o3X8T51jdo6jJN6C0LF+EmU1lZr162LOBu98P9DWzG0vL0oqZ9QE2BM4ws5lLywNS4DrjE2BJ4DLgR8CjRaVpwczM3V8FngX6AFub2UqFxfqMlM/z/ZZmtqyZ9S4tV52eNmjVqU0Ag81scGFxPoe7u5mtDlwF9DgFrnb+hpjZvGbWx3tIplY+G1cB5wO7AiN72r2Y13cEcKmZHQRs15OshSnfGsDVwOlmdnJpmSqqsc/MFgGONbNZSsvUSiptkwNXAAv1pGejmifcfQmgt5ndXlis0XD3j4GzgLuAn5nZDIVFkgJXUQ2k7v4OcDswKH96at49ghwgVgWOJJTLT4ANclArTk152wnYCXjZ3T8pK1UHtUF2RTPbMa2sPYbaBHoNcIOZ7ZIDblFqitH8wC+A9dz9ETObuqesRuGz87caMUFtBzxsZkMKi4WZ9a49u0sAbwAnAuuYWd+y0nVgZksDPyee3cHAxsBBZjZOQZl61d4PA/YFvg/cDaxgZuOXkq1OXt+VCOV8TULB7FFKnLt/6u5vAFcSynlxS2E1Jrv7J2Y2KYC7rwi831OUuJoRYmFgCmAm4Belr68UOD5nNZoQuBdYBngP2BmYOz+brsSKOc3dg2u7lgGOcPfjgT2AB4GNcnIojplNR5ia1wP+ZmZrm9lmZjZXYdGqQXZF4DjgceA4M9urp7iKzGxeYAdgJHEOlwM2LqXEmVn/mtI7FfA2cB2wuJntTVhCjjCzNUvI10oOqLsCqwC/Jca4t2qfN/r81iakT8xsauBA4Jfuvj7wQ2B3Qokrev+lZaYfMTF9H5gWmJd4TuYBDrQCLt+87/et3f+9iMXr4sAGwKru/q6Zzde0bK2Y2WzAscBPgBmAF4BDzWymwnLVrfpT5PYFwKekDlDSElybe7cnlKLDzGwhd18N+MjMbiolW7W4yud3XsICdy5wEPAY8POSnpIeMWmVxMx61W6gHwE3AAcTD+BPgP7AemZ2HHApMLCAmHsCR9UGgg8Jha2fu/8N+AMwCzDKzKZoWrhOHv5/Ag8TN/n5wEbA2oRruhhm1jstCesDPwA+Ih7CC93905KyAZjZJMDmxCT6lrs/DBwGLAVsaWVizpYBjszFwbHA1MT1HQX8FdgSeAToKVnRbxGK2wbE/beau/8zrXKfTRZNkIP/uWZ2bH73q0Ts6oC0yF1MuKLPBdYoocTVnt3e7v4h8bw+S1zXDd39UuI5mZkYE5tmGkKZ3MXMJgOciCHcBVjZ3f9mZisAh5QY+1r4L3Hu/unuH7r7DwhPzmnVs9ukopSLr8ly8TUncB6wH3AysRAbRBgAGn0uOsPMNiIWDgcTz+46AO6+MjDQzK4pINNUwA5mNkfu6gP8yd3vcfffAhcSOtTxpbwQY70CV03cZrYEsCBwCPAPwv2yGGGufxHoC2zr7v8pIOOuwJuEK2N6otLzM8Beecj/iInhMHd/vUnZWqyXK1vERw0Afg38HviJu3+PUDIXLTxJ9XH3D4AnCEXpSGKS+oeZbWVm3ysoG+7+T+AiQiHa28wmyaDenxNKXP8G5ZoqZfodMIyICT3Z3e8iFLlV3f03xBiyLvBaU7J1hpktaGbLE5Po8oQCspa7P29mixJWwkYtwO7+EfGMzmdmP83dzxHWo6lz+wbiOXmpxCKi5nK+0sx2BBZx9/8C0wGL5TkbDzjE3Z9uSi4L1/xOuYi5IGXYhfCOnEu4sWY2s+8DxwNnlhj78me/tF6+AbwLLJyeHICjgEmAo6E5RSllm5OwXv6QcInvRIx5vYCfER6mFdMy3CjVPJCL6j6Eu35PYsH4N+BgC3q7+6Ipe9NMTIy7a1hknv4NmN/MfgDg7s8TYUz/BiYc0x/pVtx9rH4BlhfpU0JBg1jxbUysRr+X+3r1AFlPIQav2YlJ6jzgz4RCsmZh2XYE/kS4iN4E5qt9tilhkZujxPXNn8OBi/L91oRSvnhuz0s8iCsWkm0V4AAitmySvLZHEhbgSfKYgQ3LdiYxAfQmJp/fARcTlprqmEUJxXytQvdcdf7mB84mYqLmAOYilOB9iBX9o8AaJWRM+WYjAp/3BMbNceUc4DTgIWDJgrLNAFxPhIocApya131R4IEcX9YtINeseR0nrV3j44GDc3tXwpJ0EbBK/X5oWM41iXiyU/M6L53n8yBgN0I5X4SwtE5eQL4zCAVjq5b98xIhGk8AGxW8/ybIn5vns3BL7bPdgN0KyVWNLfPks3oAYQ1egQghOYBQNu8C5ix2/kp9cclXZw96DgavElYaiAy7rXKQnaDgDTRf3jSDc/tYYnKdKbdnr31WYgCznDSvIixEWwO3kQovMGOew7kKXu+VCFfp8Nq+n6bMlwH3UUgBJhYPTwHfIwLvL8hBY1iet58SpvtGFxB5XWcBjq3tuwi4It9PB2xTuw8bv/fye1cjYkB/TCxoricm/tkIK/o+wNJNylh7dieuJu2U54/VhJTXfftKtkLnbg5iobp7bs9CWLlOz3vQ6FCgSowt4+Tz8MvcXoBQ4g4Exst9/Qqev9mIBcyGef89nfvmyPN4Zo7fywB/ASZs+P5bIcfiXxIekflrx1Tz3JJEHOu4DZ+7XoRi+36OJYOAa/OZnYZwoz5IAeWodv6qOWxmQonbO8eWeQml/TxgnVL3n/tYqMDVByLC9bM1sFhun0xMptXgMAUNWz5aZF2TWAVfDlwCHJj7jyEUjxlLn8PcHpg390nATUDf3L8dodSNU/AcjkOUg1kvt/vXPpstH8Y5Ovu/ukmemYAlatuHAgfUtn8G/C7fL0sBq2VNlv6EJeuM3B4v78V7cv9SpWRrOV8j8/3UwLbAzcCCheVaKyfP+wlrzKzAEMIi89MecN6WJ4LsrwVeASbK/TMSlsKzgYkLyNU6tsxHeB1+ltvzE9aunwP9aHBhk/PBIvl+HiLW8qDa59sATwLDqv+FsK4/DczT8HkcSmSyL0SE/+xJLFinJqyuG+dx6xCW625X4KhZ72v7jgCez3O7GOFyvoWwcjV6zur3Xz4fpxIhVIsTdRHPye1qUdar/jslXkW+tCe8CPPs7Xlj30e6WAgl7nVqE30h+frnALFQbs9FrOg2ze2zgXkLyzgtMClhIfoV4SYdNz/bILcHFZRveSJZ4UTg8pbPFqeMS2NFwro2MLc3J6yqk9SOuQGYtoBs1eA1czV4EgrwH4gYo+q4zUn3c+lXPq8X17bnzwng16WeD0JZu49wRc4BnEAocX1z393E4qGU1XIOwupSXePzgFtJCxGxyBhc8JquTATXb16T9wLg8NxekIYXNkQowZb5bIyTr4sIBXhQ7dnZkQjPmDi3ZwFmbVjWQUSA/Xm1fdPmXHcvEYe5XO5fBZitoWu6fb5fmFRyc/tQwvs1VW5PCoxf8P5bnnAtb09YVh8kjClTEYaU/YEBpeQbTdbSAhS6QFMC5+f73XLCHIcOjfpYYObCMo5H+NeXyu1xCWvh0aXPX8qzBxFbdCmwBRHEeQfh9juPsBzOXVC+WYn4jzmAiYj4wV3zs4UJl+pihWQbQJQwGZ4D63VEBlZlEXwMmL6QbMPz+58kYqL65esWaopSIdmqSXI2YIF8P1lOpIfl9nxEqv9ppGWugJwL5Pnql9uDCRfaqNwer+A5HIewjD8P7FDbfw5hWZ2w8DWeDXiJjiLqJ+b+2YHfAEcWlG1cYHJCIV8sn4sLCbfutLXjBuXPUgr65Dk+/wVYu7a/H1GDcNHavia8DrMQi/lJ81m4iLC8LVA75jIiAanxhWsn8m7T8mwsRVj1J8rxpajhpP4aK7JQzWxxM9sp080hMoXMzK4g6myt6ZGduImZDXb3H7v7c8UEBtz9PSJofF8zm8vd/wf8HzDYzMa3hrsb1LMlzWxiIk5hHcLkvR3hjl6JsHxcT8QGPNakjClb78yquo144J4jyiBcDSxrZrcSMT77uPvdDck0wKJAalUIdzaiPMhPifO4D2GZO4Iw2+/n7n9vQrYWOechLAirEyvzuVI2I2LNBmUtpCK4u1vUm/sVsJ+ZnUa4JY8iMpxvIuIIjySelTmblM86CvI+BbxMtMua0N1foCOTsnq2m5SrypYcF/jQ3U8lztECZrZuyrQFUQJj9iZla5FzViJucHd3P45QklY2sxPc/SkicPyiAnJVY984RAmnfxPj3TyEVW4gUcZkEIC7v5w/vUn5zGwJi/7YsxKW6TOBVbMyAB6lTe5y9z9Xv9eQjP2Ic7Q9sAkx7g0E1jazhfKYSwlLf2OZ9l/AhEQN04r7ifFkEnd/2N0fKSNWJ5TWIBvQplchBtRjiEF1i9z/IyLDatHc3pywikzXA2SuLA0DCRPuC8Tg9RxRvqGIPPl+Y2JwOJuODKL5CbfQAU3L1pmMub0WYWUY0bJ/JnKV1/o73SjbhITSeF2ep9lz//rULIHECrWxpADCJXAhGZtCKELP1s7PbMTAegRhfSgW65HyLExkOk9KrJJfJazl8+fnQ4gYn6UJC2K3uq4IZaO6XqsTVr+TiQDtDQll/EginOAFYJmC525NIiTjTkLpmC3P4WlEKZ1SclVj3XJ5792fclZxqeMRMXqnFZZvFcJKOYBwUe5HJAcsmM/GxZRN1Fo57/lNiIoKa6Wc2+QzXiwLO+W7jFhIr53bMxGhLScRMY5/BKYuLGN9nrs2Ze6b484DJa/vGGUuLUA3X5ChwL/I8hDACEJJmzhvoINyQjgv9zd+gWoDxCKEefZzQbk5eKxBIZdfTY7ViSDswwn37np0xHosRCQwTEbDE33tHC5JxCdsQEzyKxO1e1bqAffi2nkvXtqyf/2Uce0CMlVJCZcTVrZZiRIXv6BDiavipYYUkG/c2vtJ894aSlgr78/J82rCvVFlmg4hXOfdGgBNWBVOzPtteA7w3yMU3rvzfA4jypicRhSdLXXvzZ/yLUwkxtxIJHsMJLpBnE2ElZRy+S2VY8p8RGzqUUT9vNlq9+kyBc/fCkTR6iVr+8ZLGU/Pe7LUuTNgAkLZmCvP38N0xJNNTNRQazwhIL+/CkvaiVB636JjwTotYdk/gLLZpuPX9lXy9s2x5coca4qW6Rrj/1BagG6+QCsSq4+d6Eibvpqwvi1HtMiaKQe2Ypa3nACepxabUL+ZesKLjmyqamX8A2KyX5+OWmUls01XJVaghxOrumuJgOPhRFJK40oco6/oZkxZbgSOq+0fn1hYFMnozO8/j4gvqop/HkVkd1axPEUCdvPe2pVwzd9DWDJ7E2Uktqndh9cBs9R+r5GyPzlunEWHS77afwmxMKwsm40+F4Rl9dza9krUFg6E6+9FIh5q8pJjX8pza07s/XN7ZWIRcTBprc79pcok/QLYjLCsbkxkd/4wJ/kiykdNvony5x6EtffPZPx2PhvFZOvsmhFz8b+AoT1Brhx7DwGmqH1Wr3U5SfVZifvvS/+P0gJ080XqkxP7LwlX5LFEB4NjCVfCn4GjCss4DZHxMn9uz0W4gCYtLFfrgzczsQqtZ/xtTqxQ1qH5OmVzEe6q6kH8CblKIiw1PwBOze3NgGVLnD9iobAFsHrtPN6Sk8LchAIwUWfnvBvvt7kYXbmslLjLcsKahwjMPppack+h+/CvOeDXS69sTIQT7JTP8JK5vxE5W87dvMRC5jJqmZFEyYYn8v3nyid0s3wTEAvVS3N7RiI2dU46ssQPJtqMFbmunch8N3BtbXs40Ye1WDIZMD0RR7sioWDemOPMxnQE5ZesQzcjoUyOT/TUfYmO8Ix5Ca9So3UGOxvDCMW3rhRtQ7h5F2hKrjHIunKeo89l1JOlsHr6q7gA3Xhxqgm0Tw4Gl+SgX9V4m4SIEZiloIyLE1k5PyWsHkcTLsorgV1Kn7t8PxfZVSFlvQE4vvb5RsA0Dcs3G2Hh+GFt3wnABbXt+YiA9glq+5qKeausvSMIq+C6RIZVVcR1WsLd/DCp2DV47vYnFMh5+bwSdwaRQAHh1ur28gJfdg8SdZcepCX7MCfRX9ES49igXMPyNSfhpjo3J9HZasfOV/D8Dczz8+vcPpBYLGxBhEI8T+GQjJSrT+39n8lC0bldZBFLLGImy/O1KxFYPzcwQ34+Y8paNGYrZbmMjvIqvyaSPC4gXOaNuv1axpOZaIlBpbbAyvuw8fGlRcYziWL9vQhr/3HAj0pf06/yqgaj7yRVlk1mbC5HBHY+A5zt7u8Wlm0RwjK4BzGhL0sobncSk9NM7r53MQEBM9sTGEkE6d5FKB2PEZavV9x9qwIyDSZiErZ1999kc/qViLpbpwAPuPthZjYfEaO0sbu/2JBsMwKvufv7mZF2EZGhO4hIoukH/Mbd983jB3lmrDWJmR1KKB4/AR7JZ8SIQPfl3X2XpmWqyVY9s/MAH3lkH2JmdwKPuvv2ZjYsP3ug/jsNyjiCKCR7AuG2Wh74mKi+/yJwmbs/WUCuz8Y7d//EzAYQSvkn7r6pmW1GxMMNJpICfteUbC1yTuLR97fa7uPuH+f7R4G/u/tqTZ+/TuRcm/DgPEY8t6+Y2UgivGBfd7+ykFyTAW+7+4dmNguhZP7Y3T/IfsAA/3L3B0ucQzP7MTAK+IRI3tnPoyexQXPZuZ3IVT0faxEK5t8JV/gnRMmVt4gY2t3c/V8lZPzKlNYgv60XY3Cf0BGUWLlTzybrgRWUdTARc/SjSrbaZ8OIm2l4AbnGqb2fg6jr1ouwMGxHBrcTbsBrKBD4TDxgz9BRFPJa4Cf5fiHCMnc14ZYe2bBsxxDxdpWVd3piwrw/txckXAe7F7rv6ivgwwkL5bzVdScs1VcQLrjG3aZ0WLdWzGt8f95zMxDZf38iYlr/TsOWt0o+ImbslnyG10kZp87P5yKsHzOVuL4pw6qEUnl4Pp+TES7ec2vHlGwNuBAxqX+v5fP6GFisSHQ+D4fXtlcjLDU7EwuxFSjUezXH4imJYryH0FHo+Cpgx1LnrEXGRQl3eFWh4GRqRcBLv3IM/hUxz/Yh4lirZJlFCUPAlKXl7PL/U1qAbrhAqxEZnXVXRhVM3Dcnh6IXiMhaujAnpFkqGXOyv4xsDt7UAEFHBuIDdPRVnSu3p8ntyQgL3Ja53acJ2VrkrJTxISnLa8ChY/hfZmzyHNa+/2RC+aiUuOXoiEVagHDll2xeXp8oD8v7cHei/MBjFChT0yLfQoQSOZhor3MMYfGYnrBgrkF2JykkX6+UZyvCWl4N/t/LZ6TxhI/a+LZIPrOjiFIcxxGZ2QOJRc3V9eMLyFktoK8hanGu0/J542NKJzIOIxSin9T2bUkonTtTIOaNDuW3SvKYgQjP+DPhGt+biOVqPF6wdXwlLPtXAJPV9t1ND1Aw8zk4k4xNbTm3KxLhLkXLrXzVV9sX8m0pMLsR4UbbEdjTzFYB8HAn9Hb3j9z9Fnd/rYSMZjajmU0EPES4Tu8AdjSzGd39EyLLc2d3v6pJ07cHzxAK5cVmNoO7P060GlvHzKZx9zeJ+LwJ8nc+bkK2ijwfn6b7aj0igP1lohlydUy/6n9x979V/1uTcrr7DsR5etDMxieqyf/PzC4gakWd6O531u/bJkhZcPePzaxPvt+fyODsS0z0P/ZCbrWUcVxCQVuOmMxfJxTivkQS0hzufq27/6VBmapnd1EzW9PdPyUs0KcRSQBPZzjEPsRi5/0v+HPftmzTmtlUOb7NRriDfu3uFxNxl/8CtnP3t4mwjIMgxsOmZEw5e5nZVEQ9wQvdfc2U59SqkHDK1eiYkrJV13cKM5va3e8hYpKnM7PD8rA/Es/xbe7+YdMyun9WwPo3GUownIhFrtylUxMek0bn8/oclcXKxyVq9n0EzG9mE+ahVwP/aVK2uoy1zXeICgX/MrOj4LNzOymRub2Lu1/b9Nj8jSitQX5bLyLT8KdEZtDkxAr5AgrWX2qRbwTRAPxnRK2o/sRK6jCi4GeRZApaShwQJREeJFylyxHJFbcSg//faLivX4ts8xKDwdDcnp1Qgg/pAdd3fqKe2oDaeXyCyOKchqhNt2zDMlWry3mJcgdDap/1aTm2SNZVTcYqO3JyInbxMjrKmAwhsmKL3HuEUvlkdf0IhfIaYhLdL5+XkQ3L1IfI5puHsDrPlfff76iVjiDcbUVa2vF568xZeS9WFsN9iAVYaavvWoQ1614iLnlJwp32O8Jd/iQFa0kSlvsHCXff0inXHvlZ5ZVoujdsPRlgt3weLiRiy1YiQluOyvntKWrlYJqWkVB0v09HK7v5iPjkuqu8LbJOP/c/lhbgW7xY1xNm+aom2fRE79CrgRUKyzaMWMENIVbJrxCKx4C84Y+kTCHD2QlLYOVunJJQ1v5MJC1MQ2TrbkRYvBov5lqTdfKcxB/u5H94gOyFWfg630DEV1SujtOIoPaSjZlXItxp/yKC7uulLuoxccVqHBEK0lmE4rYokWV8aA6y0+cx/QvJNk0+C0NyeyjRZaEvsGk+G1UR4abd9X2Ihdal+ezOnM/IgYQ7dRZC+Wg8Jq9l8tyWUDLPITLtKwVuMSJx60lg/QZlq76/F5FR+ifCgjUhkZxyOBH32z+vdaM1y3KeOJTI1JydcEteXvt8LsKlu2ptn9V/NijrEkQh7cWIUIwnyQxUopTT4ZRd9K9GhIasScQnV1n28+a994tSsn0r/19pAb7mRalr//1r768F/lTbnpGoVdZomYtO5J2fSEOvKshPTSiWdxJK3LiF5BpBWP+2JlZ3f6AjOeConLhm7CHXuReRqXtdTlCtCRelGtPPTNbwy+3LiQSVqpH5WTRseavJMjexcJiJiC07nwh+LlZbqxMZlyCsC9MTsTLnE1bL6YkEhsspVIuOUJB6E4rHJYRy9BsitODYQudrojw3s+b2eESc4EVEDN7cREmThwgr5kp5XIkiuGsRpXKG5/ZAYqF9fo4vD+cYvXrK2+0LHcJD8ygdC4MheT2rRJSJchzcrdD1nY2wBJ6c1/U6wt18NqG4VZbqA2i4BFEnsq5MLPh3re3bmYjHK1qoN2WpDBKzEQrcvcAbZO1XYl6ev7Sc3+TVdmVEWvzuOxAP4DvAQe7uZnY10d6pah7+WYp60zKa2UDgY8+4GDM7BviLu1+UJTrWIuKO7mlSvhZZhxMxFasD57n7IbXPTiaUo5WIUgSN3Sy1c7gi4SYaQLg3liIGjteAY7xATEolHzEhHUg0uL7Ys8mxmd0LfEBkq1XXvkQ6/+LAwe6+cm7PRgQY3wYc7dFkvQhm1ssjpnFH4E1idXwE0ZfzhXx2xgMGuvvTBeSbj7C+nE7cezsTMYx/JqwNaxET16cNyjQnMbH/l6jb14uYmCBKScxMWMonILrNvA6c4RFL2Ch5/S5Ief6P8ELMQxSMXpGwHP7V3W/J4ydw93caku14ojzSku7+kpmdQihtt7n761luZVJ3P6YJeWpyTU10HNnL3S/OUkT7EQlbCxMK+j3EdT2OKJF0d5My1jGziQkDwKdERYXXcv/uRCLNEsCHTT4jncg4PeFFOtfd5zezBYgqD4e7+wGl5Pq2aLskhhblbUPC7bIjcFYGoY4EPjWzG/NXGg3YrWQ0szWIyfLCWjDsR8DsZjaKUIo2L6W81Wry3JBy3gq8ambTVMd4BORv4O4fN6185Dlchpiw3iTS948iXAfXEib6PQskA3z2fe7+H8JN2htYKwcHCMvR5IR1oTq2289fLSC7T+56FHjFzEaYWaUInUEsetbobnm+SEYiaBjiem5KuK4q5e37hGL8egnlLfkXoXBsmnJs5+5/IBYQxxKTfZPK22yEFeY8onzJKkQx3luI+++nRNeKs4lQkksIS91GZtavKTlrfEC4JI8gLJijiFipo9z9Gnc/xd1vyQQHS5m7DTPrlT/N3X9IWCxvNLNJCBf0isDBZrYd0aXike6UZwy8CbxKLBDwqBE5LhFXuy/hCpyNcK3uWFh56+1RK21bIjt8j1RAcfejiP7j/2v4GanGv/nNbFkzm87d/04swKp5dlzCkn5HU3J1K6VNgF19Ee6zufL9JIQZfipiZXwzUYX6WjpM4YMKyroY4Q4aRFS+fzL3z0OsnK6mJYW+kJz1GKgRxMS0K+leKChXZRk+mporg1DmLs73wynU549Qfn6dr4WJQfVIIgN6L6LlTpFSF4Ql9SSy3yqR3HMKMSmtT2TIbkIo7BMWknEE4TadkojvuZ6Y3GfO8/kIhdxDeS1nyvfT5zU+PJ/l6YlA7ZH1+7QBmaYC/gd8P7f71j47j7DqQ4RmHEZH55QlqPV4LHAupyWSthbN7bly3B6vYTmmIjLXp67t+xWhEL2Q88ksOZccTYGYaWp9cwlr4ElEIt6fWsfjAuevV8t2NT5XMk+Sz8kplC/RVfXE3g94m0hIGZbynUCt53hTz2+3/r+lBfgKF2a9HECrJIUBRFzP7bk9PvBvIsanRI2yerzWcsREuh6hyFVJApVy2bfpG2hM39UyGaxCWGh2okCtqE4Gih0Iy8JEtX23Ea6EIg8fEVR8G6HE7ZgDwlIp0xY5UJRq7zQ/EUu0AZEVdnvuX4awhFyWz0wVeFyiZtlQIjt32dq+pQn3+NVEhl3V07bpgOyBeZ5OqT2z0xOxWmcSCubAQrLdDPyutj1u7f0ddGRmF4mnze+el466kb1bPluLUMwbbe9U++6r8+cUhMfhF/nZocCzwLSdyd2wnFULvnHyOXgDmC739asdV2rsWyjPX72vaSXzpIRyXmTBQCTJTE0kks2UY97jdOgLCxGldZYvdX275f8uLUAXLswCZNNbouzGG3Ro0PPk4DUTYZG5kILWI0LbnyNvnseIldTE+dnKOYFOWmDwryuXGxOZc1uM4fPGCx0T2V7VQDAsr+XchDXmSkIZHpT7HqRQD8KcoG4gg2Bz3zrAP+iw2lSr0iYa009FR/PqeQjle6/a51eRSlxu98tJ7EEa7NNJh4I5aT4bB+T2uLXzNSC3p2jq/HX2Pfn8HkpYYqoi29sTC7HBBe65+mR5LXBXbXvcnLhuAOZtWraWazs7nSQ9pXzjEW7KNZq8ti1yrE/E5N0HnNry2dFETO24FFTgUpZqcd+XTJYpcb5ShnmAI/L9VoRl6y4i6W362nHV2N14olFNhn5ESNgeRILHvWSyVl77yUrJ1p2vdoiBWxf4hZnN79HT8jDgbIt+iI8R1pAzCRfWYR4+71IsR0zuf0i5xgcmNbP1iAfxXHd/y/Ouaorq+8zsR0RV8Q+Avcxsk+pzi36xeMOFji36+h0ALGjRx+9SIvX7esLF9lviATyRuM6HuPurTcnXwt+AfwLzWRRl7uvuVxAT68TQUSS1u6+xmfUl3AXVtfsvEXc3b8ZL4e5rAR+Y2UO5/SGRcLGRuz/cnfLVyftrecI6PhPwAzOb3iNG5pNMVFkht1+vfqe75aolyowws6PN7FzCVXk94X45wsy2JJT0H3uZpI9Pa8/mGsA/zeyu3P4fsDhx7xXp7ZznbzEiweMEd/9b3puffe7u7wGbeBZJbXL8q527Swnr+KvATZaFrfOz3YClqvuxKdlqMs5hZsulLB9lfNlHxPO9FBHX2LRMvQiFdnYzO5OIQZ6PmH8XBEZmggCeSYJeKFnBom/y8YQCNysRNrKuuz9nZgsSNUxn/II/0b6U1iDH9GL0+KzTCWtCZYnbnuhaMH9uz0qBmDc+v3ofSMRpVSnqJxDumMvJmj2tv9PN8k1Juh+JgOIL8/0+hIutNwXcaC0y9ieUs+PyOi+f+1cksq9WIso5DKKjFlej1hnC/L4CEa/ViwjKPonIZFsceIkCMW/EAmGKPG9DiPZT5xNxjPWivQsWvsZzEQuYxXL7AEIxX4SIbX2MAr1/U5bFCVfL8HxeryJq0U1DdH+4kuZd4kPIXqGEBcv4vCXud4SF+j4aLiI8hvvwBeCm2r6S1pjJGL20T/3cbZjPyCaM3u6plJWrF1EbdJ+6HIweE7dowzLV3bWLEnPaPbV9qxLz2p4UjDWvyTMgn4MRhFfi7hxvTiDCHxp32zf2v5cWoAsXZ0siY+g+IoairsS9ASxcWL7liEbvlSvrWGIlWj+m8SKkhPJ2EeEunSgHgquJ1dwVdBSb3bzUOaSjivgAIlD8fsIEXtU6Wp+olddo0G5+dzWQrk64HM8iLDOH5aB7Ru7/GZFx1dgkUDtvfQlF41BCoRxMLGbOAfalpYBm05MUsUCo7ruHCaXc8n7ch0iouJYGExaIMIzNatu7UyvmSZTfeICOjhrVvdjkwmsJojRDVTm+MyXud3nMiALy1Tt8LEwswsYlsmBPrR1XIo62ysg9hVotspZztx6xqN6UghX4CXf94HzdTC4Ca893ifM3ATGfTUwoRDsRC9jbSHdqHrcmseieuOD5G0CHy/l7wP75foa8xpvSsWhs+4SFTs9BaQG+5AItmAP/hLl9GJE9N39u/4BCLahqMi5CKEpnEoHYCxCZQ7PXjml64qwCcrciJvP1c3snQumdM7c3JUpNFLNe0hEU3ofIHDqZjpZFQ4n4nsYCswkrahW32JewFC2X21MQStz2hGJyEWG6n6ipa1w7byvnuepFWAb3JWoyDSbikS6iUBHmmozj5c8JifjUI8mg4tw/gCzI3OD5W4ywFm2b22sRFswpasdcSrafKvDsVpP3MoQbd+NKDj6vxBWJe8vvHkmUZqiST+YmLHGPEvUkS953RixofgrMU/u81RI3X8HzN1Wev/uJ5JhtiBqDxYrO01F8fLOcJx6r3Y8LE5bLevupxhfWtes7C+Gh2TuflcFEclSRtnHFrllpAVovTMv21IQLo+4OuprIGmp88OLzmVXVzT1OTkYn5aT6P3KVX2ACmDZv6spysF5O5usTK5NdiczJEwhLw1ylrjNhir+asLqtQKyeD84H8wJiVbpug3LNSSwQ7s5zODfhUlukkpuIzzsutwcSlpCf0mDmc8owWn9GwuK6L1FWYkYKucZbru1viazOLQgl7hrgJ8BUJWSryTg/YT1dh7A4XEWUkBhGWBuepmzbuOocLks0Ad+kdv9Z671WYIyZOp/R8YhM8bura5r7ns1np5RbcknCsvsiEfe2UO2zokkK1TnKn1sDzxHJbesTCQI7NzmW1GSai+jg0SufgccJZbxKKhon918G/KTEfdeJzKsSGfdPEXUGHyCMPH16wnVu5ByUFqB2MeqZkFPlINE7b6pRwOT52ah8OBudBPIGP4svcYfmhPCDnARKZUuOn5PUNrldZWCtnw/owvl5yYzdFXOAWIpwZ9xGBNdDBJ1eQodbuomMzjmI1fAIwoV1CWGh/FEOZpVVcyShmFSWwwmqzxo6b72JhcLQHFTXJFziCxLK+4EUXoUSK+KHCOv0CUTRW/KZvplwOzfmuiLqVE3I6HG1f8rJc50cb04gJvs/UqbURaW0LUwovEvXtv9TezaKu4KA6YgC1j8kQhyqbN0qfrVk/NushNdmlnweTiGyTHuEZYawtp1AeEcmJ1x/e+Rz/BdC+Z2wkGxTEMrvlDnO7JwyVfVXFyYWOU3PvVMwuuW+tdzUrISh4pq8H/s1KV/R+6m0AJ1crN3zQtxNmJVXJ6w0JxEuoruAGRqWaTbCvL39FxzTaj08h5obtQEZjdGV4K0JhbNywaxPWGc2JZWPgte4f17nqk3XA3mtryMUdKNBCwixYjsBeLy2bwQZlE0E3f+NUI6epqO3Y6OrPKImWT+iOPRz+VwcRiSB3EsodCXiLacjkgDmye01cyJYLuWaIfdPlJNWYwkfhBv8MsJKWlmwriLcuQsSiua6eWw/Mpyg9XluSNZVCev4MUR84E+IWKTFiHi3TZqWqX4uqCkWRFeU5+kIZ1khz2WxxuUpxxxE+aZJc3tyQlm/irSklzp/te3VCWv5n4hEgB1qnw0reH17ES7xB+iwqO5FWPv3J8JHGq3zRoSDPDqm89LJub0U2LvEdS5yb5UWoOXkr0UWqyQsRlfVLuIaROBzowNEDgAP128KwrIwE2kV7OR35svfGVzgHM5MRwD2msRKedPc3ji3J2hYps8F5ebENAkR41Zl7f4+B9rGLFo1eapuCufk9vcJi0wVF7I6Ueh48aZly++vrEQ75/YadFgopyFaKjVe6yjP2+NEfMwrhAI+kuh/eR8dWdArEi3Gxikg4+zE4mA/wuVdr+O3LBF8v0PTcrXIOC6xQF05txciFLidcnsForduKflWIyzPVwNrExakwwjleEci/qjx7hl0KB8TEAp4fyIudT06vDab5TgzU8HzN4JQjk4j3MvjEJbW+wnlfLdSsqV8iwLH5/ujGN0tviUxHzfa+YbIxn6IrFnK55W1ukW9ytrdFfhZyXPZ5KtoM/us/7SYux+a22sQN/ZsRHX2Nd39AzObxd2fLSRjbyKG7DnConUSUUetL2Hu/qW7P9/yOxMSE1W3N5E2s6Xzu242s52J3nRPAR+7+4ZmNpIIeH/Y3U9vsml0yjc5cd62dPc3zKyPZ90gM6vqvI0iTPZHEIryM03J1yLrECIDaxliUF3Z3f9dQpaU57OaWVmX6fuEG+Mp4Hx3f8/MNiJW8Yd41KRrUr7pCIv4Qe5+TtY7PI5wi+9CDMDrEi7pXwJ7uvt1DcvYy90/zWt7NDHRL+/uXqsDtwzwibvf2aRsnch6ClHPb7eUa3XCArK6R9/d0e6JBuVaiOhVux9RdmUSouvN7cTED/CEu/++kHwjiaSEjwlFYzbCEvcRsbjYDNjD3f/UpFw1+YalXDsSym9f4Fp3vybrlI0E/uDut5WQL2UcTHhFTnT3p/JenJvohf2KmfXzqCPZlDx9iQXrFO6+Tu7bC3gfeN/dz8p99TFyIDEW/trdH21K1qKU0BoJN0ZfYtX2DlGAF8Kd9hcipqey2uxMTPIDKJcR1pewMDxPaveE++U0YLUS57Am48bA64TL9BQigL0KzL4+j9mcsH5MWEjGM4nkgMqtUbfE7UtYKx+hZ/SHnZlQOC+v7SvZXmdxOtzgvQhX+HGEoj5O/lw9P2/6+ViesMhsQ8cK+MJ8NqYgLCG3Eb1hVyshY3Xe8ueMKcueFK7MToflaCY64hlXIKxuVfmQOXLsm6SgnNMSfUOvqO0bQYS5FLNo1WQZRlh6p8hzdVnuX46I0Tudhi2XRPzd+rXtHwLH1La3JbwNVaJZ460Va7KsU8lGFNo+sfbZ+UTMau8mZaMjM30oUa5pDyKE6bR8Ps4GDh3D74418W/uhV2ohFn+PCJe7Ojcdwzhx16LCCB/hAKZkjUZqzYhfQlFqK58HMcXxMV1s1z1eLcNiGKyl7fIdx0d8VoTNizfdMBvWs5VPTalqkM3PuFeq5IEihXUrL2fhXCn/rrp89aJXKsTC4eqkXmfHGjvq997hQb/finfiYTlcsccaOsFUsejI+uuaQVzcOv1JayC1xHZzsVqWKUsaxHZsH/ISemHRPHgXxGu3kcpvKghAtp3IhbW36/t/zWpaDYsz4z17yUK8m5BxGDeTUf7pGqcqcbvJhWQ0WIWc3y7BJijdsy1lK9h2ptY2L+X992qhKfph7Vjmk5YmJtYFFaxqENz++e1Y1ajpmiOza/GW2ml26ziRaIUw5VEy5jD3X1Xwi2zGFHWYQN3f7xhGa167+4fp9vvI3c/17PVipkNJR7MR5qUrZLP805OGX9NWOAWSZkq/k70n8TTBdMU7v4SMMjMrsvtHxGT1RVmNqW7/9fMViVcHK+5+z/yuG53v1TX18wmNLNx83vrLYueJaxw/0eUXmmMmmyTmtmE7v5b4truYWabeLifbyXitv5Q/V4T561VTg+Xyk2EVWtpIsljlLu/WTuv73m0Umr62i4MXGlmU+d3f5ru1L8ScTJLEq7AImQLuR2I7NJliOy5SYiYqO2JcIL13P2K+njUNB5t9S4irPsrmdm+ZjYvUcT3+S/85e5hPODZPH8QC9cNiUXNKI/2SesDx+Y9+Ck093zkPXY3EYZxYoY43Eq4nEeY2UpmNjexkPh3EzKNQc4Fifn1kJRvUcIK/H/A5mY2fx7aZFvFmQhX863u/jKAu99PLAwPbTl8BjOboOSz0SNoUlsklIs3iDICgwhX6veJ1cnihCXuJ7XjS1bJHkkGjHfy2dJEMdDG3aeMbnkbRViKtiFWyisS2ZJHEivTR4DZCshYuQSmIwbYVkvcb4lYkKeJSarE9V2LsCqcBWxX21+3YJaqpTaSCLr+E2GFno+IK3uNiMF8hiwuXPJFhxuw6st6GqFsNp6o0CLXUEKxXKGTa/pZ94/CMk5KWIyWyO1xyJ7OPeB6fq64MuGi3IbISLyqJneJbgH9icXgjwkr0sVEJ5dFCMX8UQokVHRyjy1FlIAZSSTDHUBYf28C1mr6uta2JyYWW78i3LkzEorcDIRL9V4K1GokLGs/zff9cnt+YLraMSsRITeNtrfrqa+mL9C8hLn2zbxxziRM3/sRsRZzEFlNVZxZKXfagoSLYKkxfD4h2aKj2IWLVcn9OcH/IgeGmYi4pPcJJbnxbM6afCMJ0/deqXDcXPvsVGJlXJVvaLqLwXiERWEEEStzD/Cj2nElY96G5AA1FxETdRAR99En920NLFny3muRt4p9qwbcM4G9Csu0KNHFoB531DqJlRpbJiKzwIli0fvT0RlldWKB03gcT+3ZWJlQxD8Xc5wT/5ZEcPlaJeSrbS+Zz+1mKddPidCbK4E1mr7GtfO3JGHhXSm3F8t7ca3c7k9HdmdT415VlaC+kJmA6F7wJ8LCejUdHWdKLVy/D/wq319JxML/Jsfq+fI6/5FCMb898VXiIs1BWBIOIlZMdwL/oqO1zVwUKoCb3z9R3tD31vbVb/ySSmW9Pdcv6ajBNDGhEB+X22tTsMUYoWxcyeixKrcDV9a2q0mr6biopfLe+yUdQcTDCGvIngXO1SDg5Nr2ooQLodqeh3BxrFrifNXkqCaoYflaqpPPqsLCjcas1r5/MB2xlMMIRXin2nGNF5glLC/VhDM8n4P7iGziBQnL0U15T/6NjFktdI1HEBnOleWys/I/VUzccTRcTzKf3W0Ia68RpVbuZ/TetlUbvFJ1/J5MGZ8BflyT+1MiE79JeYywrv2TjtZwrV08+hMK52NEOEvvEs9JJRsRx30xmaRAuHmPoiOxZ7JS17cnvsp8aTx4/wbWzu0lKBjQWZsAqp9LEau7g2vHlKwuPi2REn8+sGDu+xVwVu2YYYT1skdk4RCuvnVr2wsSlsHrOjv3Dck0lHCbnkm4YNalo8/u4kTNocFNDw45CZ2X78chQgo2ocMVfSg1N2/BazqCcE9tSSy6Vql9NtozVEC2tYjV+UVEItRgQhm+G9i9kExGJHecTiywbiN6Je+Q9+HihII3gsi2b9SyyuiJO+MQi5qFiZp0axJWmSU7OXZymk+KWooIuTiMCA3ZK6/xwrl/t1L3X17n8XPMmznH4oeo9TUlYuJWblqu/LkHEcpSdczo3fLTiIXkdE3K1yJrJcuKREzt1bXPDqSjUsVY0SKry+et4AVbhFDiGl2VdCJHdZOvRLgzfkC0/FmCWAnsU/wiRXDzlURK9+5EnaNBhBJXrVS+lzd+45l1tXM4P7Fimi7P5+t0FJtdmCjfsEyhczgfEdtRxe5sT2T+rU2HEjdhwWt8C9E2ri9RGuaYnBCGE5aZIgWEU7ZewGQp4+A8Z/dRuKdpTb45CUv+ACK79E4+r5jP0OTkXnsmJiaUs7OAS2qfb5nncNVC56x/PpP9COVoASJx4llCcTsUOJZQNCcqfH1nz7F4zdyejwjDqIpaL1Y91w3L1erW3ZuID7yHjuLka9fHvKbuQWqdeQiv1h1EUtusua93k/J8BbnHI0IJriOy25cnrJrLlpatJ75KX6yFCNPyFoW+v7qJP7tJiCSL/XIyWDwHswMLyVcPIt4kJ6LziFXowjmQ3ZGDxsNkK6NCsg4nrDM/ynM4GVHM9cl8EP9OR3/Hpi1cw4gV8MvAubX92xKxjt+jwZUdYcHYABi/tu8awqp1OrGaX5hwU51I4YDd2kTwcyIG704yOYawYjbWMi6/c1bC9bh7vp+CiPnchIjpqUpJzJ8/Jyp4zqpm4NsTrYjWqx2zLeG2arQmHWFtG5ewbFxAWGeqNmgbkm3siA4fNzOGjjMNyrshoex+1kWGDsV80gLy9K29H1w7dxsQLvL1cnso4ZJetuC524nIVh9OLCLeoGNRXdyaRVjcNmrZ15swWhxJJFesUVrOnvoqL0Cs/BrNlCQsRBPl+/5EhfYlctL8Cx01aPrn/gUKnJfhwMnUsqlyEliLKJD6czpWU5NRqNgnYZ0ZRCiSMxItbB6uTVxz50BWxEVOJM7cRdR2G5IT/OG1z3cE5m1Ypk3osP4NIIJ1KxfBTcAZtWOLZHQyejjBVvn+YuATOuKMFiHcv42dP8L6fB+RuPPznMRXIKyXj9WeieF53RuPp62du1WJRc10RND4jwnLaj20YFDDsk0C7JfvVyEWDafRouQSStPDFKxDRyxQj8j3Iwmr21aEdWnWvL6NKnDE4utH+XM5YoF6LxGWsTahdJxHZNo/TFoNG5Rvrpb764SW7QOICgqNVyfoRNa5Ca/RfF04tkdZCnvKq2grrRJk3ZhDiYy55d39X2a2LbESmIFYPb1oZpsC/3X3ywrIOA5hUdiMWB3/iVgpf5+I3bqIyLoaFzjFC7cNyXN6CBG4uyMRVPyMma0F3OdZ462AXDMTpvjj3P3U3Dc7oRg/5FFzsIRcfYhrOx8xCdzu7j+sffZH4CV336BEa6KanCOIAOIfuvstWSfvOkKJu5uwXB7k7lc3JM+UhEXoDHc/Ie+7XxKKWx8i4eMV4j48kGjLdm0TsnUi63yEdXcbd/9j7htIFAOfE7jN3S+tWn01KNf0hAL0MXH/vUa4c18iui08bWb9iUD8Z939ulL3oJnNSSjqD7j7AWa2IRHi0otoZ3iSu1/fsExLAJsS1vwFiRCbp8zskDzkIqLSwozAm/lZI+cv209tQZS5usKjhuAviDZxe+cx1TPUh7j+Hxe6toOJ3uaTuPt6ua/YWNeuNF7ItzQe7E9MQBeb2XjEKmpmwjLzYhaq3JNI/y4h4weE6+xQwiIzkDDVz0sodtMT1od3abDQYitmtoCZXZMP3aJE25NlU3kbRpzDgaXkIwbZx4HdzGwAgLs/RbgVFjWz2ZouBGlmvT2K8Z5HWJKeZfSCvB8TVt+jc7uU8jYeEYu3bSpv/dz9E3dflXD3Pk/EIF3d4Dl8n7imk2UxaCdiBj8mXM83EFbzBYFd3f3apmQzs5nNbMlUwCGy2W909z+aWW8z6+vubxOWmicIpZMmlbf8vr8TxVo3IhaEbxFK0mzA6ma2A1GO47xSypuZTZRvnyIC8GfLIu+XEIuv54EbKuWtyWfY3e8iYo8nJeaMCfOjnxIhQZu4+z/c/c4caxp7ht39I+LZvI0oGrw8sQDbxMz2NLN+xILxfCKh4qMmr23Ldfo3sdCaxMzWTvl9rC/M+xUZqyxw1WBkZssRLpbViQl0fWJAW5aIpxlI1KJrxLIwJsxsHiI+b1Y6VnYjgYs8Ko739uwM0bBc1XnsRVgZ9iYKVt5CuKCfICb/g5s8hzW5ZiDiVJ7N/WeQwffu/m7uG8+zQ0ADck1KZKQ9mtu93f2TtGj9gLDIPEQ0Yf5fEzJ9EWa2GGHJOpKYKM+tfTYj8Pem7zvraEo/CbFQeIrMZCf6Tr5cO7bR58LMqvqVpwFnenQZWYCY6LfKSb+yaA5MRaRRWhUxMxtEjHkzE5P8R4T1ZiHgHHe/vGkZU66piMX1D9z99nxGZicSev7o7gea2WaElekW4plpRAmun0MzW4SIYfw70X/1CTNbjwgr2CcXYo3QybWdlIhNXYJQeF8m7sUXiXCWdd39yabkq8uYSuW0wIfu/msz2zW3b/foOiO+AmOVAgeQ1rVricELIvB0CBFbZoQb9aNUkIqbdNONsCahgPzC3Z+rfVbKtTHA3d9Pa8PPgDfc/efpItqFCJR9Ogfgbpex7oYys9WJ1fBThJtgI+BDIqNuKLHyfLc75WmRbRzCEjkRcKG7P5j7KyWuD+GSqWrRnVfynsvn40QizmchItbnGnd/zKI91YFE0ePnxvxXuk22uhJ3EnE9R7n7/bmY8ALWomkJq8dR7n5xy2fbpoy3ExP9CUT8WaNuv5o8qxMK71NEqZq3iZIm0wOnuvvD1cKmybGlNrnP4u7Pmtk2RLzg1u5+Zx5zIpHl/n1icTEKuMmj1Vd3yvbZYsBa3N1mtgyxoJ6dqNW4EXCAu1/XnTK1yFdXKlcHnFjY/IlIOFocON3d/5Rj0QTu/mZT8rXIugph7d2dsJZvTSTgbU7Mwb8rbTRpO7wHBOI1+SLckGfk+95Ext+NhNm5VCLAQDLTi1Ag+7V8PjtR9+gCMrOukJy9iNiOvxID6RxEptpfgGGFZJqL6FRgxIrzYWJFtxFhVbiCCCDvTVT0XqSAjLMQJRoOZfRizFUWdB8i5mjOUtc25ZiRcGtUNbXmIRJmLidcvk/RcFB2ylHPxq7O2UDC6nUwZetXLQtcXtteiVjU7ELElq1GuMgvoqMMRolaZbORNfGIDN7r83oPJIoIn0XBciHEIvV2OjKHt877bTjRHeIKmk92G5cIDRlIKOJL5xhYvx8XIZJ7zqzGwELXdzuiPt5BhIK7BVEiZqt8ToplcuY5G5ewAlYdZu6tnltiDt699PjXjq/vvAWutrqrLB4zENlLP/J0E5jZXoSr8kB3v6dh+foSk8BMxEQ/DVEb738tx81FTA6XuPv/NSxjq4l+ZcI6sxyRfTozsRr+lZn18YbcB2ZWuZbPdfeTLAJjJyCyYg8krA2/IWKkRrr7v5uQqyZfZTFaCtiNcJVeB5zvLZa4JuX6IszsNGANomD0/1k0g5+cuD9fdPcHm7LOjOl7qnssLXEXEhP93u7+YXfL1IksMxGK+YOEteNjIrP4CSIcYxci4P4Td/+owXM3CaGQPZ+W0yOI++78dLFtTWQY/5BobTipu5doTl95GS4gEj7+Utu/KZHJOyPwc3e/Kvc3dQ6nJMaQ5QhFboS7P94qg5ktC7zq7k93t0ydyGjEffZrouvIY2lFv5qw/F9LhAjd7O6vNi1fyjiJu//TzA7LXUsR1/rpdIc/6xlmIL4ipTXIJl7EIPBrYlUyGWGpeZbImFyNsL4NKSjf7ITJ+2Vq1e07Oa5vUzLVvrO1R+KRdBTDnZKIn6lcROM3KNcsRDD2iNweh47OHscCO+b7rYhK7UVWd8SK88m8xqsRyQmjWeIK3nfVtZ2TyMKeklgpH5T34zQ9QLZliQzntch2QLm/avM0CdmdpJCc4xJlYc4kO6UQ1t4JiUl05gIy9SMsp4cSFv1JiBjLy2rHTJzX+Ragf+H7cElGb7PXt+XzgfV7omHZ1iKSxc6hcD28mky9Wrb7EGV0htJhoV6HmqeplJyEN+Rpwk2/DeEVqWpILkCU2ekxvZ3b7fWdz0LNYOI9CPPyosSq5C0i9m0pwhV4grv/tWG5Pjv3HtlKvyHiAuZNmavjeteO+6hJGfM7PWM9jiJcMC8A15jZKI/4k33cfTlislq1QdF6EyvP6vz8hri+EBaZoWa2EzGQjXL3JxqUrZ5xNQWxOn/KIzbmEmJFv4uZLdikTDXZesNn13YN4tztTNSm24pIErgBuD6DypuWr7KaDyfixp4jntvv1WT/NK2X/3T3B5qWsSbn/9z9Anffyt03dfcHPCyqg4nJq2/TcnlYIs8GpiLiKz8hPAwzmdnP8ph/EUretu7+3yblq54Niyz2cYjx+H2LrPA+HpbKpcxsZzMbxyN7F89Zv0H5jKjntiox7u1sUR4GM5vIIquzcbwj3ncuM5vKw+PxMmHlr7JiJwXGSS9AqUS3Tz1KSFXldE4nFjrnmFn1fj/POEfx1flOK3BmNhvhdz/N3Q8nCkG+Q8SmvOvuG7r7Ru5+ZW3CbYTaQ7iSmc1PxBgdQLTxGmlm05jZCoRbplHMbAoz27K2a3Yi2+tcdz+ZqP91gJnN1qJUztGQfL093BVDgfPM7EXgz+6+Vx5yD/AAMfCe3OQEX7uPBuTPB4FXzGyjHEzvA35PWG4aL1Njkdn8czMb38wmIBS2jdx9JFGKY3qisvyhRL2oGRuUbXL4TLEch4g5GkkocOMSwdifWCTLUGJiqpNyjjZu5HldnXAJ/iQXZ41gZtXkjbs/RNTIm4lwk35EPA8rmNlxecy/vEAySp63VYnYyrmIuMt/EuV9tjazNQmL0hMeJZVKyLcGYVHdk/AunEe0eVozF4anE4lJjWFmS1vU1sTMdiHCMY40syM8SmP9GzjbzC4grF1HesNlampMX3v/G2BQjtvbEy0rzyBCha5peu79LvGdVeDypngV+AdhgcMj7ugqYjDb1swmrm6epld3+X5LYmDYgTDRT0C0TxqPyAQ8nwhIbZphwLIWNaEA/kcoSwC4++1EsdmP4bMCpeMR/Vq7FauV4EjFbGkiCPbl2ucPufsJhEv1t00OEHXLkZkdSCjgfyYy6I40s5UIa8jJnmVOmsKiFt6JRB2tT9z9HcL1PGfKfjVRqmbT3N7D3e9uSDYDfpUrc3Lifp8Irj+aSAB4xcxWA5YoOeib2QQWxW5HU+LSqj4HUZ5o3yYnp7y2x5vZbtU+d3+MOHczEpa2NwiX4Aq5uC2CRSmanwOb1yyWPyKSo2YmFog7ufutDctVXcdZCcXtfsKCekb+PJ4YC9cDLnb315uUj3CFn2FmOxIW3hWI2MapzOzYVI72IRYP6+X1bxSLmofjAzea2TFmtoW7P0y4eY8FcPfb3P2+XGQ0Nvd+J+kOv2zpFxFgXz10/YksoStqn88HzFJYxjWIGJVBhPKzCxGPMgvhFlwEmLGQbOMRrsdTiXpMEMkK5xOxM0sShUjnqv3OuN0s02AyOxfokz+reI8FiRX8jrXjm+63WsVkLUEUD56bsAT+knCjLkMoTxdSKCOMyNT9IRHL+BwR87Y5UXZliZr85wIDCsg3KeGmPy63FyMyOHfI7UWJeJrlGpZrajridtYgesFeCGzayfXvTYGYLUIRX53IONyh5bP5CeVoxdzu15RctfuuV217WuDS2nb//Nk3fw5o+vzVZFkk77ktc3siQrn8HRmDSUc/1hKN6dcg6rldXJ0zQkE/i0joKtJyqibfhNU5IhYLFxKW1g2IRX+xWPPv4qu4AN3yT4W75Q6iiGFfwkJzHlEZvZRM1Q3emwgyfoAI4Jwq91c11BrtLdmZjLVzuBYRS7NhDiKXEau7e8kerbQE1HajbCcQ1sgxKXELEJbVnRs+Z7NSK29AuIHWzongXmBw7p80f1aTVamBdkvgv0QLNog+nQcQ7tJTiOSeYqVCCCXuXiLmsmrpdCVR6udhCii/xELrt4Tl9FpCURpBxFpuVTuuaHPwfGZXzvPVqsQdDKza9L1HWCTPzfO2D+ES75PXeOfacSsRFprRlL0C53AgkcDz29q+CYkyTr/PzxuTr2VMrp6RJYmYvJHVfmLhfzxlE49WI5S03xI1S6v9+xNz8afUFv16ffPXd6qMSJrmx/HoP9efGMheJipm9yesckd5LVW9IbnqKedVSnV/wp37jLvvnJ9NRChLN7j7i03KWJN1WWKF/IG7X54xF2sSZUIuSTfDlB4lJhotJGxmZxJWmIXc/QPrKCdRuVUXImr53dygTOsT2bD3eVTgXx3Yl7jfVvNw+32PqKn2Ey8Yt2VmixIlQao2QO8SgcRvE7FIcxEFmO9v6tpW35MuvXHc/ZF0wdwE/N7d983tWYC3PcpilGjv9DMitOBhd/9R7luSGFNO8IgNLY6ZjUtYe7cF7nL3oy06a5xFuCzvbVCWOYm2XCcDfyM8I/MSFsy7iYn9eWKxfQANd25JGav7b2HC8/AiEXZzK/Cgd/QonhCY2N1faFK+mpxbEovUF4lzOoS4937kHe3sqjZ9JeSbj1DUf0jEDP4KeMrdt8zPxwGmLnX+vrOU1iC/rRfh2juWWGlW7o5+RD2mK4nVaekV8nYpy0+J2jwDCDfbcbVjSrgNKkV+GOFq2Z+wLhxFWAxXJ8zzPywhI6O7Xy4g3Lfj5PZolrhC8k1KtBJbkHAdXEHE0AwiJq1HCGWu6es6OVmWhoh3PR+YI7dXIdy7u5FWwoL33UqENfqPxKS0Wj4bdxAJSI3L1iJn5RLdL2Waiw7L77KEcjJdgfvucwWO8/04+Sw/QISPPNz0/ZfjRpXlWu0bQMRtXUjEWQ7J5/lwOsoBlRj/1iT6Eu9PuE+XJixtdxKt0UrffzsSpa6WJ6yDP8n9q+W4s3oPkHF+oh5ntd03x70tOjm2iPfhu/j6ziQxeKTF/5YYJNY2szk90umPJKwf03tZ68fGRPuXPYmV1Aru/j4xea1sZkdCmYBO989WoBsTBVEPI5SRJYHDPHrUXUkMIo3JWAsAn8bMhuR3b0J0fnjAosTAx2mJ++zaNn0O3f0tws12PREvdQgRcHwxoawf4NkYvCmZMqB+A2BdM1vNIxutDxFOgLvfmPIOATYws/5NJwbkfbcQMUGtTbjXbsqfMxET67C05DRKLaB9buBoMxvhkcl+B1E/bTaLrOLfE3XoXipw37mZLWpmM3tHb13c/QOPguSLE5attbzB9k4pwyfEvdYLPksuep+wvN0DzOruf3X3Tdx9P3e/vpBldRJge6IO4quE4vGsR+mS4URZp7malKlFvl5ErOoaxLP6DnCYmY2b13RdYrFdGgOmro3THxHK+TutB5aY476r9CktwNfBxtCfzt1vNbNPiPiU7czsWSImZAN3f6ZhGVsHowFEjNuSxOp0x9qEuQhRYLgkixMrutfN7EZ3fzfdg2dY9Ou8smkFOCeoKtnjOTP72N03cPfNzOws4Bkzm9ULlBoAMLOhRImVe9z9KDP7J7FCXtLd9zazyfL/eLPpycmjTtpZRH23xdO19hpRdb865kYzex94yxuuBQaQYQRrEZMn7v4vM/s98YwMd/dfmNnCXq7+4WqEcjk1MG2ONftaVJQ/koiLejwXj41Rc/vNQVgFpzeztT3cy1U4QS+Pbi6NZjrX5SOSecbN3Z4yvW9mDwDHWJS/eK/6vQLKWy+iS8ZrRGzo2sBmHmEPw4mOPYs1Oe61hNsMdPe3zWw8Ijb6WXdfJT/b1sz+7e6/bkq2/N4xzb0PmtldRBmTk4merD8glGPRTbSdBS4nooXNbGBOoEuaWa9KGcoV8aWE63RFIli7ZMzbrBYFH98nAsU3dveVPWIVtiWUuve84diAmoVhRgB3/yXRfmopYKEcNKYhFMsJSlgvzWxxIk1+NaJQ8Dpmdnla3LYkgoqHNS1XyrYc4QpaHTjZzPZ097OJQO1HzWwhd3/Ts3F0oVXnPIQr6F3iHK4N/M7MLjCzq8zsVuAhb7DIce2+65VK4y+J4sZHWhQlfYNwp86Rz01jdaysVpjVokn9QURMzzAiQ3yEma3sUXPrCcJV2TipvK1OJBjdQnT6+HUuZirlrVT9r/q9fg+wp5mt41HUtZJpXCIhqXHFvHb/LUUk67xHxLDuAezi7n+1KFx+JNGrs5Ty9mNgj5zvziFi3+7IzzYj5o0Hm5Itv3dMc28vAHf/CTEmzk2MNT/O+Vh0F94D/Lhf5UWYk7cjqju/yOilLKzl2L6d7W9Q1t2IIobTEi61k4gCkFMR5RsepmBWDhEH9SKRobsbYRnciogH+RW1BtwFZBtMxHAtQBQg/RMRU3Yv4codt3Zs07FHcxDux6G5vRIx4K+X2z8GVi51XVOGWYhuCoOIWNAfExP+/kR7pZlK3XuEhfxYYmKam1A0DyVcQdsQinnTMVuTEOUOxsvt6l6rYgYHEi7xm4FlSl7blOck4Hv5flwicebPZOkhCmZytsi5FvB6jtnrEV1Inio1rqRMqxDJE0vl9lxEXbo/ArsSynnJ5u/bEfF3g3J7IsKdew1RvPfeEs8uXzz3trb3arzt49j4ajsLnEf7pv+jo4fp67XPWq0cH49hf7dQjyGyqCa+PtFC5B/u/k+irtqbRDD5ukQF/MebkK1VRjObmLBQbpTyTE1YHM4hin/OAFzi7tc0KV/KthSh+PYnlNwRwHnu/nLKN4hQQIBmrm9LfNjihNIxIr//ZiKQ/Qdp/TjW3W9q+Z3GMLPBwGHE/f+mRyzo+YRLa0qi08LzTd97Kdswolj19UQ5kx2Ja3kKYbHZGPiZR8xgIyEeZtY3n88fERXj58t77Qai8v5MHjFRlxD1BtdrSrYxyNuLUNqqVmwfEmU6PgJONbNpvZAFzszmrqz6aVG6iojFnJ5oW7glsJcXqsBvkQ25M7C9u98BkM/B4UQCzStE4sW1TclXWbAsiuAakWl/NNDHzHYmFoczEbU5NycWh40/u18y97beb0WyYcc22kaBqykeXe5P15TiVslVfV/G9nwI3OHub+U2RLzMvin7ul6gUra7u5mtSMQmzEqY4W8jVnf9CZflbwhrw1454TaGRRX03Yn0+L/nwPAUsIiZbU8MHht6w71N87wtZWYbuftZhLt5FjPbJA+5J39OWP+dpuSrTzYe7vibCRffymY2vkeixflEWZ3nm5KrE/kWAa5z95vdfQdCQd8J+BdxTm8FtjezKbyBkggWcYpn1JS2kcB1ZjY7oRRNChxnZnsRSvGJRDD5TGP6m90o64IWfZJ7Az8hlMtd8hkZn7DA/Z0ogNykXNXYPCcd9b6qZ8Y8Orfs5+5rA1t7lr1o8vlI+ZYjFn/P0dFFppovpiCKC19SU+waka+m/Myb33kfYek6k7iuzxH33Kfu/oa7/7sJuSp6+tw7NtM2ClwOBj2uP11dPgAz24aIA5iciCHDOwLEv5f/g6dVpDFqq7xhwC+I2l/DCEXJ3f2PhMWhHxH7cSJhcej2Vl4tK935CcVy7dq+e4m4qLWAU71Q83Ji4jzWzDZ093MIV99uZvZrQvE9yRsOaAfImEA3s2XNbCcz24KoyXQ+sWpfKpW4N4BjmlR+a9e2+vkEMEVO9rj7qUQg+RwetQ8vpKOFUbfjEaP4P2KxMqe7H0lYCC8lnpFfEC6j8YFNiIXZZITC2e3UJs9liYXVUSnTFETLqR0tel/+mhgPXydCNBqjWtwQ7vmz3P3FSu7WibwaCwsob0MJpXcK4BOi33Rvd//QzBYEjqFQIlnGkU0C3G9mO7r7SUSM24bufgSx4BpGlChqnJ4+947VfF3fa1MvOmpFzUoEce5CuPpuJFYlMxABqH8gel+WlHUZYtVeVdu/hVixrwVsTdRYa7SFFxFLVnV7mDHl2za3Zycm1H1qx09c6NwtAeyR79ciXKXbtBxTdWFoOuZtAB2tkpYhVsSjcntLQlnapcA5m6L2flXCmrUfoXzcS2SZb0Io4qsTC7Ymq/BXz+6yRDLAmoSCfiLhrlyJiIF7itG7WfRpQLbWmJ2jCEt0FfO2F2Gdnq92zEqEpXW+7pavRbbFifjFIYQLfA9CyZw3780hRB26pfIemK1J+VLGhQjrbvG6fZ3INkM+E4fl9vg5f1xMKB4PlZw76IjVnpfIiN01t8fN8eUJysS8tc3cO7a+igvQJSF7YH+61u8iCgn/hIgRWCH3DSDiF47OSXTOhs/bbISysXbtPP6KUCyH5L5ZgZeAAwtf47mIwNgf5/b3iJjBRltjdSLXLERw+9x0KHHLEqviDXJ7s7y+6zQoVz/CXbVPbv+SWtFMot/pFfl+dyLurcnzVg3+KxMK2jrAv/NcLUoomtcSrt616r/TgGyT5UQ0fW3fb3KivLx6TgmL0jO1sWVWYKYG5BuUY0Z1Do8gLH8z1e7J3QnlY8WabOfSkHJZk23e/O7xiAXiM9SK9/aEF6Fs/JKoH7lY7huHSAxYC1ikyfuvRbblCG/DhLk9B2H5rYqmb0TUzCt17nrk3KtXXp/SAnRJyB7Wny6/v668jU+41yYksulOqQ0K1aTfrc3eO5FvDqJo5ia1fX1y8D8sJ4iZc/9sNJxZVzsvA+moaj8nEWi/W26PIiwP05W4ttX3En1YL8xzWnV+uIgo/Dkx4bL6PtEqpikZxyFW58fk9x9JKr/5+USEy6Npa+Vk+RxMntunE8H2QwlLxzQ1+celwzrc5MJrEcIKeBCRIX4ZkTgBUXj50trkNGPT8uX3zUtYOCrrzDlEluREuT0E2JsOi2HfaiJtUMY1CEvvYYRVZoa8zk9SwCJdk6t6fhckFKTpiJCWfYjs3YV7gGzVzz1zLFmtdm03IeIIv19Kzpq8PW7u1at2fUoL0KlQHTf3woS1Y0bC4nAHcHztuAkp0AaI0ZW33fMBvJ1oEzN3DhQnAot29jsNyDcJUYTy5Nq+28nG2zmBHUIomrM0KSMwfv7sm4PqDYRFplLi5iJczdUKdKpC9+AIYpU5Q24fm9d5GNHS5gS+II2+G+UaTFrTCGXpOmJFPCvwFll+gyiGex8Rh9mUZWt2wsX4a8IiORfR2/dXxEQ/OI/bmCjU2/h1rcm6OFE64m/AGS2fHU/UHRyPlgm3Abn61N5fRSR19KnJdTMZ5kBHqEbjEyhhJbwzx5of5/sp8rOF8rxOX0CuamG4KmH53ZvoBrAYsUDck1CGFyogW33emI0Oy9X3iZiyNXJ7FcJFPnspGemhc69eLdertABjFKyH96dLGTcimrxDKExn5fshRFr60WTPzoblmoJwu+ydg8FVwM9bjhmWx8zRoFyz54R0JrBv7tufaNM1lI4Yt5OJ5IkZCl3X+Qh32qIt+w9L2Z+uDbbW4OQ+DmEJ/AcRjzVpTqTPEzGESxLWj9OIfrGN1VLLCenPRK2vOfPeO4eIm3mIrItXO7crFLq29Ul0YWIRcwgtsZ+FJ8956VDSLs/nt7LEnZ6TaR8aVNwYXbHsS3gdTiKs5HeRC0E6XLpNWwMHtMh2AzAzERf4BDBpfj4Tke08d4n7L2XYgUjUuZhYJPYjSq2cT4QVPEYB5bcmX4+fe/XKa1VagE6FilXdDYSWvyVhwq1cLxNQrpDhYsAWxMqkd05WqxBWuN/R0WB9PEKJmqxh+frWZJiT6IP4Z+CqluPmJpTMgQ3KNmcOAFsRLVZOAVbNzw4mLB4rEnEpZ5SYQGuyjmT0xsz9au+NdJVSJmZmC8KysDth6d2QsDacRsRcDs5Jas4mZST6Hj5U214ir2NfwtJ1DmEtvB8YWeratp6TlPMI4Gc06AL/AtlGEBbouvX+cmKRUylxTcfS9iHqj81LJPGcTyTEXEHE/M6Qxy2X4023xwm2yDc7UVfwFMIaODFRhuPgnCuqUJFR+VmjRWapLQ4IhfKhfE77EUrwPXSEt6xKw4luLbL2yLlXr85f1Yqvx5DlLvoTN/YjRIDnDzxanFT96d7zhls7mdkqRKbao0Qa+vNEKYF1icyhUe7+UdaLmoUI5G2yDVBfYjLqQwxS0xKruVHE+bzJ3f9g0bT+ciI27o8NydaPsAw97u5rZomB3Yi4wMPymE0It9biRPP3xgoIVzWpzGwWIuljXmKVfrC7P5rHLEtMTGc3XcPKzKYGlnD3y3P7GML69vOUsw9RCuN6d/9VU3K1yDguEQf1jLtvnaVM1nf34fn5rIRl5H13f6pEHbAWeft41pkzs8UIC8jHhGW40RI/NZnmJtzP67v74xaNwT/0KMtxNRFmsHoh2ZYglKS3iPIW91q0nNqIWLDeQMRF7dfwszsnYZU8l1hczU+4b+ckFtrLuvvfs37eRcDm7n5vg/LNQFiyLnb32/Ia7+ju29fGnYuJXtOXNiXXGGTtkXOvGDM9opl97UZeijB1X2VmVX+61Xz0/nQbevPdC5YnAp1nc/dXLbosfI+wGq1GmOjnM7N5iXiGUU0qbwCpPPYjztnsRAmO58zsQiIodjkzW4ToDrFdU8pbyvahmW1IFEjdwd1PtihuvHkqlG8RMWV3Av9y9383OcHnvTeccHmvTdTSehlYzczmJxqCn0S4PmhYeetNWD0ONbPF3H03wpW7A+HW2JRw169N9Oq82msNwhuSsY+7/y8XObea2d1EEPb61THu/kz9d5o6h7WxZRhxvvq6+/Xu/rFFB4aP3P3uPM9vNK28tdzn/yIyxFc3s/UIa8zrZnamu4/MWmaNUqvndpeZ/Y5w01cFW+8jsk63IzwOu7r7zU09uzneXUssDM9MBWQvQgnZlSg6u3te2yWBvZtU3pLehEK5rpl9kO9XNrPV3f23ecyrKXPj9PS5V3wJpU2A1Yse3J+OsMh8Qi0riKgZNV2+TiFKXlxK2Xo9EwA3EV0V1qUjq2laYtJ/hLI9CIcSk9QVxGpuGOGu/AURnF0kXZ5oi/UQYeWq9s1GtHm6LF8jS523lKcKGj+ZcG3sQGYYEwuxJWiJ2WtYvioJZZy8/35V+6xoeQFCEXqMUND/zOju8d4lZUsZlgd2z/c75vlbI8eW3ci6YAXkqsaVGehw3y5HKCFVaaLPgvELybgwseDaIbd3Ac7J91MTC5vvV89GiXsxx+WDiWSe6YlQnDeIONH9gAdKjX0pX4+de/X6kmtXWgD3zwb93wKrtOwfSFiPNqzdXKUa01fKxxZE/NE1dGSBVYPbgAJyVYPstMTKuD8RR3YyHVmn4xGZnrPUf6fQeVwgz+OBLfI3Gi/YItPcwIn5ftza9ayu78DC916VWTcBkXF6dA7699Bw0/cxyFddw+q8jUsEP1/YA2Qbh7CUr1nJSliOjiwtW03GeYg+ptvkdqUML5jXeaWC13Q4UdrnVmDj2r6/pfLxKrB44fNXjc1XEQvrGQrLswLRa7XanoJYPF9GxIXOmErSnoSi1FgiWSey9vi5V68vuH7FBYgV3cxEocWqAG6VjTgLBbI4v0DWhXOg+Ftt3zi1wa7UBL864eY7i4gfg3DxnkRYBp+n4cDnL5F3IWLVXK9b1lSw/Rx0BNVvRKyGpyFcpgvXjluWXNUXPE/1YPtqUu9DWGYOJtyUDxGBxyU6LExL1Jvr04mc/YkA6GLZfpWsOWkuV9s3f+4rWr+KrJmX7+chQgn2zO1FUhlZq6B8VbzsXESM4Bl0WLoWTQVkuVLytcg6f47N1fjXaJZuJ+ftEzoKfd9JuJnHJyxap1HQWl6Ts23mXr3GcA2LfnmsnO7ISfQYos5RffV5DTBt6ZPUIvO8OVBsVFqWlGd2oubcKjnoX0RaF3Ig2ZvCNbfGIPcwoj7T9E0pH0Rg86NE8/Q9iCzde4nEidWIThAbEsrvY5Rz2Xd6PlonJCJBpchEQFSwv4XIPj2AmtWDjrplJdxVlXI5S0052o5ITpkkt1chXPbjl5AxZZiBWESsTYeFdw7gfbL7CB3ZnSXO40Q5ltxb27c2kTCwCxme0ZNedLIwLChLZRV8k2y7l/tnJiyXxxJZ4yU9Sm019+rVyXUs9sU9vD/dl8g+lLB+bFFQht5EjMfLwEW5rw8Rk3Ih0Vi9fnyPM3/TbBmTPkQMyla1fVX9pfuI+mRr56R1Dqn0Nn3eagrIskRXj7VpaYNFS9xWARnnImLJJsiJ6LZ8b4Xlqrfvejmv5RF57fchlPejabhG3pjOB7GQOJtYPFR1335JZMM2PnnS4kkgSl78icjGro5ZL2UuVqfsS/6H+sKwtIV1HkKJ2zC3q1CIGcjFRCG52nbu1Wv0V7EyIpkivxORHbSTRybYOERA7zjAKx6p6kXLDYyJTEt/392fbvh7RzsfZrY2MSlt65EB1otQ4g4CDvUenDVUy4Dq9mucZVauAY5y91tr392XaLT+kbsfn+fPm5KrRcZKpuFE1teRhPXoVuAQL5y+X5NvGSIz9jEiHnRjd3/ezOZw9ycLy7gIUYj0OsKNtSZhTdqNsHBNBPzX3e9p8vrWzt2yhBX/XaKe2vpEUebfE5P9cOAUd3+kCbk6kW8lQgl6hahtOSORWPGEd5T8mdLdX2tSvq+CmQ1097dLywGQWfY3ET2LTy0tD7T/3Cs6aEyBqw0QCxJFAp8laldtRWTYnevu9zUiTJtSO4fLE4P+08REtQShxG3tUWuoF1Fj7f2C4vY4zOwQ4AV3P6dl/9aEpWt1b7j8S37/FO7+er4fh6jtdjbR4/SElOuV0hOTmc3p7k+Y2VSElXI6IjngeTNbjXCtjXL3twrIZkTR4KeAd9x9vtw/P5GRPYiwJL3YtGw1GVciakn+mrDODCHc9yOIavfLEzFc1+bxTS8glifiZrcnAu6PIyys8xPlOR5094N7+sTe5MKwi/IsRFj5t2wdexr6fs2931F6NfElZtYrb6BVCTfWMCI1eRYiQ+xFYIe80cUYyHM4gpgEHiGC8Pdz96uISf8SM1vJ3T+V8tYpfwdGmdlcLftfIFxu1rRAqXhcYGZnA7j7B0Qc1NmEUr5mKm+rAUtVdbkalg+LIsd3mdnp7v5/RPzbH4nac6sRiSEnlFDeIE2mUcNtaWAyMzs89z9EZCe+Qrh5G8PMpjSzxWu71gSOc/efuvsoIv7ycuBqd98VWN7dr63VXmtSeetPuHK3At4jnpXzchx5kLAGX920XF+HSr6eIqe7/4WIz/tT09+tufe7TbcW8jWzATkA9DazAcQKfTUi6+8lomr7W2b2P6LB9QfdKc93hMWIAPJZCXfQ0QDufpGZORE/IzrB3c+y6AhwvJmdTNyD/YgA3r1KuChzcN2AKHJ8grvvTChHKwEXuPvLZrYocZ13aHpSSvlWJ2ppnQhsYWYnufuOZrYWYT2ancievL6k1cOioPDLFkV770lR9nf3v5jZM+7+TpOyEFbdpS0KBv+BUMwnqR22N3HvjQe86+7/hGYUDzObnSgT0Rs42t3fMLOniTI1MwDr5LnclHA5X9bdMn2XcfcHm/w+zb1jB93mQs0B4hhCw3+GaHWyAeEWGkG4Wp4zs1FErMW77v5RtwjTxtTM3wPd/e20LFQts0a5+0tpAenvHa2WeoTroCdgZnMQFfbfrO3bmQhyXpooqHmmRwXyxs+bmfV290/MbCIiVuZOYF9ich1OBBhPQc211rB8/Yk6Uce7+9VmNh7hDrrZ3XfJYwa4+/sNx5T1rivctfPYx6PLwrSEpeEUd9+7CZk6kXF24h4bSijg/Yl4xh/kuVyScFOu4e6vNizXBUQXg1mIeMa58+dBRHD71RadZX4F7ObuNzYln/hmaO4de+gWBc56eH+6dqGmvK1G1Ow5jIhZOBW41t1/npPA2UQSw+0Fxe0x1M7bIsAhRFHNF9Kd8GntuAmAT939vQLxRpWMUxAFcP9hZhMS5S1uc/e9c+U8BHjb3f9WSsEk6lad5e53574Vgd/kvl0blmc8z1ZheX0HA7/3jCHM/ZUSN4hof3drg/JN6O7/qSmUQ4iYtyeIcitTEfUa7yKs6Xu5+3UNyjcFETd7tXckJZwAXO7RK3kbYoE4FWHh/6m7X92UfOKbobl37OJbV+Ds843Lq/50fYiA7N8S1cWr/nSNNi5vN8xsaWIC3drd78xJfVVgZyJdfjDRgPu3Y/4rYx8W2V/rEYHXF5eWpzPMbCRR2PMD4EZ3P9rMBhJNw59y960KyFQpltMB/3D3T83sh0Sm7lCPPrWLEffgSkQMZiMLBzObhHDx3UF0LjiXKGeyOFH24C+1Y+vN6pvqzTkOHVa/o3Lsuxx4m4h3W5Aoa/IWoRwN8EgKadJyOQ0RQ/sAcc89ambnEOPxP4kxerr8fPK01Mii3wZo7h37+NZj4LzzxuXvA/Pn4L8eUcW7PxHj82cNEF/IMOI83ZmT0vtmdhVh+p6asCAVsc70cBYgYgXfM7N+3nCT8i/DzJYjCnqOIJTxvdMVeahFosqtZjaXN1wGpmbx3R+4w8z+5e5HpGJ5h5ndRGR1rkk8w03ec9V4tTyxcNkwx4/dgVNyvLk//4/PYkGbei7c/QMz2wi4Jse8JYiuLbulS3dcwiJ8hkdMXKPy5Xe9YmYHEPF3vWvj8cmEgnkqUUpibXd/rmn5xNdHc+/YR3fGwA0l3EF/IPqqbeEFU/jbjZxE5wX+TRT13N8iGPqjtC693/Tk3pOpWY5mIaqxv0MoR7sSBXHv8MJ11OpYZIX9h2intA8h47FEHNxuhGLeuLwWCQBnEgrarsRK/Q7gx0Qm3SREV4OqxMm61UTfjTKNQ7T4ecfM5iEavY8AfuPux+YxPwa2pge4hGpj31Puvlht/yzASMLy9ViD8kwNjO/uf609JzMTrbAWIzo//CGPHUTce680JZ/4dtHcO/bQbWVEciW8HBEYe7u7v2hmfdKsK76ADB7emkjzvhtYzaK466QZu3AeUfNKJDkpDQcuIRSgG4lszsuJiWqFjOcqgtln5TgmAnD33xHujHWJ+mQ3EOUuFgKmKaS8DSIsW6OI2LvFCCvhDER9sH+k3H2AnwGbdbfyliwGbGyREbkxcU2vAQblQodU5M6lBzwXOfYtC8xuZlvW9j8LnNyw8jYLkazwWWmNVOKeI2Jq/wwsnJM+7v6ylLf2RnPv2EO3XlCPGkwrAjub2Y/d/WMvUCi1nTCzyQjlbUbgyTyHPyWqoR9HTKT75H6RWJQHOYyIe/sPUbCyn7ufQkxg++S+IuTEuQbwKzO70sym96j59hywpZmtQxR33a3J1XJNsVySOH9/JApEr0MUHr2esGiOD0ycv/YykTn5cDfLNijfvkhYBI8kenM+Q7SLexNY1qIbCe5+pLvf1Z0ydZU8NysBR2QMYbX/vw2Lsixxnvqb2VqZXFEpcS8R9fvmA9Y0s/Eblk10E5p7xw4a6cSQbplbiB6KL+tGGp16HEKukpYhWhTdC/wsY2sGAf8l+ocq5i1pcZ2uTfS7PAT4fgZgL5nxg4Pc/eWC8k0CXEnEHo0iAsUPzcPWJJICDvMCySgWxWZXBO5x9xst2ov9FniYyKA8BtixYcuRAQcDv/YI9P8lUfrlQeBsjxplkxDJFQOIFmmvj/EPFqL02Jfn8Y9EmZC1PDJNe3kkp9TdqQPc/dEmZRPdT+n7T3QvTbbS6jH96XoStUF0OOE++4QIKF6cmNRfBY7paUH4pamdtyoucGKi0vnEwEweyR5LE5a3rdz9HwVlXZqw/i3nWXbDop7fzITicb+ZTZSBxk1mJFYT+cmEUrlJpUCa2QyES/J/RJ283zQhU4t8BkxL1FAbRZTQ+TGRgboX0VlhReDhhly5X4uSY5+ZTUoo4+8Q7tKD8rkZTYkrIZtoBs29312a9Im/Ax0uG/G5BtI/IwbaXYE9iObW1xOFNvfQeRudPG8rA+eY2Q+ImkfbE2n0O5rZ+sAvgVNLKG811+QiRJ2+tYF1LYoI4+77Af8ADrGoR/ef3N9EuYvqXpoiv3MHosvC3rUYvReJBcT67v6bQvffVMCHxLX9lbv/naih1oeIgXsYeLEnK29Jo2Nf7d6bkCgNsjhRGHp6wppKKm+9pLyNFWju/Y7SmAVOdGDRDHwA8D+PtP4jiKB7J2JS1s/Jqiqa+qor43Q00jVwFBH4vwxwD1Fa5X+Em/Jl4A/u/rtSVoZU3jYGrk85VgW2AW5x95PzmFkzpqtp2YYTC4W7gY/d/SAzO4OIvVzfs61TKcxsSuI6nkYUIj0X6OPu66WSuSaRVNFYkd52IpM79iKy2P/m7ruY2dyEBfODVNqFEG2MFLiGsWhzcj5hcXkZuAKYHFiKyPzbLGO3tibS+c8qJmwPxcymJ2KzTnH3881sPmBLoi3WBe7+Qkn5KsxsR6IH4Unu/kuLchjLElmyv3X34wvJtRChEK0H7ATMBqySVplziftwGa/VUmtIrsoiPaFHN4OjgPHcffs8d6cTVsMRtZhRuQBbyOfhXCI+8O9EO6yHPPrXzktY+X/u7k+Wk1II8U1RWnGDWLQ5uZhYGW8B3A+sQMS9LUsMqs+Z2fxEcdfGg+57OhYdAqYmMhN3MLNJMuPvdMJF9AOLorMlZKtcVzNZFOU9iehrunomU3wA3E7UeyuZLTkgZZgMWATYJpW3Ie6+OdGWrVHlDT5ziy8CXGlmP3D33YGZzGyXPHc7Ei7Bheq/07ScbYARcYF3pCt8WWBpM9vI3R8h6r5JeROizZEFrkEsSjX80d175fYcRID26kTpkNWJtkrTAke42pyMRgZk70dY354nektOCPzY3f9pUeT105Lu5nRNHgrcQFS2H0koHisBR7v77QVdugsTMZV/Jop8/g9YOK1dKwHfB37o7u80LVtNxpmJOm8TE/UOnwFWBg70qGc1WhN78XksakX+DNjJ3f+a+/YAXnD3y4oKJ4T41pAFrkHc/U5ghJk9n7tmJ9rWDHD30wh32y7Axu5+jYJOOzCzSd39LeA1YHd3f4OYpN4ATktL3KNNK29mNlUmIVTu8cOB9enosjCuu/8SuBXY38wmLmg1GkS00nmZyHR+CFjIzJYn4gmvLKW8mdnCFq1+3gQ2B35BJCssQgTgfw9AylsHVitMbbUire7+IGHhPdvMRlm0V/oB8awIIb4jyAJXAItel5cCTwFLZ8kLxfKMgbQonAZc5e4/NbPzicDsg9JiszNwjndzYdlO5JqdyIbc0t3vMLMhRJunxwkr3Kh0iS/u7n+yKN779wblG+2eyvN4LBH39jyhFG1FuKMvdfdrC1oHRxC9a/9DJPM8SdQv+xsRM/i4R1FhAZjZuMD8wBPArIRb/E6IDNM8ZlsirGAW4vn4XRFhhRDdghS4QqTV43x3H5TbfUrEHbUDmXV4GVE37SbC/TeScKs9k/Fm7zcs05xEV4yL3P3M3Dc+0R5rADDE3f9rUQNuL6IW3atNypgyzQ1sSnTv+MTMtgFWI3qG/svM+hFu549LLyIsenbOAhxEKCePA6tXVsHS8vUkMkt3baJl0qJEYsfj+VkvrxVstayVWEZSIUR3IRdqIdz9NmArM3s93WpS3lpIt9oORBunnQir1kvE5L4eUfeNAspbX8Ly9q67n2nRZ/AqwhKyK/ACkUzxPaIW3elNKW9mNpuZbZjJHhC9QWcAbsrM5hcJ99oMAO7+YXXvlVKOKlegu7/q7ncQyvm5wLhEWRNKytcTcffXgP8jlPHbiHZn1Wet1fY1tgjxHUQWuMKk6+h9d/99aVlKY2YzAcOJwpOvEQHsuwHvEskKjwO/d/fHzGwD4J1SbrVMCLiOaNu1JPCKu++Wny1KhyJ3u7vf0IT1KGMmjyLKR1xGKLv7pXVtJSKpYmOijde17r5Jd8ozJhkz23RW4jq/6+7vVMkJtZ99gclKWC17MrXzZ0Bvwvq2Qr7/jbs/nBbr913dW4T4TiMFrocwtruH0iV5DaEUfQhsRMRrXUW4JPcnJqr/I9xFL+TvFTtvZjYUuBl40t0Xz3393P3DulxNymjRneJAYDMiw/klovTGMZltOieRFXu9u1/XhEydyLgKYWG7EegH7OHu/zC1d+oSZrYGkSjzJHAh4UnZmSja+y9gaSIDtcf1hhVCfHvIhdpDGJsnLIuWP6cCh7v7Lu6+B5F9uDKwqbs/7O7rEdal14BJq98ted7c/X6ixtYcZrZl7vvQWloUNSmju99EZHJ+393XAu4DdgduyVIS47j7ju5+XYksZ4sis0sTLvB9gWeBU81sGld7pzFSXau0XO5J1JDsC5yRP48nysKsB1ws5U2I7z6ywIniZEbdGcB27v6emY3r7v/LOK4/Afu6+wV57OQeJUR6DGmJux44zAt1V0g5KgvWIkQ27OXARUT/y5cIxekqd/9LAdl6EyVz7iNcpyMIa9FkRHzjkkQXEhWvHgN5XX9BJD+dla7SzYmetbtnaMEE6ZKWFVOI7ziywImeQH+iuv6yAKm89XP3l4hMzymrA3ua8gafWeLWAA43s+nrNbkalqMKXn+BiI36M3CCu5/t7jcDP21aeatb+TLZZDWivtv2HrxBXON7iOb1Ysw8RVjb1gZw938D5xDdPU606EDyXn4m5U2I7ziywIkeQdasGgYc7+4P1YLZ9yLcfj8pLOKXYmYD3f3t0nLAZ9aa44G13f3V1tISDclQBdwvR8RsPU8oGy8BtxAlWH6Wx6rURQu187cwMB6RQfwPoij0g+7+wzxuQmBi7yE9gIUQzSALnOgpXAG8CmxrZiuk8rY4sB1wR1nRusxn9cpKCwI8SGTtLlVCeYPPepsuR7jHHyGUkP0JRX0VopftvnmslLcW8vytSXTNWJJI/FiUsGIuaGZn5nH/kfImxNhHn9ICCAHhGjWz44ENgJPN7D5gDuBH7n57Wem6RuW26gnuK3f/yMxOA/o0qbyZ2VREjbl78zzMCvzc3c+waDm2MLAlkW28KjB5U7K1G2Y2CVHrcEWia0Zf4Fl3f9ui5+6tZjaXF+z9K4Qoh1yooseRSgBEH9EXFJDdPpjZD4jEk5eJrMhtiT6cS2Rs4yRE3NZe7v5U/o6ubwsZR9mfiA98hIh7+4G7/zWVt7uA91y9YYUYa5ELVfQ43P3/8vVCbmty7+FUiRvufjbwFnAcsDxwFhH3drqZjQdMna96coOuL6OVClkKWNPd3yPqHu4B7JLK2zLAkcB0Ut6EGLuRC1UI8Y0ws/5En9rHzGxBoqDsK2S2JHAa8GOicG9f4Ah3f7KAqD2ajHlbBTiFKMQMcAGh7B6X7dq2IqyXcpsKMZYjF6oQ4hthZjMS9cgmJZS2JdL1vR8wCPi1u/8+65b1cfc35Tb9PGY2DvAbovTLjbX9A4n+sB8B/3D3O3T+hBCywAkhvhHu/jczq1x9JxDlLnD3w81sH2BrM+sH3NyTEj16Epmt+3fgObL5fNWWDZgCuNTdP6iO1/kTQigGTgjxtWgpl3I5kV06CaGwTZ/7jyXKmbwipaNzspPHTwhF7RNgZNZB/DBd0scQHSuEEOIzZIETQnxlWor0LkwoaZcShWa3A/6b7bMWBvbMgHzRgpnNQPQ2/YO7321mjxJu1AvN7B2iJ/Ah7v6PknIKIXoessAJIb4yqbytTliH3gd2psPadjKwIKHI/V7K2xfSjyhgPdzMFnP3d4E1gfOJ/rrbuPuVPaQ4tBCiB6EkBiFElzCzyYE53f0PZjYZobztD8wLHEG0eOoLHJSJCpO6+1sKuO+gZrlcEJgQeJaol7cVkfBxrrvfV1JGIUR7IAucEOJLSXfopsAGZrasu78JHAAMBA4GVgeuJWq//dzMBrj7W6CA+4psaeZmtirwK6Kl2BPALMDVRPLHDma2UEExhRBtghQ4IcSXkkVjf0M0oh+ZStyLwADg6Xz/DnAncJS7v19O2p6FmQ3It73NbHxgF6Kf6V3E+XzG3Z8gEkH+BnzQ6R8SQogacqEKIbpElgLpQxTlnQS4BriXcAPeRTRa37pew2xsx8xmJ1zNLwLPEA3pNwCmAkYAo9z9OTMbBfwOeNfdPyokrhCijZACJ4T4UsxsEPALoqvCfcCPiLIXpwIvEK7T1xW/1YGZzQmcTihtBsxPWNjmBJYFlnX3v5vZAsBFwObufm8RYYUQbYcUOCFEp9STD7Ku25pEWYvTgIeAHwKDgYvc/Y+FxOyRpLXySeBxd18ze8XuRVgwTwB+CzwA9AaWBA5w92tKySuEaD8UAyeE6JQMuB+W7/9OBNrfAewAzAGcSNR9e6OYkD2U7KCwIbCome3g7p8S5VZmcvd/A+sBtxOu523d/RqVChFCfBVkgRNCfI7MmPzUzK4Hpnf3uXP/YGA/wvJ2IHBPKieiE7LLws3AH4iM3S0y4UMIIb4RssAJIT6jZgUaH8DdRwAPm9k9uf0C4fp7AfivlLcvxt3vB5YDlgFud/cXzaxPulSFEOJro1ZaQojPqNUp29HM/gHc4O4bmdmFZnYv4Tbdlsg2faikrO2Cuz9kZisCN5jZu+5+bGmZhBDtj1yoQojPMLNFiMbqxwPzEOUuXnb3o81sf2A84C53/21BMduSjCe8BZiLOKeyXgohvjZS4IQQAJjZ1MAlwBPuvr2ZjQMsDmwN7O7ur5hZb3f/RO2xvh5mNtDd3y4thxCi/VEchhCi4l3gRmB1M1vR3T9w99uJ4PsF4bOODGqP9fV5B0aLNRRCiK+FYuCEGEupNVafn3CVvkjEuL0K7GlmUxKdFmYEXism6HeISvGVAiyE+KZIgRNiLKWWsHAK0cZpCSL27R5gIqLg7J3Apu7+l6q0SCl5hRBCdCAFToixkHThTQBsSdQm+31mSm4IvOHux5rZf4im69U4IauREEL0EBQDJ8RYiAdvEzFZ86Z17Rai08KPzawPcBXwx9weUE5aIYQQrUiBE2IsoQqcN7MZzGye3H0X4S5dLLcfJOLd+rj7P4HzgO3c/X3FbQkhRM9BZUSEGIsws+HAMUTG6YNEm6dFgSmAfkSP04Pd/YpiQgohhPhSFAMnxFiCmc1OdFFYy93/v707jbWjrsM4/n0ohVKgBYNGDS4BIaQlWChLS1QWiYLGtkYQiRpqwCgE5A3IC4QEt0QxLmA0EYUG12gqiESpRbAxghS0LQHKqhRZhIS17FB+vpi58UCkkpZ2zpzz/SQ3d+7MnJn/ua+e/LffrUnOptlU9nxgXXu8pqpWuM+bJA03A5w0BpLsCJxI08M2vT39VWAxsEVVnQXcPnG/4U2Shptz4KQxUFWP0FRZWAYckWRGVT1LM8dtm3bRgiSpJ5wDJ42YiXJX7fFL9m5LchAwn2a49HLgk8BZ1jaVpH4xwEkjJMkUYBZwM7A7MJVmM96aGBZNModmLtzzwO+q6hLnvElSvziEKo2W6TQB7nya+W0PVdWLbdWFAFTVX4FFwCPA3kl2MbxJUr8Y4KQRUlUPAP+mqaBwJfDgwLUaOF4GXAFMAh7bzM2UJG0kh1ClETBQmD40oWwO8N72eHFVrUqyA/BUVT038LltqurpThotSdpgBjhpRCT5EPBRYDXwE5oe9pOBR2mGS98DnFRVD77SMyRJ/eAQqtRjA+Wxdgc+D1wPTKaZAzcZOBd4BjgK+LnhTZJGgz1wUs8l2R84B7ioqn7UDpUuBA4HTq2qG5NsX1VrXW0qSaPBHjip/26h6W37MEBVPQpcCFwFfDfJNODJ9prhTZJGgD1wUs8MLFjYD9gWWAPcC/wRWFFVn2vvmw7sWFV3ddZYSdImYQ+c1DNteJsHfA94F82ebnNotg7ZJ8kP2/seM7xJ0mgywEk9k+R1wAnAYcD9NMOnd1TV48ARwF5JZnbYREnSJmaAk3okyRbAs8ADwHE0ixWOrar7khwBBJhbVTd110pJ0qZmgJOG3MBWIe8G5lXVkzTVFk4DTqmq29si9V8H3jJRyF6SNLq27LoBktavnfP2fuD7wLHt6R/T9LZ9O8klwPHA6fa8SdJ4cBWqNOSSbE1TmP68qloycH4aMB94Hri3qv7sPm+SNB7sgZOGWJJDgLuBO4EX2nNbtfVM3wD8sqqenbjf8CZJ48E5cNKQSrIv8EWaoLYOmJ9kUlU9l2Qf4JvATl22UZLUDYdQpSGU5G005bFuq6ovJNmOZhj1YWAtsD9wdlVd3GEzJUkdMcBJQyjJbsBJNBv1nlRV17Rz4Q4Ftgbuq6rlznmTpPFkgJOGwEB5rH2A6cAdwDM0q0t3BhZV1XVdtlGSNDycAyd1LMkWbXg7HPgZcABwM/AO4Dc0tU5PTDK7w2ZKkoaIq1CljiSZWlVPAZOSTAVOoaln+mbgXzTz3x5K8gzwCZoKDJIkOYQqdSHJHjSrSNcAt9EUpD8aeCPwAeCYqrozyTHA5cATVfV8R82VJA0ZA5y0mSWZAfyAJrQFmAX8E5gBHAwcXFV3J9kb+CmwsKqWd9JYSdJQMsBJm1GSrYDVwE1VNa8tTn86zXSG84DLgL8Dk2hWoJ5ZVZd21V5J0nByEYO0GbUVFD4GzElyYlW9CDwF7FJVjwJHAVcBfwE+U1WXThSzlyRpgj1wUgfaKgtLgWXANOBTVbWm21ZJkvrCHjipA1V1PXAIcBBwVVWtSbJlO6QqSdJ6uY2I1JGqWpnkMOD3SZ6oqm913SZJUj84hCp1LMkBwBXATOCedl6cJEmvyAAnDYEk06rq8a7bIUnqB+fbSMNhLTQ1UbtuiCRp+NkDJ0mS1DP2wEmSJPWMAU6SJKlnDHCSJEk9Y4CTNFaSrEuycuDn7RvwjAVJZmyC5knSq+JGvpLGzdNVNWsjn7EAuAy4+dV+IMmWVfXCRr5XkgB74CSJJLOTLEvytyRLkrypPf/pJNclWZVkcZKpSQ4E5gHntD14uyb5U1vfliQ7JbmrPV6Y5FdJfgv8Icm2SS5on7kiyfz2vplJlrfPuyHJbt38JyT1hQFO0rjZZmD49OIkk4HzgCOrajZwAfCV9t5fV9V+VfVOYDVwXFVdDVwKnFZVs6rqzv/zvrnAsVV1KHAGcGVV7UdTC/ecJNsCnwW+0/YM7gvc89p+ZUmjxiFUSePmJUOoSfYE9gSWtvsoTwLuby/vmeTLwA7AdsCSDXjf0qp6uD1+HzAvyant31OAtwLXAGck2ZkmNN6+Ae+RNEYMcJLGXYCbqmru/7i2CFhQVauSLAQOfoVnvMB/RzSmvOzaky9710eq6taX3bM6ybXAB4ElSY6vqitf/VeQNG4cQpU07m4FXp9kLkCSyUlmtte2B+5vh1k/PvCZte21CXcBs9vjI9fzriXAyRMl05Ls3f7eBfhHVZ1LMzy710Z9I0kjzwAnaaxV1XM0oetrSVYBK4ED28tnAtcCS4FbBj72C+C0diHCrsA3gBOSXA3stJ7XfQmYDNyQ5Mb2b4CjgRuTrAT2AC56Db6apBFmLVRJkqSesQdOkiSpZwxwkiRJPWOAkyRJ6hkDnCRJUs8Y4CRJknrGACdJktQzBjhJkqSeMcBJkiT1zH8ADwXaRwj9fVIAAAAASUVORK5CYII=\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" }, { "name": "stdout", "output_type": "stream", "text": [ "MSE: 0.00034\n", "RMSE: 0.01846\n", "MAE: 0.00692\n" ] } ], "source": [ "best_model, feature_importance_df = ML.perform_linear_regression(splits, 'Xar_train', 'yar_train', 'Xar_test', 'yar_test', save_df)" ] }, { "cell_type": "markdown", "id": "7bd6a002-4551-4bac-88f6-e2e0a826c9ed", "metadata": {}, "source": [ "#### For higher degree polynomial fitting:" ] }, { "cell_type": "code", "execution_count": 19, "id": "1c7a5dc5-0f3e-4687-9b12-7450f9fbdfd0", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Best Degree: 1\n", "Minimum MSE: 0.00034\n" ] }, { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" }, { "name": "stdout", "output_type": "stream", "text": [ "MSE: 0.00034\n", "RMSE: 0.01846\n", "MAE: 0.00652\n" ] } ], "source": [ "best_model, feature_importance_df = ML.perform_poly_regression(splits, 'Xar_train', 'yar_train', 'Xar_test', 'yar_test', save_df, range(1, 3))" ] }, { "cell_type": "markdown", "id": "12580246-e7f8-47fc-98ee-83dc7fdf5aa4", "metadata": {}, "source": [ "### Vulnerability" ] }, { "cell_type": "code", "execution_count": 20, "id": "7ef2a750-1d72-4dca-ba46-7982c983c642", "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" }, { "name": "stdout", "output_type": "stream", "text": [ "MSE: 0.00016\n", "RMSE: 0.01252\n", "MAE: 0.00176\n" ] } ], "source": [ "best_model, feature_importance_df = ML.perform_linear_regression(splits, 'Xvr_train', 'yvr_train', 'Xvr_test', 'yvr_test', save_df)" ] }, { "cell_type": "markdown", "id": "a5fd71bc-e299-4d05-aa27-e30627c3c1b8", "metadata": {}, "source": [ "#### For higher degree polynomial fitting:" ] }, { "cell_type": "code", "execution_count": 21, "id": "625250df-d68c-4d97-8f4b-d95734d2ddf5", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Best Degree: 1\n", "Minimum MSE: 0.00016\n" ] }, { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" }, { "name": "stdout", "output_type": "stream", "text": [ "MSE: 0.00016\n", "RMSE: 0.01252\n", "MAE: 0.00183\n" ] } ], "source": [ "best_model, feature_importance_df = ML.perform_poly_regression(splits, 'Xvr_train', 'yvr_train', 'Xvr_test', 'yvr_test', save_df, range(1, 3))" ] }, { "cell_type": "markdown", "id": "01b3bfde-1fe3-4e31-9f8f-64811db8e568", "metadata": {}, "source": [ "### Resilience" ] }, { "cell_type": "code", "execution_count": 22, "id": "30eacae0-3d5c-4ab3-860f-7254a3087086", "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" }, { "name": "stdout", "output_type": "stream", "text": [ "MSE: 0.00052\n", "RMSE: 0.02278\n", "MAE: 0.00530\n" ] } ], "source": [ "best_model, feature_importance_df = ML.perform_linear_regression(splits, 'Xrr_train', 'yrr_train', 'Xrr_test', 'yrr_test', save_df)" ] }, { "cell_type": "markdown", "id": "e2294226-003f-4b9d-b94f-c4df64c060f4", "metadata": {}, "source": [ "#### For higher degree polynomial fitting:" ] }, { "cell_type": "code", "execution_count": 23, "id": "fb84408e-1061-4571-bfb0-3955805e61d2", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Best Degree: 1\n", "Minimum MSE: 0.00052\n" ] }, { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" }, { "name": "stdout", "output_type": "stream", "text": [ "MSE: 0.00052\n", "RMSE: 0.02278\n", "MAE: 0.00508\n" ] } ], "source": [ "best_model, feature_importance_df = ML.perform_poly_regression(splits, 'Xrr_train', 'yrr_train', 'Xrr_test', 'yrr_test', save_df, range(1, 3))" ] }, { "cell_type": "markdown", "id": "363f9af5-284c-46bd-8de1-3df993f543ef", "metadata": {}, "source": [ "## Ridge Regression" ] }, { "cell_type": "markdown", "id": "65eb13f6-2180-465b-b834-80cb9b56cbd5", "metadata": {}, "source": [ "Ridge regression is a linear regression algorithm used to deal with multicollinearity in data. It adds a penalty term to the sum of squared errors that forces the model to choose smaller coefficients for correlated variables. This helps to reduce the variance in the model by shrinking the regression coefficients towards zero.\n", "\n", "Pros of Ridge Regression:\n", "- Helps to deal with multicollinearity in the data\n", "- Can improve the stability and generalization performance of the model\n", "- Can prevent overfitting of the model by reducing the variance in the estimates\n", "- Works well when the number of predictors is larger than the number of samples\n", "\n", "Cons of Ridge Regression:\n", "- The selection of the penalty parameter is crucial for the performance of the model\n", "- It assumes that all predictors are relevant to the outcome, which may not always be the case\n", "- It does not perform feature selection, meaning all variables will be retained in the model, which can lead to overfitting" ] }, { "cell_type": "markdown", "id": "d0b2ee29-59ce-448f-a6b7-d37352c330cb", "metadata": {}, "source": [ "### Adaptability" ] }, { "cell_type": "code", "execution_count": 24, "id": "7574b5c7-1087-48ef-98cd-66bc47d581c3", "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" }, { "name": "stdout", "output_type": "stream", "text": [ "MSE: 0.00034\n", "RMSE: 0.01846\n", "MAE: 0.00692\n" ] } ], "source": [ "best_model, importances = ML.perform_ridge_regression(splits, 'Xar_train', 'yar_train', 'Xar_test', 'yar_test', save_df)" ] }, { "cell_type": "markdown", "id": "62a61628-d470-460c-9065-65f37e557419", "metadata": {}, "source": [ "### Vulnerability" ] }, { "cell_type": "code", "execution_count": 25, "id": "fca6b113-59fe-43cf-b548-fb212886bcec", "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" }, { "name": "stdout", "output_type": "stream", "text": [ "MSE: 0.00016\n", "RMSE: 0.01252\n", "MAE: 0.00176\n" ] } ], "source": [ "best_model, importances = ML.perform_ridge_regression(splits, 'Xvr_train', 'yvr_train', 'Xvr_test', 'yvr_test', save_df)" ] }, { "cell_type": "markdown", "id": "583a5f6b-45f2-4052-834d-05ee7058f28a", "metadata": {}, "source": [ "### Resilience" ] }, { "cell_type": "code", "execution_count": 26, "id": "c1212069-7610-4c9f-a3c2-34c30b93c23d", "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" }, { "name": "stdout", "output_type": "stream", "text": [ "MSE: 0.00052\n", "RMSE: 0.02278\n", "MAE: 0.00529\n" ] } ], "source": [ "best_model, importances = ML.perform_ridge_regression(splits, 'Xrr_train', 'yrr_train', 'Xrr_test', 'yrr_test', save_df)" ] }, { "cell_type": "markdown", "id": "48831915-5c5c-470a-8ba3-736f95541a8d", "metadata": { "jp-MarkdownHeadingCollapsed": true, "tags": [] }, "source": [ "## Support Vector Regression " ] }, { "cell_type": "markdown", "id": "401cca2e-244f-429f-80ac-4aaab6f9d448", "metadata": { "tags": [] }, "source": [ "### Adaptability" ] }, { "cell_type": "code", "execution_count": null, "id": "f92fde25-72a1-49c4-8723-ebabe40b7fa6", "metadata": {}, "outputs": [], "source": [ "best_model, importances = ML.perform_svr(splits, 'Xar_train', 'yar_train', 'Xar_test', 'yar_test', save_df)" ] }, { "cell_type": "markdown", "id": "1c8dfe1e-e617-4d2d-a321-2893adaaa649", "metadata": { "tags": [] }, "source": [ "### Vulnerability" ] }, { "cell_type": "code", "execution_count": null, "id": "94bb61f3-475e-47b1-82ed-306ee3c5b47f", "metadata": {}, "outputs": [], "source": [ "best_model, importances = ML.perform_svr(splits, 'Xvr_train', 'yvr_train', 'Xvr_test', 'yvr_test', save_df)" ] }, { "cell_type": "markdown", "id": "7acfb9b4-0ea9-42df-8cbe-b2dbe5313501", "metadata": { "tags": [] }, "source": [ "### Resilience" ] }, { "cell_type": "code", "execution_count": null, "id": "c5e13d6e-b061-4926-839b-e38700533023", "metadata": {}, "outputs": [], "source": [ "best_model, importances = ML.perform_svr(splits, 'Xrr_train', 'yrr_train', 'Xrr_test', 'yrr_test', save_df)" ] }, { "cell_type": "markdown", "id": "a500ffc7-7931-4559-a084-d31784296464", "metadata": {}, "source": [ "## Random Forest Regression" ] }, { "cell_type": "markdown", "id": "8fca82c1-c9cf-48fc-8d17-e2fafab4474c", "metadata": {}, "source": [ "Random Forest Regression builds a number of decision trees on a randomly selected subset of the training set, and then averages the predictions of each tree to produce the final prediction. The randomness in the selection of features and samples reduces the variance and overfitting.\n", "\n", "Pros:\n", "- Handles high dimensional datasets well\n", "- Can handle both categorical and continuous data\n", "- Tends to have good predictive accuracy\n", "- Provides a measure of feature importance\n", "\n", "Cons:\n", "- Can be slower than other regression algorithms due to the large number of trees\n", "- Can be difficult to interpret the relationships between the independent and dependent variables\n", "- May overfit the training data if the number of trees is too large" ] }, { "cell_type": "markdown", "id": "9ec6af2c-da2a-454d-b1f6-0848faffa4c4", "metadata": {}, "source": [ "### Adaptability" ] }, { "cell_type": "code", "execution_count": 27, "id": "4bc9bcb2-b18a-41ec-96fd-1d4599b07686", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "MSE: 0.0003194777055431521\n", "RMSE: 0.017873939284420548\n", "MAE: 0.005748392591169003\n" ] }, { "data": { "image/png": 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MzMxaA98AwKwCEXEjRd9dY2ZmZma15ZkZMzMzMzOrS56ZMWuj+nTvQ8PwhlqHYWZmZtZsnpkxMzMzM7O65GTGzMzMzMzqkpMZMzMzMzOrS/6eGbM2yt8zY2ZmtmJW5festHX+nhkzMzMzM2tVnMyYmZmZmVldcjJjZmZmZmZ1ycmMmZmZmZnVJSczNSLps5L+KulZSc9JuljS6jWMZz9JMyTNljRT0n6rsO/xVdY/W9KwSsolzZO0/orGmGtvH0k/XkltjZbUN/e8h6RZFez3N0lrp58froxYzMzMzOqRk5kakCTgTuDuiNgC2BLoCvxyFfXfvuj5dsCFwL4R0RPYB7hQUq9VEU9E7LIq+lkZIuKeiDi/xjF8IyLeAtYGnMyYmZlZm+Vkpja+DLwfEdcDRMRi4FTgSEmd0yfvvQAkTZX08/T4XEnflzQofap/e5pJuTklSEjqI+lRSZMljZS0USofLelXkh4FTi6KZxjwq4iYm+KZC/waOD3tu7mkf0iaLmmKpM1S+RlpFme6pPNz/fRNj9eXNC89Hppmoh6QNEfS8ELnkhbkHp8uaVKaJTonV35m2u8fwFbNGXRJp0malX5OSWXLzIZIGibp7PT4JElPpVj+nDuOS9PjEZIukTRe0vOSDkzlq0m6XNKTku5Lr+eBVcY6VNKdabyelfTb3LbCbNP5wGaSpkm6QNJGksak57Mk7dqccTIzMzOrF+2brmKfgC8Ck/MFEfG2pP8DNgfGALumROAjYECqNhD4I7ARsH1q50VgHDBA0hPA78lmWF6VNIRstufItP/aEfGlMvFcWFTWAByfHt8MnB8Rd0nqCKwm6evAfsBOEfGepHUrOO4dgW2A94BJku6PiIbCRkl7AlukegLukbQb8C5wcDrm9sAUisYv51RJ3809757a7gMcAeyU2n4iJXZvNhLvj4FNI2KRpLXL1NmI7HXpCdwD3A58C+gBbAtsCDwNXNdIP+X0JjvmRcAcSb+PiH8VxbdNRPQGkPQ/wMiI+KWkdkDnZvRpZmZmVjeczNSGgFLfslQoHwucBMwF7ge+Iqkz0CMi5qTZlokR8W8ASdPITp7fIksWHkwTNe2Al3Lt31pFPAJC0prAZyLiLoCIeD/1ORi4PiLeS+VvVHDcD0bE62n/O8mSgIbc9j3Tz9T0vCtZcrMmcFehL0n3NNLHRRHxcWJWmBlKfd0VEe/m+t+VLAEpZwZws6S7gbvL1Lk7IpYAT0n6VK6v21L5fyU9UmbfUu+BfNlDETE/xfsUsAnwrxL7FEwCrpPUIcU1rbiCpGOAYwDo1khLZmZmZnXAy8xq40lgmW8wlbQW8DngObKT0r5kJ9tjyE7uj2bZ2YhFuceLyRJTAU9GRO/0s21E7Jmr926l8QA7AE+lNkspl5B9xNL3VceibcX1SyVQv87Fv3lEXFumbrXKHUc+Xlg25r2Ay4A+wGQVXWuU5F8HFf1uyuvAOrnn6wKvlWm78BqXFRFjgN2A/wA3SfpeiTpXRUTfiOjreRszMzOrd05mauMhoHPhZDMtCfp/wIiIeC8iPiD7BP7bwONkMzXD0u/GzAE2kNQ/tdtB0hcriOdC4CeSeqT9egA/Bf5fRLwN/Fvp7maS1kizRKNI1/ik8sIys3lkJ/8AxdeJfEXSupI6kS1RG1e0fWRqs2tq8zOSNiRL6PaX1CnNFH2zgmMqNgbYT9k1SV2A/cnG82VgQ0nrSVoD2Dv1vRrwuYh4BDiD7GL7rhX29RhwQLp25lPAoDL1RgPfVZpGAw4Hys3ilPIO2awVKeZNgFci4mrgWrKE1MzMzKzV8jKzGoiIkLQ/cLmkn5EllX8jSyAKxgJ7pOtRxgKfpYlkJiI+SBeaXyKpG9nr+zuymZfG9psm6UfAvWmJ0ofAGbllSocBf5D0i7TtoIh4QFJvoEHSB7n4LwT+Iukw4OGirh4DbiK7LuhP+etlUhyjJH0BmJDO7xcA342IKZJuBaYBLzQ1DmWOcYqkEcDEVHRNREwFSMf1BNmyvtlpezvgj2kcRbZ87a2leUej7gD2AGYBz6S255eodxXZtTbTJQXZkrufVHFMr0sal25g8PfU3+mSPiQbu+VmZszMzMxaE0Ws6Oods6ZJGgr0jYgTah3LqiCpa0QskLQeWQI1ICL+W+u48tRdwbG1jsLMzKx+xXCfR68qkiZHRPFlEZ6ZMfuE3JfugLY6cG5LS2TMzMzMWgMnM7ZKRMQIYESNw1hlImJQrWMwMzMza+18AwAzMzMzM6tLnpkxa6P6dO9Dw/CGpiuamZmZtVCemTEzMzMzs7rkZMbMzMzMzOqSkxkzMzMzM6tLTmbMzMzMzKwu+Uszzdoof2mmmbUF/lJDs9ah3JdmembGzMzMzMzqkpMZMzMzMzOrS05mzMzMzMysLjmZMTMzMzOzuuRkppWTtKDo+VBJl67kPv4mae2V0M4gSfcVlY2QdGAT++0j6cfp8X6Stl7RWFoqSX0lXZIer/TX0szMzKyetK91AFb/IuIbNe7/HuCe9HQ/4D7gqVXRt6R2EbF4VfQFEBENQMOq6s/MzMysJfPMTBsmaRNJD0makX5vnMqXmQ0pzO5I2kjSGEnTJM2StGsqnydpfUk9JD0t6WpJT0oaJalTqtMv9TNB0gWSZjUj3nmSzpE0RdJMST1T+VBJl0raBdgHuCDFuJmkkyQ9lfr+c4k2h0r6q6QHJM2RNDy37buSJqa2/iCpXWE8JP1C0hNA/6L2lutP0nppLKamdl6QtH6JWBZI+o2kyZL+IWlHSaMlPS9pn1RnudmrVL6BpDskTUo/A6odXzMzM7N642Sm9euUTsanSZoG/CK37VLgxojoBdwMXNJEW98BRkZEb2A7YFqJOlsAl0XEF4G3gANS+fXAcRHRH1iRmYzXImIH4ApgWH5DRIwnm6E5PSJ6R8RzwI+B7dMxHlemzR2BQ4HewEFpKdcXgCHAgHS8i1MdgC7ArIjYKSIeK2qrVH/DgcciYvsU38Zl4ugCjI6IPsA7wHnAV4D9WfZ1K+Vi4KKI6Ec25teUqiTpGEkNkhp4r4kWzczMzFo4LzNr/Ramk3Egm4kACl841B/4Vnp8E/DbJtqaBFwnqQNwd0RMK1Fnbq58MtAjXU+zZko2AP4E7F1i33LfbJYvvzPX9rdK1C02A7hZ0t3A3WXqPBgRrwNIuhMYCHwE9AEmSQLoBLyS6i8G7qiiv90KsUbE/ZLeLLPvB8AD6fFMYFFEfChpJtCjkWMEGAxsnWIFWEvSmhHxTr5SRFwFXAXpSzPNzMzM6phnZiyvcHL7Eem9oezseHWAiBhDdmL+H+AmSd8r0cai3OPFZAmzStQr5XVgnaKydYHXSrRfaLspewGXkSUmkyWV2qf4pD7IYr4hzfD0joitIuLstP39Rq6TKddfJYnDhxFRqLeEdKwRsYSmj3U1oH8u3s8UJzJmZmZmrY2TmbZtPHBwenwoUFgyNY/sZBxgX6ADZNfYAK9ExNXAtcAOlXQSEW8C70jaORUdXKbqs0D3tMSr0F+55WzlvAOsmfZfDfhcRDwCnAGsDXQtsc9XJK2bru/ZDxgHPAQcKGnD1Na6KZ6yGulvDGmJmqSvs3zCtjKMAk7IxdL7E+jDzMzMrEXxMrO27SSyZWOnA68CR6Tyq4G/SppIdlL/biofBJwu6UNgAVBqZqaco4CrJb0LjAbmF1eIiEWSvgtcL6kj8CHw/YhYrm4j/pz6OYksabpWUjeymZaLIuKtEvs8RrbMbnPgT+mOYUg6CxiVkpQPgeOBFxrpux3wx+L+JJ0D3CJpCvAo8H9VHE+lTgIukzSD7N/1GMpfI2RmZmbWKmjpqhazT46krhFRuCvaj4GNIuLkGof18TVEEXFCU3VXYp/zUp+vNVX3E42ju4JjaxmBmdknL4b7PMesNZA0OSL6Fpd7ZsZWlb0k/YTsPfcCMLS24ZiZmZlZvfPMjFkb5ZkZM2sLPDNj1jqUm5nxDQDMzMzMzKwueZmZWRvVp3sfGoY31DoMMzMzs2bzzIyZmZmZmdUlJzNmZmZmZlaXnMyYmZmZmVld8t3MzNoo383MzFoL37HMrPXz3czMzMzMzKxVcTJjZmZmZmZ1ycmMmZmZmZnVJSczZmZmZmZWl5zMWJsgKSTdlHveXtKrku6rsp3Rkvqmx3+TtPZKiG1oimWapNmSTl2BtvaTtPWKxmRmZmZWD5zMWFvxLrCNpE7p+VeA/6xIgxHxjYh4a0UDS26NiN7AAOBMSZ9rZjv7AU5mzMzMrE1wMmNtyd+BvdLjQ4BbChskdZF0naRJkqZK2jeVd5L0Z0kzJN0KdMrtM0/S+unx3ZImS3pS0jG5Ogsk/VLSdEmPS/pUYwFGxOvAP4GN0v7flTQxzdr8QVK7cu1K2gXYB7gg1d9sxYfMzMzMrOVyMmNtyZ+BgyV1BHoBT+S2nQk8HBH9gN3JEoIuwA+A9yKiF/BLoE+Zto+MiD5AX+AkSeul8i7A4xGxHTAGOLqxACVtDHQEZkj6AjAEGJBmbRYDh5ZrNyLGA/cAp0dE74h4rqJRMTMzM6tT7WsdgNmqEhEzJPUgm5X5W9HmPYF9JA1LzzsCGwO7AZfk9p9RpvmTJO2fHn8O2AJ4HfgAKFyXM5lseVspQyTtDmxFlpi8L2kPsuRpkiTIZoVeSfUrbXcZadYomznqVskeZmZmZi2Xkxlra+4BLgQGAevlygUcEBFz8pVTEtHoV0tLGgQMBvpHxHuSRpMlQwAfRkRh/8WU/zd3a0ScIKk/cL+kv6eYboiIn5SoX2m7y4iIq4CrANRd/spsMzMzq2teZmZtzXXALyJiZlH5SOBEpexF0vapfAxpaZekbciWpxXrBryZEpmewM7NDS4iJgA3AScDDwEHStow9b+upE2aaOIdYM3m9m9mZmZWT5zMWJsSEf+OiItLbDoX6EB2rcqs9BzgCqBrWl52BjCxxL4PAO1TnXOBx1cwzN8ARwD/As4CRqW2HyTdGKARfwZOTzcx8A0AzMzMrFXT0pUqZtaWqLuCY2sdhZnZiovhPpcxa+0kTY6IvsXlnpkxMzMzM7O65GTGzMzMzMzqkpMZMzMzMzOrS741s1kb1ad7HxqGN9Q6DDMzM7Nm88yMmZmZmZnVJSczZmZmZmZWl5zMmJmZmZlZXXIyY2ZmZmZmdclfmmnWRvlLM82sUv5SSjOrNX9pppmZmZmZtSpOZszMzMzMrC45mTEzMzMzs7rkZMbMzMzMzOqSk5lWTtJiSdMkzZJ0m6TONYhhkKRdPqG2e0iatYJtjJY0J43TNEkbrqz4Pkkp7uUuhJM0VNKltYjJzMzMbFVyMtP6LYyI3hGxDfABcFwlO0lqvxJjGAR8IslMtSS1K7Pp0DROvSPilVUUy8ocYzMzM7M2x8lM2zIW2FxSF0nXSZokaaqkfeHjT/Rvk3QvMEpSV0nXS5opaYakA1K9PSVNkDQl1e+ayudJOieVz5TUU1IPsgTq1DTrsWs+IElnSxqWez4rzbb0kPS0pKslPSlplKROqU4fSdMlTQCOz+3bTtIF6bhmSDo2lQ+S9IikPwEzqx00SatJelbSBrnn/5S0vqQNJN2R+pwkaUCqs6Ok8Wl8x0vaqswYbyRpTG72bNcS/e+R2pmZXrc1StQ5QtIzkh4FBlR7jGZmZmb1yMlMG5FmAb5OdjJ/JvBwRPQDdgcukNQlVe0PHB4RXwZ+BsyPiG0johfwsKT1gbOAwRGxA9AAnJbr6rVUfgUwLCLmAVcCF6VZj7FVhL0FcFlEfBF4CzgglV8PnBQR/YvqH5Xi7Qf0A46WtGnatiNwZkRsXaav61NC8TNJym+IiCXAH4FDU9FgYHpEvAZcnI6tX4rvmlRnNrBbRGwP/Bz4Va7J/Bh/BxgZEb2B7YBp+b4ldQRGAEMiYlugPfCDojobAeeQJTFfAcodI5KOkdQgqYH3ytUyMzMzqw9e5tL6dZI0LT0eC1wLjAf2yc2IdAQ2To8fjIg30uPBwMGFhiLiTUl7k50sj0vn/KsDE3L93Zl+Twa+tYKxz42IQuyTgR6SugFrR8SjqfwmsiQNYE+gl6QD0/NuZAnRB8DEiJhbpp9DI+I/ktYE7gAOA24sqnMd8Ffgd8CRZAkVZGO0dS7/WSu10w24QdIWQAAdcm3lx3gScJ2kDsDdueMt2CqNwzPp+Q1ks1G/y9XZCRgdEa8CSLoV2LLUgUbEVcBVkL4008zMzKyOOZlp/RamT/0/lmYeDoiIOUXlOwHv5ovITsQpKnswIg4p09+i9Hsxlb2/PmLZGcKOJdoqtNepTEz52E6MiJHLFEqDWPa4lhER/0m/30lL0XakKJmJiH9JelnSl8mSh8IszWpA/4hYWNTn74FHImL/tNRudG7zx7FExBhJuwF7ATdJuiAi8n0vM0vUCCcmZmZm1uZ4mVnbNBI4sbCcStL2ZeqNAk4oPJG0DvA4MEDS5qmss6SSswA57wBrltk2D9ghtbUDsGmZegBExFvAfEkDU9Ghuc0jgR+kWQ4kbZlbPleSpPZp6Rxpv72BcndHu4ZsudlfImJxKiseo97pYTfgP+nx0Eb63wR4JSKuJps126GoymyyGanN0/PDgEeL6jwBDJK0XjqGg8r1Z2ZmZtaaOJlpm84lW/Y0Q9ltjc8tU+88YJ10Yfp0YPe0lGkocIukGWTJTc8m+rsX2L/UDQDIlnWtm5bC/QB4pnjnEo4ALks3AMjPiFwDPAVMScf1B5qeHVoDGJmOZRpZAnJ1mbr3AF1ZusQM4CSgb7rhwFMsvVvcb4FfSxoHlLuDGmR3epsmaSrZNTcX5zdGxPtkx3ubpJnAErJrkPJ1XgLOJlvu9w9gSiP9mZmZmbUaivDqFLNKKPtOl4siYrk7jtUjdVdwbK2jMLN6EMN9rmBmtSVpckQs9/16vmbGrAKSfkw2c3RoU3XNzMzMbNXwMjOzCkTE+RGxSUQ8VutYzMzMzCzjZMbMzMzMzOqSl5mZtVF9uvehYXhDrcMwMzMzazbPzJiZmZmZWV1yMmNmZmZmZnXJyYyZmZmZmdUlf8+MWRvl75kxa9v83TFmVk/Kfc+MZ2bMzMzMzKwuOZkxMzMzM7O65GTGzMzMzMzqkpMZMzMzMzOrS05m6oikxZKmSZol6TZJnWsQwyBJu+Seny3pPymuws/aK6GfoZIuXdF2muhjQfrdQ9KsKvYbIenAFei3h6SFRWO2enPbMzMzM2urnMzUl4UR0TsitgE+AI6rZCdJ7VdiDIOAXYrKLkpxFX7eWon9tSq51+K5ojH7oML9232C4ZmZmZnVFScz9WsssLmkLpKukzRJ0lRJ+8LHMxu3SboXGCWpq6TrJc2UNEPSAanenpImSJqS6ndN5fMknZPKZ0rqKakHWQJ1appN2LVccKn/uyXdK2mupBMknZZifFzSuqneaEm/kzQ+zTjtWKKtTSQ9lOJ+SNLGktZM7XZIddZKMXeQtJmkByRNljRWUs9UZ9N0rJMkndvUAEs6OtWdLumOopmwwantZyTtnep3zI3xVEm7l3otGulvj7TfzPSarpF7LX4u6THgIElfS6/LdEkPpTol3wdmZmZmrZmTmTqUPt3/OjATOBN4OCL6AbsDF0jqkqr2Bw6PiC8DPwPmR8S2EdELeFjS+sBZwOCI2AFoAE7LdfVaKr8CGBYR84ArWToTMzbVKyQ30yQ9ktt/G+A7wI7AL4H3ImJ7YALwvVy9LhGxC/BD4LoSh3wpcGOK+2bgkoh4BxgN7JXqHAzcEREfAlcBJ0ZEH2AYcHmqczFwRRqr/5Yf4Y/dGRH9ImI74GngqNy2HsCXUv9XSuoIHA8QEdsChwA3pHJY9rUA2Cw3ZpeleiOAIWn/9sAPcv29HxEDgYeAq4EDUlwHpe2NvQ/MzMzMWqWVufzIPnmdJE1Lj8cC1wLjgX0kDUvlHYGN0+MHI+KN9Hgw2Qk/ABHxZppR2BoYJwlgdbJEo+DO9Hsy8K1G4rooIi4sUf5ISjrekTQfuDeVzwR65erdkmIak2ZY1i5qp3+u/5uA36bH1wBnAHcDRwBHp5mlXYDb0jEBrJF+DwAOyLXzm0aOCWAbSecBawNdgZG5bX+JiCXAs5KeB3oCA4Hfp2OZLekFYMtUP/9aQFpmVngiaTtgbkQ8k4puIEuOfpee35p+7wyMiYi5qZ9Cm3tS+n3wdP6AJB0DHANAtyaO3szMzKyFczJTXxbmT4ABlJ2xHxARc4rKdwLezRcBxV/3LLKT7EPK9Lco/V5M894ri3KPl+SeLylqrziupr6WOgAiYpyyi+m/BLSLiFmS1gLeKh6nKtrOGwHsFxHTJQ0lu16osZhFee82so0m9s3vX+p1LJQv9z4oFhFXkc1coe7y13+bmZlZXfMys/o3EjgxJTVI2r5MvVHACYUnktYBHgcGSNo8lXWWtGWZ/QveAdZc4aiXNST1P5BsKdz8ou3jWTqrdCjwWG7bjWQzO9cDRMTbwFxJB6U2lWY9AMYVtdOUNYGX0nU5xfUPkrSapM2AzwNzgDGFemkcN07llZgN9Ci8FsBhwKMl6k0AviRp09TPuqm80veBmZmZWavhZKb+nQt0AGYou71wuQvbzwPWSRfZTwd2j4hXgaHALZJmkCU3PZvo715gfy17A4D8NTPTlN0ooBpvShpPdj3OUSW2nwQckWI8DDg5t+1mYB3SUrXkUOCodJxPAoWL4U8Gjpc0ieUXWW0l6d+5n4PIrjN6AniQLNnIm0OWbPwdOC4i3ie7NqedpJlky8KGRsQiKpD2P4JsedxMstmrK0vUe5Vsmdid6fgKy88qfR+YmZmZtRqK8EoTqx1Jo8luLtDQzP0PBPaNiMNWamBtgLorOLbWUZhZrcRw//9vZvVD0uSI6Ftc7mtmrG5J+j3ZXd2+UetYzMzMzGzVczJjNRURg1Zg3xNXYihmZmZmVmd8zYyZmZmZmdUlz8yYtVF9uvehYXizLlUyMzMzaxE8M2NmZmZmZnXJyYyZmZmZmdUlJzNmZmZmZlaX/D0zZm2Uv2fGrO3yd8yYWb0p9z0znpkxMzMzM7O65GTGzMzMzMzqkpMZMzMzMzOrS05mzMzMzMysLjmZMTMzMzOzuuRkxioiabGkaZJmSbpNUucaxDBI0i5ltp0taViV7S1YOZF93N48STMlTZc0StKnV2b7RX31kPSdT6p9MzMzs3rgZMYqtTAiekfENsAHwHGV7CSp/UqMYRBQMplpQXaPiO2ABuCnn0QHaUx7AE5mzMzMrE1zMmPNMRbYXFIXSddJmiRpqqR9ASQNTbM39wKjJHWVdH2atZgh6YBUb09JEyRNSfW7pvJ5ks5J5TMl9ZTUgyyBOjXNEO1aIq7tJD0s6VlJRxcKJZ2eYpwh6ZzinZS5IM06zZQ0JJVfLmmf9PguSdelx0dJOq+JMRqTxqhj7tinSto9tfGEpC/mYhgtqU+lYwqcD+yaxuJUSWMl9c61N05SryZiNDMzM6trK/NTc2sD0qzA14EHgDOBhyPiSElrAxMl/SNV7Q/0iog3JP0GmB8R26Y21pG0PnAWMDgi3pX0I+A04Bdp/9ciYgdJPwSGRcT3JV0JLIiIC8uE1wvYGegCTJV0P7ANsAWwIyDgHkm7RcSY3H7fAnoD2wHrA5MkjSFLSHYF7gE+A2yU6g8E/tzEUO0NzASOB4iIbSX1JEvutkz7fxsYLmkjoHtETJb0qwrHdFAal73TmL4BDAVOSe2vEREzioOSdAxwDADdmjgCMzMzsxbOMzNWqU6SppEtn/o/4FpgT+DHqXw00BHYONV/MCLeSI8HA5cVGoqIN8mSjq2BcWn/w4FNcv3dmX5PJltSVYm/RsTCiHgNeIQsgdkz/UwFpgA9yZKbvIHALRGxOCJeBh4F+pHNQO0qaWvgKeDllHj0B8aXieGRdDxrAb9Obd+Ujns28AKwJfAX4KC0z7eB29LjSse02G3A3pI6AEcCI0pVioirIqJvRPRllV/1ZGZmZrZyeWbGKrUwInrnCyQJOCAi5hSV7wS8my8Coqg9kZ2cH1Kmv0Xp92Iqf58W9xGpn19HxB8a2U8lG4v4j6R1gK+RzdKsS5Z4LIiId8q0tXtKprKGszEq1/braSnYEODYXCyVjGlxe+9JehDYN8XYt1xdMzMzs9bCMzO2IkYCJxZO2CVtX6beKOCEwpOUIDwODJC0eSrrnJZHNeYdYM1Gtu+brlFZj+xmAZNSjEfmrsf5jKQNi/YbAwyR1E7SBsBuwMS0bQJwSqozFhiWfldqDHBo6ntLslmWQqLyZ+AMoFtEzExllY5pqbG4BrgEmNTIDI6ZmZlZq+FkxlbEuUAHYIakWel5KecB66QL7KeTzV68SnaNxy2SZpAlNz2b6O9eYP9GbgAwEbg/tXVuRLwYEaOAPwETJM0Ebmf5JOAuYAYwHXgYOCMi/pu2jQXaR8Q/yZaprUt1yczlQLvU963A0IgozDrdDhxMtuSsoNIxnQF8pOw20KcCRMRk4G3g+iriMzMzM6tbiihemWNm9UhSd7LrbHpGxJIm63dXfLy4zczalBju//vNrL5ImhwRyy2j98yMWSsg6XvAE8CZlSQyZmZmZq2BbwBg1gpExI3AjbWOw8zMzGxV8syMmZmZmZnVJc/MmLVRfbr3oWF4Q63DMDMzM2s2z8yYmZmZmVldcjJjZmZmZmZ1ycmMmZmZmZnVJX/PjFkb5e+ZMWv5/H0wZmYZf8+MmZmZmZm1Kk5mzMzMzMysLjmZMTMzMzOzuuRkxszMzMzM6pKTmRZG0mJJ03I/PT7BvuZJWr/CuvtKujv3/CeS/pl7/k1J91TR99mShpUo75mOe6qkzSptr7kkDZX0aurzKUlHf9J9lonjFEmda9G3mZmZWb1yMtPyLIyI3rmfebUOKBkP9M897w+8LWnD9HwXYFwlDUlq38jm/YC/RsT2EfFcBW1J0oq+j2+NiN7AIOBXkj5VyU5NHEe1TgGczJiZmZlVwclMHZDUR9KjkiZLGilpo1Q+WtJFksZIelpSP0l3SnpW0nm5/e9O+z4p6ZgyfXxX0sQ0Q/EHSe3y2yPiVWC+pM1T0WeAO8iSGNLv8ZI2kfSQpBnp98ap/RGS/lfSI8Bvivo+WtLfJe1FdlL//VQPSadJmpV+TkllPdLxXg5MAT4n6QxJMyVNl3R+qreZpAfSsY+V1LOxcY6IV4DngE2aGPNfSXoUODmN+fjU70RJa0pqJ+kCSZPSOByb9h2U9r9d0mxJN6dk7CSgO/BI7rivkNSQXrNzcmP1jbTvY5IukXRfKu8i6brU51RJ+zZ2rGZmZmatwcr8ZNlWjk6SpqXHc4FvA78H9o2IVyUNAX4JHJnqfBARu0k6Gfgr0Ad4A3hO0kUR8TpwZES8IakTMEnSHakcAElfAIYAAyLiw5QkHArcWBTbeGCXlOg8CzwOfDWdUPcCJgG3ATdGxA2SjgQuIZttAdgSGBwRiyWdnfo+AdgT2C8iFkm6ElgQERdK6gMcAewECHgiJRFvAlsBR0TEDyV9PfWxU0S8J2nd1N9VwHER8ayknYDLgS+XG3hJnwc+D7wA3NXImK8dEV+StDowGxgSEZMkrQUsBI4C5kdEP0lrAOMkjUr7bg98EXiRbCZrQERcIuk0YPeIeC3VOzO9Zu2AhyT1Ap4B/gDsFhFzJd2SC/9M4OGIOFLS2sBESf+IiHfLHa+ZmZlZvXMy0/IsTEueAJC0DbAN8KAkgHbAS7n6hetUZgJPRsRLab/ngc8BrwMnSdo/1fscsEUqL9iDLAmalProBLxSIrZxZDMw7YAJwETg52Qn6HMi4n1J/YFvpfo3Ab/N7X9bRCzOPT8M+DdZIvNhif4GAncVTsgl3Qnsmo75hYh4PNUbDFwfEe8BpCSga4r1tnRMAGuU6ANgiKSBwCLgWGADGh/zW9PvrYCXImJS6vftFOeeQC9JB6Z63cjG/ANgYkT8O9WbBvQAHisR07fTLFp7YCNga7KZ1OcjYm6qcwtQmGnbE9hHS69D6ghsDDydbzS1eczHUZmZmZnVMSczLZ/IkpT+ZbYvSr+X5B4XnreXNIjsZL9/mrUYTXaiW9zHDRHxkyZiGQ+cSHZyf3VEvCOpI9m1JuWul8l/fXXxLMEsoDfwWbJZqGIqUVaqLRX1A9mJ/1v5xLARt0bECR83Jm1L42Ne6LtUv4XyEyNi5DKF2WuRf40WU+LfoKRNgWFAv4h4U9IIstessfEQcEBEzGmkDhFxFdmMFeouf7W4mZmZ1TVfM9PyzQE2SDMeSOog6YtV7N8NeDMlMj2BnUvUeQg4UOlifknrStqkRL2nyK7t2BWYmsqmAceRJTqk3wenx4dSetahYCrZTMg9krqX2D4G2E9SZ0ldgP2BsSXqjQKOVLobmKR10yzJXEkHpTJJ2q6RWPIqHfPZQHdJ/VK9NZXdFGAk8ANJHVL5lin+xrwDrJker0WWMM1XdjOCr+f6+7yW3uFuSG7/kcCJSlNJkrav8FjNzMzM6paTmRYuIj4ADgR+I2k6WfKwS6M7LesBshmaGcC5ZNe5FPfxFHAWMCrVe5BsaVNxvQCeAF7LLQubQHadSSGZOQk4IrVzGHByE8f3GNksxP0quk10REwBRpAtZ3sCuCYippZo4wGypWcNaelWYanVocBRadyeBCq6KL7SMU/1hgC/T/UeJJtBuYYs8ZsiaRbZdS5NzYJeBfxd0iMRMZ0s0XsSuI406xURC4EfAg9Iegx4GZif9j8X6ADMSH2eW8mxmpmZmdUzZeenZlYPJHWNiAVpBuYy4NmIuKhZbXVXcOzKjc/MVq4Y7v+jzcwAJE2OiL7F5Z6ZMasvR6fZpyfJlhD+obbhmJmZmdWObwBgVkfSLEyzZmLMzMzMWhvPzJiZmZmZWV3yzIxZG9Wnex8ahjfUOgwzMzOzZvPMjJmZmZmZ1SUnM2ZmZmZmVpeczJiZmZmZWV3y98yYtVH+nhmzlsHfJWNm1jR/z4yZmZmZmbUqTmbMzMzMzKwuOZkxMzMzM7O65GTGzMzMzMzqkpMZMzMzMzOrS05mWghJ+0sKST1rHUtTJM2TNFPSdEmjJH36E2h//Srqj5Y0J8UzTtJWK9D3aEl9c897SJrV3Paq7HuEpAOrqF82tuLjMDMzM2uNnMy0HIcAjwEHr4zGJLVbGe00YveI2A5oAH76CfdViUNTPDcAF1SygzL+N2BmZmZWp3wi1wJI6goMAI4iJTOSvi7pL7k6gyTdmx7vKWmCpCmSbkv7F2Y0fi7pMeAgSUdLmpRmLO6Q1DnV20zS42nbLyQtyPVzeiqfIemcCsIfA2wuqZ2kC3L7HpvaUyqflWZzhuSOZ4ykuyQ9JenKUomFpO9KmihpmqQ/VJCkjQE2L3csaTbjaUmXA1OAz1VwjIVYOkq6Ph3HVEm7p/Khki7N1bsvHV+7NNtSOPZT0/bNJD0gabKksUWzcbtJGi/p+cIsTbkxLIqtk6Q/p2O9FehU6XGZmZmZ1SsnMy3DfsADEfEM8IakHYAHgZ0ldUl1hgC3puVXZwGDI2IHspmR03JtvR8RAyPiz8CdEdEvzVg8TZYsAVwMXBwR/YAXCztK2hPYAtgR6A30kbRbE7HvDcxMbc9PbfYDjpa0KfCt1NZ2wGDgAkkbpX13BP4H2BbYLNX9mKQvpOMeEBG9gcXAoU3E801gZhPHshVwY0RsHxEvlGjj5pQ8TQP+lis/HiAitiWbSbtBUsdGYukNfCYitkn7XJ/KrwJOjIg+wDDg8tw+GwEDycb1/FTW2BgW/AB4LyJ6Ab8E+pQKSNIxkhokNfBeI5GbmZmZ1YH2tQ7AgOzE+Hfp8Z+BQyJiiqQHgG9Kuh3YCzgD+BKwNTBOEsDqwIRcW7fmHm8j6TxgbaArMDKV9ydLoAD+BFyYHu+Zfqam513JEoIxJWJ+RNJiYAZZcnUN0Ct3zUe3tO9A4JaIWAy8LOlRsmTnbWBiRDwPIOmWVPf2XB97kJ2UT0rH2gl4pUQskCUgC4F5wInAyWWO5f+AFyLi8TLtQLZkrSHF1QO4L5UPBH4PEBGzJb0AbNlIO88Dn5f0e+B+YFSaRdsFuC0dE8AauX3ujoglwFOSPpXrt9QYzsjttxtwSYpthqT8to9FxFVkyRTqLn/tuJmZmdU1JzM1Jmk94MtkiUcA7YCQdAZZYnI88AYwKSLeUXYG/GBEHFKmyXdzj0cA+0XEdElDgUFNhQP8OiL+UEHou0fEa7njENlsw8h8JUnfaKSN4pPp4ucCboiIn1QQz8cJSC6e5Y4lJSfv0jwqU/4Ry85ydgSIiDclbQd8lex1/DZwCvBWmmkqZVGJ/sr1W8zJiZmZmbUpXmZWeweSLXnaJCJ6RMTngLlkn8aPBnYAjmbpjMvjwABJhetCOksqNzuwJvCSpA4suzzrceCA9Dh/w4GRwJFaeg3OZyRtWOFxjAR+kPpC0pZpidwYYEi6fmQDshmEiWmfHSVtmq6VGUJ2A4S8h4ADCzFIWlfSJlXE09xjKWcMaRzTmG8MzCGbDeotaTVJnyNb2kZaErhaRNwB/AzYISLeBuZKOijVUUp4muq33BiWim0boNcKHquZmZlZi+dkpvYOAe4qKrsD+E5aVnQf8PX0m4h4FRgK3JKWEj0OlLud88+AJ8iuv5mdKz8FOE3SRLJrNOantkeRLTubIGkm2ZKvNSs8jmuAp4Apym4X/Aeymb+7yJZDTQceBs6IiP+mfSaQXRcyiyyBW2YcIuIpsiVso9KxPpjibdIKHks5lwPtUnu3AkMjYhEwLsU/k2zJ3pRU/zPA6HTtzQigMMN0KHCUpOnAk8C+TfTb2BgWXAF0TeN0BssnO2ZmZmatjiK8MqWtUXZXs4UREZIOJrtGp6kT6pUdwyBgWETsvSr7taXUXcGxtY7CzGK4/x82M2uKpMkRsdx36PmambapD3Bpuq7kLeDI2oZjZmZmZlY9JzNtUESMJbvNby1jGE12TZCZmZmZWbP4mhkzMzMzM6tLnpkxa6P6dO9Dw/CGpiuamZmZtVCemTEzMzMzs7rkZMbMzMzMzOqSkxkzMzMzM6tL/p4ZszbK3zNj1jL4e2bMzJpW7ntmPDNjZmZmZmZ1ycmMmZmZmZnVJSczZmZmZmZWl5zMmJmZmZlZXXIyYxWRtFjSNEmzJN0mqXMNYhgkaZcy24ZKCkl75Mr2T2UHNtHuPEnrlyg/TtL30uMRTbVTtO/ZkoZV0o+ZmZmZNY+TGavUwojoHRHbAB8Ax1Wyk6T2KzGGQUDJZCaZCRySe34wML25nUXElRFxY3P3NzMzM7NPlpMZa46xwOaSuki6TtIkSVMl7Qsfz5LcJuleYJSkrpKulzRT0gxJB6R6e0qaIGlKqt81lc+TdE4qnympp6QeZAnUqWmGaNcyce0oqUNqa3NgWmGjpD1SnDNT3Gvk9j1d0sT0s3mqv9zsSirvI+lRSZMljZS0UbUDKOm0NMs1S9IpqayHpNmSrknlN0saLGmcpGcl7ZjqlRv3L6b4p6Vx3qLauMzMzMzqiZMZq0qaafk62SzImcDDEdEP2B24QFKXVLU/cHhEfBn4GTA/IraNiF7Aw2m51VnA4IjYAWgATst19VoqvwIYFhHzgCuBi9IM0dgS4QXwD+CrwL7APbm4OwIjgCERsS3QHvhBbt+3I2JH4FLgd40cfwfg98CBEdEHuA74ZZnqhcRrmqRpQPfURh/gCGAnYGfgaEnbp302By4GegE9ge8AA4FhwE9TnXLjfhxwcUT0BvoC/y53HGZmZmatgZMZq1SndELeAPwfcC2wJ/DjVD4a6AhsnOo/GBFvpMeDgcsKDUXEm2Qn8VsD49L+hwOb5Pq7M/2eDPSoIs4/ky0vOxi4JVe+FTA3Ip5Jz28AdsttvyX3u38j7W8FbAM8mOI+C/hsmbqFxKt3SjBeTOUDgbsi4t2IWEB2rIWZprkRMTMilgBPAg9F9s22M1k6DuXGfQLwU0k/AjaJiIXFAUk6RlKDpAbea+QozczMzOrAyryewVq3hemE/GOSBBwQEXOKyncC3s0Xkc2aUFT2YEQcQmmL0u/FVPE+jYiJkrZJ8T6Thfhxf43uWuZxMQFPRkRjCU9TGotlUe7xktzzJSwdh5LjDjwt6QlgL2CkpO9HxMP5ChFxFXAVgLrLXztuZmZmdc0zM7YiRgInpqSG3FKpYqOAEwpPJK0DPA4MyF2f0lnSlk309w6wZgVx/YSlS7IKZgM9Cv0BhwGP5rYPyf2e0Ejbc4ANJPVPcXeQ9MUKYsobA+yXjrkLsD/Z9T6VKjnukj4PPB8Rl5AtsetVZVxmZmZmdcXJjK2Ic4EOwAxJs9LzUs4D1kkXtU8Hdo+IV4GhwC2SZpAlNz2b6O9eYP9GbgAAQET8PSIeKSp7n+w6ldskzSSb6bgyV2WNNKtxMnBqI21/ABwI/CYdyzQav8NaqTamkF2/MxF4ArgmIqZW0US5cR8CzErLz3oCvhObmZmZtWrKluObWVuj7gqOrXUUZhbD/f+wmVlTJE2OiL7F5Z6ZMTMzMzOzuuRkxszMzMzM6pKTGTMzMzMzq0u+NbNZG9Wnex8ahjfUOgwzMzOzZvPMjJmZmZmZ1SUnM2ZmZmZmVpeczJiZmZmZWV3y98yYtVH+nhmzVcvfJ2Nm1nz+nhkzMzMzM2tVnMyYmZmZmVldcjJjZmZmZmZ1ycmMmZmZmZnVJSczJUhaLGmapFmSbpPUuQYxDJK0S5X7rCHpHyn2IUXbRkiam7ZNl7THCsR2ysoYE0nHSJqdfiZKGriibVbYb3dJt1e5zwhJB1ZSLmnBisZY1N5xkr63Mts0MzMzaw2czJS2MCJ6R8Q2wAfAcZXsJKn9SoxhEFBVMgNsD3RIsd9aYvvpEdEbOAW4cgViOwWoKpmR1K7o+d7AscDAiOhJNsZ/kvTpFYirIhHxYkQsl5i0VBFxZUTcWOs4zMzMzFoaJzNNGwtsLqmLpOskTZI0VdK+AJKGptmbe4FRkrpKul7STEkzJB2Q6u0paYKkKal+11Q+T9I5qXympJ6SepCd3J+aZlJ2zQckaV1Jd6f2H5fUS9KGwB+B3mmfzRo5pgnAZ1Jb7SRdkI5rhqRjU/kgSaMl3Z5mTm5W5iSgO/CIpEcqOLafS3oMOKgohh+RJVevAUTEFOAG4Pi0bz9J49Ms0kRJa6ZYL8yN7Ym5ftZPj/tKGp0eny3pJkkPS3pW0tGpvIekWU0cvyRdKukpSfcDG1byZil6nZTanpViHpIb2/ty9S6VNDQ9Pj/1OUPShbnjGJYej5b0mzQmzxTeG5I6S/pL2u9WSU9IWu72hWZmZmatycqcSWh10kzL14EHgDOBhyPiSElrAxMl/SNV7Q/0iog3JP0GmB8R26Y21kkn2mcBgyPiXUk/Ak4DfpH2fy0idpD0Q2BYRHxf0pXAgoi4sERo5wBTI2I/SV8GboyI3pK+n/bfu4lD+xpwd3p8VIq3n6Q1gHGSRqVt2wNfBF4ExgEDIuISSacBu0fEaxUc2/sRUWr52BeByUVlDcDhklYHbgWGRMQkSWsBC4FjgE2B7SPiI0nrNnGcAL2AnYEuwNSUmOSVO/7tga2AbYFPAU8B15Xp4wJJZ5Uo/xbQG9gOWB+YJGlMuUDT8ewP9IyISO+zUtpHxI6SvgEMBwYDPwTejIhekrYBppXrx8zMzKy1cDJTWidJ09LjscC1wHhgn8In5EBHYOP0+MGIeCM9HgwcXGgoIt5UtqRqa7ITZYDVyWZHCu5MvyeTnQA3ZSBwQGr/YUnrSepWwX4XSPot2SzDzqlsT6CXll730Q3Ygmx53cSI+DdAGo8ewGNFbe7cxLGVWu5WjoAgSyJeiohJ6RjfTjEMBq6MiI9S+RvlGsr5a0QsBBammaQdWfZEv9zx7wbcEhGLgRclPdxIH6dHxMfX4GjpNTMDc228LOlRoB/wdpl23gbeB65JSdd9Zerl3y89cn1dDBARsyTNKLWjpGPIksLsSM3MzMzqmJOZ0hama0s+puxM/YCImFNUvhPwbr6I7IScorIHI+KQMv0tSr8XU9lrohJllXy19OlkJ8InkS3p6pPaOjEiRi7TgTQoF1djsTV1bO+WKX8q9Z9PEnZI5aXGkEbKP2LpksmORduK65d6bUod/zfK9FWNUq8TLBsvpJjTbNOOwB5kCfEJwJdL7F/q/VKur2VExFXAVQDqLn8duZmZmdU1XzNTuZHAiSmpQdL2ZeqNIjsJJdVbB3gcGCBp81TWWdKWTfT3DrBmmW1jgENTW4PIlqmV+7R/GRGxhOwT/NUkfZXsuH4gqUNqb0tJXaqIrTnHBvBb4DeS1kv79QaGApcDs4HukvqlbWumJX+jgOPS48KyLIB5ZIkRpBmrnH0ldUz9DAImFW0vd/xjgIPTNTUbAbtXcEzFxgBDUhsbkM32TAReALZWdve5bmTJC8quNeoWEX8ju8lC7yr6egz4dmpna7LlcWZmZmatmmdmKncu8DtgRkpo5gGlrk05D7hM2QXmi4FzIuLOdIH3Lem6DMiuM3mmkf7uBW5XdqOBEyNibG7b2cD1aSnRe8Dh1RxIuh7jPOAM4CtkS5WmpON6FdiviSauAv4u6aWI2L0Zx0ZE3CPpM8B4SUGWIH03Il4CSBfL/15SJ7LrZQYD1wBbkr0GHwJXA5eSXUN0raSfAk8UdTURuJ9sSeC5EfGishssFFxT5vjvIpsVmZmO5dEmxqSUu8iup5pONstzRkT8Nx3fX4AZwLPA1FR/TeCvkjqSzbScWkVflwM3pPfE1NT2/GbEbGZmZlY3FOGVJtY6STqb8jdRaFWU3fq6Q0S8r+xOdg8BW0bEB2X36a7g2FUWolmbF8P9/62ZWXNJmhwRy92p1TMzZq1DZ7LbZXcgm9X5QWOJjJmZmVlr4GTGWq2IOLvWMawqEfEO4O+VMTMzszbFNwAwMzMzM7O65GTGzMzMzMzqkpeZmbVRfbr3oWF4Q63DMDMzM2s2z8yYmZmZmVldcjJjZmZmZmZ1ycmMmZmZmZnVJX9pplkb5S/NtLbCX1ZpZlb/yn1ppmdmzMzMzMysLjmZMTMzMzOzuuRkxszMzMzM6pKTGTMzMzMzq0tNJjOSFkuaJmmWpNskdV4VgRXFMEjSLqu631z/Z0sa1kSd/SRtnXv+C0mDV0Fs3SXdnh73lvSN3LYm414J/Q+VdGlR2WhJfdPjv0lau4k2Pq7fSJ3VJF2S3oczJU2StGkj9VfasUtaUKa88G/jSUnTJZ0mabW0ra+kS5pot4ekWSsjRjMzM7O2qH0FdRZGRG8ASTcDxwH/29ROktpHxEcrFt7HBgELgPErqb1Pwn7AfcBTABHx81XRaUS8CByYnvYG+gJ/WxV9VyIivtF0rYoMAboDvSJiiaTPAu+upLabK/9vY0PgT0A3YHhENAANNYzNzMzMrNWrdpnZWGBzSV0kXZc+HZ8qaV/4+FP62yTdC4yS1FXS9emT9BmSDkj19pQ0QdKUVL9rKp8n6ZxUPlNST0k9yBKoU9On4LvmA0qfwN8k6WFJz0o6OpVL0gW5T/KHpPJBksZIukvSU5KuzH2aviDX7oGSRhQPgKSj03FPl3SHpM5p1mgf4IIU42aSRkg6MO2zRxqnmWnc1ih3vCX6+5ukXunxVEk/T4/PlfT9wqf7klYHfgEMSTEMSU1snWY+npd0UqkXVdICSb9Mx/S4pE+l8k0kPZReu4ckbdzE+6NU2/MkrZ8e/0zSbEkPSrqlaObkIEkTJT1T/BonGwEvRcQSgIj4d0S8mdr9WhrD6ZIeyu1T8tjTDMqs9HNKU+WViIhXgGOAE9J7b5Ck+1K7Jd+jRePUMfdvZaqk3VP5UEl3S7pX0lxJJ6Q4p6bXat1Ub7n3ZTXxm5mZmdWjipMZSe2BrwMzgTOBhyOiH7A72Ul8l1S1P3B4RHwZ+BkwPyK2jYhewMPpxPYsYHBE7ED26fVpua5eS+VXAMMiYh5wJXBRRPSOiLElwusF7JX6/rmk7sC3yGYqtgMGpxg3SvV3BP4H2BbYLNWt1J0R0S8itgOeBo6KiPHAPcDpKcbncuPWERgBDImIbclmw35Q7nhL9DcG2FXSWsBHwIBUPpAsuQQgIj4Afg7cmmK4NW3qCXw1HfNwSR1K9NEFeDwd0xigcLJ9KXBjeu1uBsotmyokUNMkTSObHVqGsmVkBwDbk413cZ32EbEjcAowvEQffwG+mfr4f5K2T+1uAFwNHJDiPyi3z3LHLqkPcASwE7AzcLSk7cuVlznekiLiebJ/UxuW2FzqPZp3fGpjW+AQ4Ib03gHYBvhOOo5fAu9FxPbABOB7qc5y78tqYjczMzOrR5UkM53SCWoD8H/AtcCewI9T+WigI1D41P7BiHgjPR4MXFZoKH2SvjOwNTAu7X84sEmuvzvT78lAjwqP468RsTAiXgMeITvpGwjcEhGLI+Jl4FGgX6o/MSKej4jFwC2pbqW2kTRW0kzgUOCLTdTfCpgbEc+k5zcAu+W2N3W8Y1P9gcD9QNf0qXuPiJhTQbz3R8SiNDavAJ8qUecDsiVyxXH0J1s6BXAT5cepkED1TsuuSi2vGsjS1+kd4N6i7Y2OQ0T8m2wsfwIsAR6StAfZ+2lMRMxN9d7I7Vbq2AcCd0XEuxGxIPW7ayPl1VKZ8lLv0byBZGNMRMwGXgC2TNseiYh3IuJVYD5Lx24mS8eqovelpGMkNUhq4L3qD87MzMysJanqmpkCSSL7JHxOUflOLHsdg4Dir14WWcJzSJn+FqXfiyuMjxJ9BOVPKsvVLy7vSGkjgP0iYrqkoWTX8zSmsTig6eOdRDaL8TzwILA+2czJ5CbaLW6/sT4+jIhoog4sP27VWNFxICIWAX8H/i7pZbLrlB5sJK5Sx14ujqbia5Kkz6d+XgG+ULS53Huukv7zx7Ek93wJS8dqBBW8LyPiKuAqAHWXvxbdzMzM6lpzb808EjgxJTU0shxnFHBC4YmkdYDHgQGSNk9lnSVtWWb/gneANRvZvm+65mA9spO4SWTLpYZIapeWIu0GTEz1d5S0qbJrZYYAj6XylyV9IZXvX6avNYGX0nKtQyuIcTbQo3C8wGFks0QVScvH/gV8m2zsxpItRyu13K6pcarWeODg9PhQlo5TczxGtkyso7JrpPaqZmdJOxSWZqXXpxfZ7MUE4EtKdzYrXEPSiDHAful914XsdR7bSHml8W1Athzy0lximFfqPVoc16GprS3JZjormXkrKPe+NDMzM2u1mpvMnAt0AGYou7XsuWXqnQesky6ong7snpbKDAVukTSD7AR9uQvfi9wL7K8SNwBIJpItwXocODfd4esuYAYwHXgYOCMi/pvqTwDOB2YBc1NdgB+TLbd6GHipTCw/A54gmxGYnSv/M3B6ujB7s0JhRLxPdi3GbWkJ0BKyk95qjAVejoj30uPPUvpE+xGyi97zNwBYEScBR6TX6TDg5OY2FBGTyK4rmk62hKuBbMlUpTYE7k3vtxlk1w9dmt5PxwB3pvfYrY20QURMIZvFmEj2Ol4TEVPLlTcRU6c01k8C/yBL3s8pU7fUezTvcqBdeo/cCgxNM1GVKve+NDMzM2u1VPpD5Poh6WxgQURcWGH9QWQ3Ftj7EwzLSpDUNSIWpGt+xgDHpCSiVav2PbqqqLuCY2sdhdknL4bX9/9zZmYGkiZHxHI3mar0mhSzleEqZV8s2hG4oS0kMmZmZmb2yan7mRkzax7PzFhb4ZkZM7P6V25mprnXzJiZmZmZmdWUl5mZtVF9uvehYXiprwQyMzMzqw+emTEzMzMzs7rkZMbMzMzMzOqSkxkzMzMzM6tLvpuZWRvlu5nZquQ7ipmZ2Yrw3czMzMzMzKxVcTJjZmZmZmZ1ycmMmZmZmZnVJSczZmZmZmZWl5zMWFUkLZY0TdIsSfdKWnsltr2giT4LPz1WVp8l+hokab6kqZKeljT8E+ij5HHmtq8t6Ye5590l3b6y4zAzMzOrd05mrFoLI6J3RGwDvAEcX+mOktqvYJ+Fn3kV9CVJzX1/j42I7YG+wHcl9WlmO821NvBxMhMRL0bEgas4BjMzM7MWz8mMrYgJwGcAJI2W1Dc9Xl/SvPR4qKTbJN0LjJLUVdJDkqZImilp32o7LdeGpB5pNuVyYAqwq6TZkq5JM0k3SxosaZykZyXt2Fg/EfEuMBnYTFJvSY9LmiHpLknr5I77d5LGpz52TOVnSxqWi3lW8YxSI2NxfupzmqQL0nHNSvt0lHR9qj9V0u65cb5T0gPp2H5b7biamZmZ1RsnM9YsktoBewD3VFC9P3B4RHwZeB/YPyJ2AHYH/p8kNbF/p9wSs7uaaGMr4MY0s/ICsDlwMdAL6Al8BxgIDAN+2sQxrgfsDDwJ3Aj8KCJ6ATOB/PKzLhGxC9lsynVND8fHyh3Hj4Hn0izU6UX7HA8QEdsChwA3SOqYtvUGhgDbAkMkfa6KWMzMzMzqTnOX/Vjb1UnSNKAH2azFgxXs82BEvJEeC/iVpN2AJWQzO58C/tvI/gsjonfhiaQOZdoAeCEiHs/tOzciZqb9ngQeioiQNDMdQym7Spqa2j4f+DewdkQ8mrbfANyWq38LQESMkbRWFdcRlRuLxgwEfp/6my3pBWDLtO2hiJifjvUpYBPgX8t0KB0DHANAtwqjNDMzM2uhnMxYtRZGRG9J3YD7yGYKLgE+YulMX8eifd7NPT4U2ADoExEfpuVoxfWb0lgb7xbVXZR7vCT3fAnl3/9jI2LvwpN0rI0p/mrzYNnxgNLH2JyxaGwWK3+siylxfBFxFXAVgLrLX8luZmZmdc3LzKxZ0gzAScCwNFMyDyhcKN/YxerdgFfSyfvuZLMH1VoZbVQsHeubknZNRYcBj+aqDAGQNBCYn+rPA3ZI5TsAm5ZoutxxvAOsWSacMWRJEJK2BDYG5jTvyMzMzMzqm2dmrNkiYqqk6cDBwIXAXyQdBjzcyG43A/dKagCmAbOb0fXKaKNahwNXSuoMPA8ckdv2pqTxwFrAkansDuB7aUneJOCZEm2WPI6IeD3dpGAW8Hfgstw+l6c4ZpLN/gyNiEVNX3ZkZmZm1voowitNzJpL0mhgWEQ01DqWaqm7gmNrHYW1FTHc/9eYmVnzSZocEX2Ly73MzMzMzMzM6pKXmZmtgIgYVOsYzMzMzNoqz8yYmZmZmVldcjJjZmZmZmZ1ycvMzNqoPt370DC87u5bYGZmZvYxz8yYmZmZmVldcjJjZmZmZmZ1ycmMmZmZmZnVJX9pplkb5S/NtFXFX5hpZmYryl+aaWZmZmZmrYqTGTMzMzMzq0tOZszMzMzMrC45mTEzMzMzs7rkZMZKkrSg6PlQSZeuor7nSVq/ivplYys+jira/JuktdPPD3PlgyTd15w2q+z/AklPSrqgmfs367jNzMzM6kn7Wgdg1hJFxDcAJPUAfghcvopDOBbYICIWreJ+zczMzOqGZ2asapI2kfSQpBnp98apfISkA3P1FqTfG0kaI2mapFmSdk3le0qaIGmKpNskdc11c2IqnympZ6q/rqS7U7+PS+pVIrZNU5uTJJ1bJv4zJJ2UHl8k6eH0eA9Jf0yPC7ND5wObpdgLsyRdJd0uabakmyWpRB+jJf1G0kRJz+SOuaOk69NxTZW0e4l97wG6AE9IGlJuXNPj09OxzpB0TqnjNTMzM2utnMxYOZ3SCfw0SdOAX+S2XQrcGBG9gJuBS5po6zvAyIjoDWwHTEuJwlnA4IjYAWgATsvt81oqvwIYlsrOAaamfn8K3Fiir4uBKyKiH/DfMvGMAXZNj/uSJScdgIHA2KK6Pwaei4jeEXF6KtseOAXYGvg8MKBMP+0jYsdUd3gqOx4gIrYFDgFukNQxv1NE7AMsTH3eWqZtJO0JbAHsCPQG+kjarVz9tM8xkhokNfBeYzXNzMzMWj4nM1ZO4WS6d0pCfp7b1h/4U3p8E1kS0JhJwBGSzga2jYh3gJ3JkoFxKVk6HNgkt8+d6fdkoEd6PDD1R0Q8DKwnqVtRXwOAW3KxlTKZ7MR/TWARMIEsqdmV5ZOZUiZGxL8jYgkwLRdfsaaOYTbwArBlBX2Wsmf6mQpMAXqSJTdlRcRVEdE3IvrSuZm9mpmZmbUQvmbGVobC13t/REqQ09Kr1QEiYkyaMdgLuCkt13oTeDAiDinTZuFakcUsfZ8ut5wr13dTZUs3RnwoaR5wBDAemAHsDmwGPN3YvkWxFcdXrl5Tx9CUkuOa2vp1RPyhGW2amZmZ1T3PzFhzjAcOTo8PBR5Lj+cBfdLjfYEOkF1jA7wSEVcD1wI7AI8DAyRtnup0ltTUDMWY1B+SBpEtRXu7qM64otgaa2tY+j0WOA6YFhHFidA7wJpNxFWN/DFsCWwMzGlin3mUGFdgJHBk4VojSZ+RtOFKjNXMzMysRXMyY81xEtmysRnAYcDJqfxq4EuSJgI7Ae+m8kFk18lMBQ4ALo6IV4GhwC2pncfJlkk15mygb6p/PtnStGInA8dLmgQUL0HLGwtsBEyIiJeB9ymxxCwiXidbCjerubdJLnI50E7STOBWYGgFdywrOa4RMYpsud+E1N7trNzEy8zMzKxF0/IfRJtZW6DuCo6tdRTWFsRw/z9jZmYrRtLkiOhbXO6ZGTMzMzMzq0tOZszMzMzMrC45mTEzMzMzs7rkWzObtVF9uvehYXhDrcMwMzMzazbPzJiZmZmZWV1yMmNmZmZmZnXJyYyZmZmZmdUlJzNmZmZmZlaXnMyYmZmZmVldcjJjZmZmZmZ1ycmMmZmZmZnVJSczZmZmZmZWl5zMmJmZmZlZXXIyY2ZmZmZmdcnJjJmZmZmZ1SUnM2ZmZmZmVpeczJiZmZmZWV1yMmNmZmZmZnVJEVHrGMysBiS9A8ypdRx1ZH3gtVoHUUc8XtXxeFXPY1Ydj1d1PF7VWRXjtUlEbFBc2P4T7tTMWq45EdG31kHUC0kNHq/Kebyq4/GqnsesOh6v6ni8qlPL8fIyMzMzMzMzq0tOZszMzMzMrC45mTFru66qdQB1xuNVHY9XdTxe1fOYVcfjVR2PV3VqNl6+AYCZmZmZmdUlz8yYmZmZmVldcjJjZmZmZmZ1ycmMWSslSbWOoZ54vKonyf+H2CfG/yar4/GqnsesOi31b36LDMrMmk9SV4DwBXEVkdQZPF7VkLQpQEQsaan/ubUkknaRtKMkf7dbBSR9TtIaQKdax1IP/De/ev67X52W/je/xQVkZs0naR/gWkl/lvQNSRvXOqaWTNJewJWSbpU0QFKHWsfU0knqB4yV9Etouf+5tRSSvg7cTu7E3J8Gl5f+Tf4FuA44RFJ7v7/K89/86vnvfnXq4W9+iwrGzJpP0pbAFcAlwARgAPA/kraqaWAtlKSvARcC1wBzgFOAtWoZU514FXgK+JykiyH7zw18kp6nzLrAMODIiHgUWD1t7lSoU6v4WiJJvYGLyP4tPgB8KSI+Kry/bFn+m189/91vlhb/N9/JjFnr0RF4LCLGRcTFwB1kf4SOlfTZ2obWskjqBBwEnBsRYyLi58AHwPdqG1nLlj6NWwi8CVwLdJR0jqRtJG3mJRtLReYNspOAkZI+BfxF0rXARZL6eLyWsxkwPiKeAP4B9JR0qaTTfIJe0hr4b37F/He/evXyN9/JjFnrMRvYXNIPASJiCvB34CNgS2g5n6LUWkQsBH4J3J+7juFJoFuhjqR2tYitJYuIJRHxMtkJ+ofAcGBn4GFgQ2i5F4jWQnpv9QD+FzgT+CvZF8s9CZwiaW3/m1zGROCrkq4DngbuAsYBawKHSVrD47WM2cDnJf0A/De/Kenv/nnAfbm/7/67X4Yk5f7mP0kL/ptf8wDMrPnSRcUDJA2MiA+AnwL9JB0MEBGTgTeA76bnLeJTlFpJ4zVQ0o4R8XxEzI+Ij9Lm50jLgCTtD+zhE4Fl3mM75YrbAd2BzwFbA9OAA2Dp8oO2Kjdeu6T31g+ATYF+EXF1mnX4O7AYeN//Jj8er/4R8S+gP3AfcG9E/DoibiFbQtUjIhZ5vLRB4eQxIj4EzgJ2kvTtVOa/+UXyYwb8OyLejojF6bn/7hcpjFdERO7Dvg7Ap2mhf/OdzJjVKUlfBe4B9gJuknQc2Sd1DwFfk3RSqvofYLV0d6A2q2i8bpV0gtJdgJJ2ZON0EHA+8FxbPxEoGrNbJJ2YNv2J7GTpXrI1598nW37wqVrE2VIUjdcfJZ0MvE12Hcgmki5MVfsAnwe61CTQFiI3XnsDf0p/s14im8HqKuk7qWo3YENJ3Uq31DZI2g+4jezGCIUZhMlkf/P38t/85RWPWUR8WJSsrIb/7n+sxHgVPuz7E9lyvBb5N19t+DUzq0vpD/HqwB+Av0XEXyRtD1wA3J1+tgT+H9mnTv2AfSJiek0CrrEy49WbbLxGAldExLvpxOqPZNPpP4yIp2oVc601MWYPkJ2AHp+2jUqf3rWPiPdrFXMtNfJv8rdkszCXkn2ieR3Z+2sg8J2ImFWjkGuqifH6B/A7sk99TwBeBLYBDmyr4wUgaRPgb8As4J/p920R8ZGk9YDtyP59zqWN/80vKDFmM8nGbHGaeVgi6StkJ+r+u9/4eH2W7GYm90XEP1ra33wnM2Z1StKPyNaSnx8RCyRtA/we+HNE/EHZ7SY3Bt6JiFdqGWtLUGK8vkg2XndExGWStgDuBA6OiCdrGWtLUWbMLgWuj4gbU53VWsIyg5agkffYnRFxaToB6AK0SzcHaNMaGa+bI+JaZRf9fxGYHBEv1DLWWkuzyFuTnWQeQvaB1eNkf78+SHUK12i97b/5ZcdsAtm/x8KYbU72AeCQtv53v6n3mKRuETE/zdgsbqytVc3LzMzq1wxgPWAzSe3Tp5bDgDOU3Snpw4h4zv+pfax4vJ4ETgdOS7MOzwO7tPX/0IqUG7PhacxaxHrpFqTceJ0qaYd0m+H5TmQ+Vmq8zgB+Kmm7iJgTEXe29UQGICIWADPSe+da4BmyC7EPAFB2Z6mPIuKf/pufKTNm/Vk6Zj0i4p9Af//db/Q9dmCqsk6q16ISGXAyY1Z3Cut9I+LvwALgZGAbSV3TxZ8PkF1cbFQ8XoqIxRHxTg1DbTGaGLMGsjGzpML3mJO+pML3V5u+CLuUiHhfktLSnhFkJ5tfkHQz2ZcarlPTAFugRsbsT8B4SWv77/5SZcarZ3qPjW+p7zEvMzOrA2m5xbpAA7Ak/8mIpN+SLdV4H/gX8D/AgIiYV4NQWwSPV/U8ZtXxeFXH41WdUuOVTjKj8DvV+yvQC9jP18h4zKrRmsbLyYxZCyfpW8CvyO5Q8x+yPzwjIuLtXJ3dyf7YbAlc1sYvYvR4VcljVh2PV3U8XtVpbLxyF663AzYHxgKDI2JG7SKuPY9ZdVrbeDmZMWvB0kX8fwQuiYhxkg4gW8O6CLggIuYX1W8fS2+l2OZ4vKrnMauOx6s6Hq/qNGO8NoiIV2sQaovhMatOaxwvXzNj1vKtBWyRHt9F9oVyq5PdbQRJO0vaK233tTIer+bwmFXH41Udj1d1mhqvnSR9A6Cln2SuQh6z6rSq8XIyY9aCRfYNz/8LfEvSrunOUY+Rffvursq+FG1jYEqq36anWj1e1fOYVcfjVR2PV3UqHK9NgKm1i7Jl8ZhVpzWOl5eZmbVwkjqSfdtuL+CPETEmlT8CHBsRz9QyvpbG41U9j1l1PF7V8XhVx+NVPY9ZdVrbeLWvdQBm1rh0q8SbgQB+Iqkn2drWDYH5je7cBnm8qucxq47Hqzoer+p4vKrnMatOaxsvz8yY1QlJqwMDgGPJbmF6cUTUzTTwqubxqp7HrDoer+p4vKrj8aqex6w6rWW8nMyY1Zl0u8QIf/N6RTxe1fOYVcfjVR2PV3U8XtXzmFWn3sfLyYyZmZmZmdUl383MzMzMzMzqkpMZMzMzMzOrS05mzMzMzMysLjmZMTMzMzOzuuRkxszMbBWStGAV99dD0ndWZZ9mZquKkxkzM7NWSlJ7oAfgZMbMWqX2tQ7AzMysLZI0CDgHeBnoDdwJzAROBjoB+0XEc5JGkH2h3ReBTwGnRcR9kjoCVwB9gY9S+SOShgJ7AR2BLkBn4AuSpgE3AHcBN6VtACdExPgUz9nAa8A2wGTguxERkvoBF6d9FgF7AO8B5wODgDWAyyLiDytzjMzMmuJkxszMrHa2A74AvAE8D1wTETtKOhk4ETgl1esBfAnYDHhE0ubA8QARsa2knsAoSVum+v2BXhHxRkpShkXE3gCSOgNfiYj3JW0B3EKWEAFsT5Y0vQiMAwZImgjcCgyJiEmS1gIWAkcB8yOin6Q1gHGSRkXE3JU+SmZmZTiZMTMzq51JEfESgKTngFGpfCawe67eX9K3cz8r6XmgJzAQ+D1ARMyW9AJQSGYejIg3yvTZAbhUUm9gcW4fgIkR8e8UzzSyJGo+8FJETEp9vZ227wn0knRg2rcbsAXgZMbMVhknM2ZmZrWzKPd4Se75Epb9PzqK9gtAjbT7biPbTiVb2rYd2bWz75eJZ3GKQSX6J5WfGBEjG+nLzOwT5RsAmJmZtXwHSVpN0mbA54E5wBjgUIC0vGzjVF7sHWDN3PNuZDMtS4DDgHZN9D0b6J6um0HSmunGAiOBH0jqUIhBUpdG2jEzW+k8M2NmZtbyzQEeJbsBwHHpepfLgSslzSS7AcDQiFgkLTdhMwP4SNJ0YARwOXCHpIOAR2h8FoeI+EDSEOD3kjqRXS8zGLiGbBnaFGWdvgrstxKO1cysYoooNXNsZmZmLUG6m9l9EXF7rWMxM2tpvMzMzMzMzMzqkmdmzMzMzMysLnlmxszMzMzM6pKTGTMzMzMzq0tOZszMzMzMrC45mTEzMzMzs7rkZMbMzMzMzOqSkxkzMzMzM6tL/x/sy8Bb1mSZxgAAAABJRU5ErkJggg==\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "best_model, importances = ML.perform_random_forest(splits, 'Xar_train', 'yar_train', 'Xar_test', 'yar_test', save_df, random_state)" ] }, { "cell_type": "markdown", "id": "7f062b68-7b5b-4d69-8aac-427e7b9d355e", "metadata": {}, "source": [ "### Vulnerability" ] }, { "cell_type": "code", "execution_count": 28, "id": "37495d6d-dd2b-4db9-82b2-1edf46bbf9a5", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "MSE: 0.00015487748787118143\n", "RMSE: 0.012444978419876084\n", "MAE: 0.0017970720583366875\n" ] }, { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "best_model, importances = ML.perform_random_forest(splits, 'Xvr_train', 'yvr_train', 'Xvr_test', 'yvr_test', save_df, random_state)" ] }, { "cell_type": "markdown", "id": "3055eeaf-6d05-4677-8802-2b404e83e210", "metadata": {}, "source": [ "### Resilience" ] }, { "cell_type": "code", "execution_count": 29, "id": "7ef5a02e-0a62-489b-aaa2-2db5e5d4ae69", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "MSE: 0.0005067027843961834\n", "RMSE: 0.02251005962666877\n", "MAE: 0.004664485230912826\n" ] }, { "data": { "image/png": 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\n", 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" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "best_model, importances = ML.perform_random_forest(splits, 'Xrr_train', 'yrr_train', 'Xrr_test', 'yrr_test', save_df, random_state)" ] }, { "cell_type": "markdown", "id": "6b45b1ad-29fc-4e36-947d-46f95fcfaef9", "metadata": {}, "source": [ "## XGBoost Regression" ] }, { "cell_type": "markdown", "id": "d76344a2-5240-4b1b-982e-9249be265aac", "metadata": {}, "source": [ "XGBoost Regression is a type of regression algorithm that uses an ensemble of decision trees to make predictions. It is an extension of the gradient boosting algorithm, and is known for its high predictive power and speed.\n", "\n", "Pros:\n", "- High accuracy: XGBoost Regression is known for its high accuracy and predictive power, making it a popular choice for regression tasks.\n", "- Speed: XGBoost Regression is optimized for performance, and can handle large datasets with ease.\n", "- Handles missing data: XGBoost Regression can handle missing data by using regularization techniques.\n", "- Feature importance: XGBoost Regression provides a feature importance score, which can help identify the most important variables in the dataset.\n", "\n", "Cons:\n", "- Overfitting: XGBoost Regression can be prone to overfitting if the hyperparameters are not tuned correctly.\n", "- Complexity: XGBoost Regression can be more complex to implement and tune than simpler regression algorithms.\n", "- Black box: Like other ensemble methods, XGBoost Regression can be difficult to interpret due to its black box nature." ] }, { "cell_type": "markdown", "id": "1cfc725b-2d7f-496f-b695-902cd11b8e3a", "metadata": {}, "source": [ "### Adaptability" ] }, { "cell_type": "code", "execution_count": 30, "id": "c91ba69c-23fd-42be-8282-cc578a46565d", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Best Hyperparameters: {'learning_rate': 0.01, 'max_depth': 3, 'n_estimators': 1000}\n", "Best Score: 0.12872455679372036\n", "MSE: 0.00033268993823605964\n", "RMSE: 0.018239789972366995\n", "MAE: 0.006439004628337608\n" ] }, { "data": { "image/png": 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zM2sLfAMAsxpExDWU/XaNmZmZmdWXZ2bMzMzMzKyQPDNj1k7169mPhlEN9Q7DzMzMrMU8M2NmZmZmZoXkZMbMzMzMzArJyYyZmZmZmRWSf2fGrJ3y78xYUa3K3zUwM7PVg39nxszMzMzM2hQnM2ZmZmZmVkhOZszMzMzMrJCczJiZmZmZWSE5makTSZ+U9FdJT0l6WtL5ktasYzx7S5olaa6k2ZL2XoV9P9LM+mdIGllLuaQFkjZY0Rhz7e0p6Yet1NY4Sf1zr3tJmlPDfndLWif9fb81YjEzMzMrIiczdSBJwC3AbRHxWWALoDvw81XUf8ey19sCvwH2iojewJ7AbyT1WRXxRMTOq6Kf1hARt0fEOXWO4WsR8TqwDuBkxszMzNotJzP18UXg3Yi4CiAilgAnAYdJ6pq+ee8DIGm6pJ+m52dJ+q6kIelb/b+kmZTrUoKEpH6SHpQ0VdIYSRun8nGSfiHpQeCEsnhGAr+IiPkpnvnAL4FT0r6bS/q7pJmSpknaLJWfmmZxZko6J9dP//R8A0kL0vMRaSbqHknzJI0qdS5pYe75KZKmpFmiM3Plp6X9/g5s2ZJBl3SypDnp78RUtsxsiKSRks5Iz4+X9HiK5YbccVyUno+WdIGkRyQ9I2m/VL6GpEskPSbpzvR+7tfMWEdIuiWN11OSfp3bVpptOgfYTNIMSedK2ljS+PR6jqRdWjJOZmZmZkXRsekqthJ8HpiaL4iINyX9E9gcGA/skhKBD4BBqdpg4I/AxsB2qZ1/Aw8DgyQ9ClxINsPykqThZLM9h6X914mIL1SJ5zdlZQ3AMen5dcA5EXGrpM7AGpK+CuwN7BgR70har4bj3gHYGngHmCLprohoKG2UtDvw2VRPwO2SdgXeBg5Ix9wRmEbZ+OWcJOnbudc9U9v9gEOBHVPbj6bE7rVG4v0h8OmIWCxpnSp1NiZ7X3oDtwN/Ab4B9AK2ATYCngCubKSfavqSHfNiYJ6kCyPi/8ri2zoi+gJI+n/AmIj4uaQOQNcW9GlmZmZWGE5m6kNApV99K5VPAI4H5gN3AV+S1BXoFRHz0mzL5Ih4DkDSDLIPz6+TJQv3pomaDsDzufZvbEY8AkJSD+ATEXErQES8m/ocBlwVEe+k8ldrOO57I+KVtP8tZElAQ2777ulvenrdnSy56QHcWupL0u2N9HFeRHyYmJVmhlJft0bE27n+dyFLQKqZBVwn6Tbgtip1bouIpcDjkj6e6+umVP4fSQ9U2bfSOZAvuy8i3kjxPg5sCvxfhX1KpgBXSuqU4ppRXkHSkcCRAKzdSEtmZmZmBeBlZvXxGLDML5hK+hjwKeBpsg+l/ck+bI8n+3B/BMvORizOPV9ClpgKeCwi+qa/bSJi91y9t2uNB9geeDy1WUm1hOwDPjqvOpdtK69fKYH6ZS7+zSPiD1XqNle148jHC8vGvAdwMdAPmKqya42S/PugssemvAKsm3u9HvBylbZL73FVETEe2BX4F3CtpO9UqHNZRPSPiP6etzEzM7OiczJTH/cBXUsfNtOSoP8BRkfEOxHxHtk38N8EJpHN1IxMj42ZB2woaWBqt5Okz9cQz2+AH0nqlfbrBfwY+J+IeBN4TunuZpLWSrNEY0nX+KTy0jKzBWQf/gHKrxP5kqT1JHUhW6L2cNn2ManN7qnNT0jaiCyh20dSlzRT9N81HFO58cDeyq5J6gbsQzaeLwAbSVpf0lrA11PfawCfiogHgFPJLrbvXmNfDwH7pmtnPg4MqVJvHPBtpWk04BCg2ixOJW+RzVqRYt4UeDEiLgf+QJaQmpmZmbVZXmZWBxERkvYBLpH0E7Kk8m6yBKJkArBbuh5lAvBJmkhmIuK9dKH5BZLWJnt/f0s289LYfjMk/QC4Iy1Reh84NbdM6WDg95J+lrbtHxH3SOoLNEh6Lxf/b4A/SzoYuL+sq4eAa8muC/pT/nqZFMdYSZ8DJqbP9wuBb0fENEk3AjOAZ5sahyrHOE3SaGByKroiIqYDpON6lGxZ39y0vQPwxzSOIlu+9vpHeUejbgZ2A+YAT6a236hQ7zKya21mSgqyJXc/asYxvSLp4XQDg7+l/k6R9D7Z2C03M2NmZmbWlihiRVfvmDVN0gigf0QcW+9YVgVJ3SNioaT1yRKoQRHxn3rHlaeeCo6qdxRmzRej/P8tM7P2RtLUiCi/LMIzM2YryZ3pDmhrAmetbomMmZmZWVvgZMZWiYgYDYyucxirTEQMqXcMZmZmZm2dbwBgZmZmZmaF5JkZs3aqX89+NIxqaLqimZmZ2WrKMzNmZmZmZlZITmbMzMzMzKyQnMyYmZmZmVkhOZkxMzMzM7NC8o9mmrVT/tFMW9X8Y5dmZtZS1X400zMzZmZmZmZWSE5mzMzMzMyskJzMmJmZmZlZITmZMTMzMzOzQnIyYzWRtETSDElzJN0kqWsdYhgiaecq286QNLKZ7S1sncg+bG+BpNmSZkoaK+m/WrP9sr56SfrWymrfzMzMrAiczFitFkVE34jYGngPOLqWnSR1bMUYhgAVk5nVyNCI2BZoAH68MjpIY9oLcDJjZmZm7ZqTGWuJCcDmkrpJulLSFEnTJe0FIGlEmr25Axgrqbukq9KsxSxJ+6Z6u0uaKGlaqt89lS+QdGYqny2pt6ReZAnUSWmGaJcKcW0r6X5JT0k6olQo6ZQU4yxJZ5bvpMy5adZptqThqfwSSXum57dKujI9P1zS2U2M0fg0Rp1zxz5d0tDUxqOSPp+LYZykfrWOKXAOsEsai5MkTZDUN9few5L6NBGjmZmZWaG15rfm1g6kWYGvAvcApwH3R8RhktYBJkv6e6o6EOgTEa9K+hXwRkRsk9pYV9IGwOnAsIh4W9IPgJOBn6X9X46I7SV9HxgZEd+VdCmwMCJ+UyW8PsBOQDdguqS7gK2BzwI7AAJul7RrRIzP7fcNoC+wLbABMEXSeLKEZBfgduATwMap/mDghiaG6uvAbOAYgIjYRlJvsuRui7T/N4FRkjYGekbEVEm/qHFMh6Rx+Xoa01eBEcCJqf21ImJWeVCSjgSOBGDtJo7AzMzMbDXnmRmrVRdJM8iWT/0T+AOwO/DDVD4O6AxskurfGxGvpufDgItLDUXEa2RJx1bAw2n/Q4BNc/3dkh6nki2pqsVfI2JRRLwMPECWwOye/qYD04DeZMlN3mDg+ohYEhEvAA8CA8hmoHaRtBXwOPBCSjwGAo9UieGBdDwfA36Z2r42Hfdc4FlgC+DPwP5pn28CN6XntY5puZuAr0vqBBwGjK5UKSIui4j+EdGfVX7Vk5mZmVnr8syM1WpRRPTNF0gSsG9EzCsr3xF4O18ElP/0t8g+nB9Ypb/F6XEJtZ+n5X1E6ueXEfH7RvZTxcYi/iVpXeArZLM065ElHgsj4q0qbQ1NyVTWcDZG1dp+JS0FGw4clYulljEtb+8dSfcCe6UYl/uFXDMzM7O2xjMztiLGAMeVPrBL2q5KvbHAsaUXKUGYBAyStHkq65qWRzXmLaBHI9v3SteorE92s4ApKcbDctfjfELSRmX7jQeGS+ogaUNgV2By2jYRODHVmQCMTI+1Gg8clPregmyWpZSo3ACcCqwdEbNTWa1jWmksrgAuAKY0MoNjZmZm1mY4mbEVcRbQCZglaU56XcnZwLrpAvuZZLMXL5Fd43G9pFlkyU3vJvq7A9inkRsATAbuSm2dFRH/joixwJ+AiZJmA39h+STgVmAWMBO4Hzg1Iv6Ttk0AOkbEP8iWqa1H85KZS4AOqe8bgRERUZp1+gtwANmSs5Jax3QW8IGy20CfBBARU4E3gauaEZ+ZmZlZYSmifGWOmRWRpJ5k19n0joilTdbvqfhwcZvZKhCj/P8bMzNrGUlTI2K5ZfSemTFrAyR9B3gUOK2WRMbMzMysLfANAMzagIi4Brim3nGYmZmZrUqemTEzMzMzs0LyzIxZO9WvZz8aRjXUOwwzMzOzFvPMjJmZmZmZFZKTGTMzMzMzKyQnM2ZmZmZmVkj+nRmzdsq/M2Pl/DswZma2uvLvzJiZmZmZWZviZMbMzMzMzArJyYyZmZmZmRWSkxkzMzMzMyskJzMVSFoiaYakOZJuktS1DjEMkbRzM/dZS9LfU+zDy7aNljQ/bZspabcViO3E1hgTSUdKmpv+JksavKJt1thvT0l/aeY+oyXtV0u5pIUrGmNZe0dL+k5rtmlmZmbWFjiZqWxRRPSNiK2B94Cja9lJUsdWjGEI0KxkBtgO6JRiv7HC9lMioi9wInDpCsR2ItCsZEZSh7LXXweOAgZHRG+yMf6TpP9agbhqEhH/jojlEpPVVURcGhHX1DsOMzMzs9WNk5mmTQA2l9RN0pWSpkiaLmkvAEkj0uzNHcBYSd0lXSVptqRZkvZN9XaXNFHStFS/eypfIOnMVD5bUm9Jvcg+3J+UZlJ2yQckaT1Jt6X2J0nqI2kj4I9A37TPZo0c00TgE6mtDpLOTcc1S9JRqXyIpHGS/pJmTq5T5nigJ/CApAdqOLafSnoI2L8shh+QJVcvA0TENOBq4Ji07wBJj6RZpMmSeqRYf5Mb2+Ny/WyQnveXNC49P0PStZLul/SUpCNSeS9Jc5o4fkm6SNLjku4CNqrlZCl7n5TanpNiHp4b2ztz9S6SNCI9Pyf1OUvSb3LHMTI9HyfpV2lMniydG5K6Svpz2u9GSY9KWu72hWZmZmZtSWvOJLQ5aablq8A9wGnA/RFxmKR1gMmS/p6qDgT6RMSrkn4FvBER26Q21k0ftE8HhkXE25J+AJwM/Czt/3JEbC/p+8DIiPiupEuBhRHxmwqhnQlMj4i9JX0RuCYi+kr6btr/600c2leA29Lzw1O8AyStBTwsaWzath3weeDfwMPAoIi4QNLJwNCIeLmGY3s3IiotH/s8MLWsrAE4RNKawI3A8IiYIuljwCLgSODTwHYR8YGk9Zo4ToA+wE5AN2B6Skzyqh3/dsCWwDbAx4HHgSur9HGupNMrlH8D6AtsC2wATJE0vlqg6Xj2AXpHRKTzrJKOEbGDpK8Bo4BhwPeB1yKij6StgRnV+jEzMzNrK5zMVNZF0oz0fALwB+ARYM/SN+RAZ2CT9PzeiHg1PR8GHFBqKCJeU7akaiuyD8oAa5LNjpTckh6nkn0AbspgYN/U/v2S1pe0dg37nSvp12SzDDulst2BPvrouo+1gc+SLa+bHBHPAaTx6AU8VNbmTk0cW6XlbtUICLIk4vmImJKO8c0UwzDg0oj4IJW/Wq2hnL9GxCJgUZpJ2oFlP+hXO/5dgesjYgnwb0n3N9LHKRHx4TU4+uiamcG5Nl6Q9CAwAHizSjtvAu8CV6Sk684q9fLnS69cX+cDRMQcSbMq7SjpSLKkMDtSMzMzswJzMlPZonRtyYeUfVLfNyLmlZXvCLydLyL7QE5Z2b0RcWCV/hanxyXU9p6oQlktP919CtkH4ePJlnT1S20dFxFjlulAGpKLq7HYmjq2t6uUP576zycJ26fySmNII+Uf8NGSyc5l28rrV3pvKh3/16r01RyV3idYNl5IMafZph2A3cgS4mOBL1bYv9L5Uq2vZUTEZcBlAOop/9y7mZmZFZqvmandGOC4lNQgabsq9caSfQgl1VsXmAQMkrR5KusqaYsm+nsL6FFl23jgoNTWELJlatW+7V9GRCwl+wZ/DUlfJjuu70nqlNrbQlK3ZsTWkmMD+DXwK0nrp/36AiOAS4C5QE9JA9K2HmnJ31jg6PS8tCwLYAFZYgRpxipnL0mdUz9DgCll26sd/3jggHRNzcbA0BqOqdx4YHhqY0Oy2Z7JwLPAVsruPrc2WfKCsmuN1o6Iu8lustC3GX09BHwztbMV2fI4MzMzszbNMzO1Owv4LTArJTQLgErXppwNXKzsAvMlwJkRcUu6wPv6dF0GZNeZPNlIf3cAf1F2o4HjImJCbtsZwFVpKdE7wCHNOZB0PcbZwKnAl8iWKk1Lx/USsHcTTVwG/E3S8xExtAXHRkTcLukTwCOSgixB+nZEPA+QLpa/UFIXsutlhgFXAFuQvQfvA5cDF5FdQ/QHST8GHi3rajJwF9mSwLMi4t/KbrBQckWV47+VbFZkdjqWB5sYk0puJbueaibZLM+pEfGfdHx/BmYBTwHTU/0ewF8ldSabaTmpGX1dAlydzonpqe03WhCzmZmZWWEowitNrG2SdAbVb6LQpii79XWniHhX2Z3s7gO2iIj3qu7TU8FRqyxEK4AY5f8fmJnZ6knS1IhY7k6tnpkxaxu6kt0uuxPZrM73GktkzMzMzNoCJzPWZkXEGfWOYVWJiLcA/66MmZmZtSu+AYCZmZmZmRWSZ2bM2ql+PfvRMKqh3mGYmZmZtZhnZszMzMzMrJCczJiZmZmZWSE5mTEzMzMzs0JyMmNmZmZmZoXkH800a6f8o5ntl38c08zMiqbaj2Z6ZsbMzMzMzArJyYyZmZmZmRWSkxkzMzMzMyskJzNmZmZmZlZITmasXZAUkq7Nve4o6SVJdzaznXGS+qfnd0tapxViG5FimSFprqSTVqCtvSVttaIxmZmZmRWBkxlrL94GtpbUJb3+EvCvFWkwIr4WEa+vaGDJjRHRFxgEnCbpUy1sZ2/AyYyZmZm1C05mrD35G7BHen4gcH1pg6Rukq6UNEXSdEl7pfIukm6QNEvSjUCX3D4LJG2Qnt8maaqkxyQdmauzUNLPJc2UNEnSxxsLMCJeAf4BbJz2/7akyWnW5veSOlRrV9LOwJ7Auan+Zis+ZGZmZmarLycz1p7cABwgqTPQB3g0t+004P6IGAAMJUsIugHfA96JiD7Az4F+Vdo+LCL6Af2B4yWtn8q7AZMiYltgPHBEYwFK2gToDMyS9DlgODAozdosAQ6q1m5EPALcDpwSEX0j4ukK7R8pqUFSA+80FomZmZnZ6q9jvQMwW1UiYpakXmSzMneXbd4d2FPSyPS6M7AJsCtwQW7/WVWaP17SPun5p4DPAq8A7wGl63Kmki1vq2S4pKHAlmSJybuSdiNLnqZIgmxW6MVUv9Z2lxERlwGXQfrRTDMzM7MCczJj7c3twG+AIcD6uXIB+0bEvHzllEQ0+qFf0hBgGDAwIt6RNI4sGQJ4PyJK+y+h+n9zN0bEsZIGAndJ+luK6eqI+FGF+rW2a2ZmZtZmeZmZtTdXAj+LiNll5WOA45SyF0nbpfLxpKVdkrYmW55Wbm3gtZTI9AZ2amlwETERuBY4AbgP2E/SRqn/9SRt2kQTbwE9Wtq/mZmZWZE4mbF2JSKei4jzK2w6C+hEdq3KnPQa4HdA97S87FRgcoV97wE6pjpnAZNWMMxfAYcC/wecDoxNbd9LujFAI24ATkk3MfANAMzMzKxN00crVcysPVFPBUfVOwqrhxjlf/fNzKxYJE2NiP7l5Z6ZMTMzMzOzQnIyY2ZmZmZmheRkxszMzMzMCsm3czVrp/r17EfDqIZ6h2FmZmbWYp6ZMTMzMzOzQnIyY2ZmZmZmheRkxszMzMzMCsm/M2PWTvl3ZorFvw1jZmbtmX9nxszMzMzM2hQnM2ZmZmZmVkhOZszMzMzMrJCczJiZmZmZWSE5mbGaSFoiaYakOZJuktS1DjEMkbRzlW0jJIWk3XJl+6Sy/Zpod4GkDSqUHy3pO+n56KbaKdv3DEkja+nHzMzMzFrGyYzValFE9I2IrYH3gKNr2UlSx1aMYQhQMZlJZgMH5l4fAMxsaWcRcWlEXNPS/c3MzMxs5XIyYy0xAdhcUjdJV0qaImm6pL3gw1mSmyTdAYyV1F3SVZJmS5olad9Ub3dJEyVNS/W7p/IFks5M5bMl9ZbUiyyBOinNEO1SJa4dJHVKbW0OzChtlLRbinN2inut3L6nSJqc/jZP9ZebXUnl/SQ9KGmqpDGSNm7uAEo6Oc1yzZF0YirrJWmupCtS+XWShkl6WNJTknZI9aqN++dT/DPSOH+2uXGZmZmZFYmTGWuWNNPyVbJZkNOA+yNiADAUOFdSt1R1IHBIRHwR+AnwRkRsExF9gPvTcqvTgWERsT3QAJyc6+rlVP47YGRELAAuBc5LM0QTKoQXwN+BLwN7Abfn4u4MjAaGR8Q2QEfge7l934yIHYCLgN82cvydgAuB/SKiH3Al8PMq1UuJ1wxJM4CeqY1+wKHAjsBOwBGStkv7bA6cD/QBegPfAgYDI4EfpzrVxv1o4PyI6Av0B56rdhxmZmZmbYGTGatVl/SBvAH4J/AHYHfgh6l8HNAZ2CTVvzciXk3PhwEXlxqKiNfIPsRvBTyc9j8E2DTX3y3pcSrQqxlx3kC2vOwA4Ppc+ZbA/Ih4Mr2+Gtg1t/363OPARtrfEtgauDfFfTrwySp1S4lX35Rg/DuVDwZujYi3I2Ih2bGWZprmR8TsiFgKPAbcF9kv287mo3GoNu4TgR9L+gGwaUQsKg9I0pGSGiQ18E4jR2lmZmZWAK15PYO1bYvSB/IPSRKwb0TMKyvfEXg7X0Q2a0JZ2b0RcSCVLU6PS2jGeRoRkyVtneJ9Mgvxw/4a3bXK83ICHouIxhKepjQWy+Lc86W510v5aBwqjjvwhKRHgT2AMZK+GxH35ytExGXAZQDqKf+kvJmZmRWaZ2ZsRYwBjktJDbmlUuXGAseWXkhaF5gEDMpdn9JV0hZN9PcW0KOGuH7ER0uySuYCvUr9AQcDD+a2D889Tmyk7XnAhpIGprg7Sfp8DTHljQf2TsfcDdiH7HqfWlUcd0mfAZ6JiAvIltj1aWZcZmZmZoXiZMZWxFlAJ2CWpDnpdSVnA+umi9pnAkMj4iVgBHC9pFlkyU3vJvq7A9inkRsAABARf4uIB8rK3iW7TuUmSbPJZjouzVVZK81qnACc1Ejb7wH7Ab9KxzKDxu+wVqmNaWTX70wGHgWuiIjpzWii2rgPB+ak5We9Ad+JzczMzNo0Zcvxzay9UU8FR9U7CqtVjPK/1WZm1n5JmhoR/cvLPTNjZmZmZmaF5GTGzMzMzMwKycmMmZmZmZkVkm/NbNZO9evZj4ZRDfUOw8zMzKzFPDNjZmZmZmaF5GTGzMzMzMwKycmMmZmZmZkVkn9nxqyd8u/MFIN/X8bMzMy/M2NmZmZmZm2MkxkzMzMzMyskJzNmZmZmZlZITmbMzMzMzKyQnMyYmZmZmVkhOZlp4yQtLHs9QtJFrdzH3ZLWaYV2hki6s6xstKT9mthvT0k/TM/3lrTVisayupLUX9IF6Xmrv5dmZmZmRdKx3gFY8UXE1+rc/+3A7enl3sCdwOOrom9JHSJiyaroCyAiGoCGVdWfmZmZ2erMMzPtmKRNJd0naVZ63CSVLzMbUprdkbSxpPGSZkiaI2mXVL5A0gaSekl6QtLlkh6TNFZSl1RnQOpnoqRzJc1pQbwLJJ0paZqk2ZJ6p/IRki6StDOwJ3BuinEzScdLejz1fUOFNkdI+qukeyTNkzQqt+3bkiantn4vqUNpPCT9TNKjwMCy9pbrT9L6aSymp3aelbRBhVgWSvqVpKmS/i5pB0njJD0jac9UZ7nZq1S+oaSbJU1Jf4OaO75mZmZmReNkpu3rkj6Mz5A0A/hZbttFwDUR0Qe4Drigiba+BYyJiL7AtsCMCnU+C1wcEZ8HXgf2TeVXAUdHxEBgRWYyXo6I7YHfASPzGyLiEbIZmlMiom9EPA38ENguHePRVdrcATgI6Avsn5ZyfQ4YDgxKx7sk1QHoBsyJiB0j4qGytir1Nwp4KCK2S/FtUiWObsC4iOgHvAWcDXwJ2Idl37dKzgfOi4gBZGN+RaVKko6U1CCpgXeaaNHMzMxsNedlZm3fovRhHMhmIoDSr6cOBL6Rnl8L/LqJtqYAV0rqBNwWETMq1JmfK58K9ErX0/RIyQbAn4CvV9i32k+d58tvybX9jQp1y80CrpN0G3BblTr3RsQrAJJuAQYDHwD9gCmSALoAL6b6S4Cbm9HfrqVYI+IuSa9V2fc94J70fDawOCLelzQb6NXIMQIMA7ZKsQJ8TFKPiHgrXykiLgMuA1BP+aflzczMrNA8M2N5pQ+3H5DODWWfjtcEiIjxZB/M/wVcK+k7FdpYnHu+hCxhVoV6lbwCrFtWth7wcoX2S203ZQ/gYrLEZKqkSvuUf6gPspivTjM8fSNiy4g4I21/t5HrZKr1V0vi8H5ElOotJR1rRCyl6WNdAxiYi/cT5YmMmZmZWVvjZKZ9ewQ4ID0/CCgtmVpA9mEcYC+gE2TX2AAvRsTlwB+A7WvpJCJeA96StFMqOqBK1aeAnmmJV6m/asvZqnkL6JH2XwP4VEQ8AJwKrAN0r7DPlyStl67v2Rt4GLgP2E/SRqmt9VI8VTXS33jSEjVJX2X5hK01jAWOzcXSdyX0YWZmZrZa8TKz9u14smVjpwAvAYem8suBv0qaTPah/u1UPgQ4RdL7wEKg0sxMNYcDl0t6GxgHvFFeISIWS/o2cJWkzsD7wHcjYrm6jbgh9XM8WdL0B0lrk820nBcRr1fY5yGyZXabA39KdwxD0unA2JSkvA8cAzzbSN8dgD+W9yfpTOB6SdOAB4F/NuN4anU8cLGkWWT/XY+n+jVCZmZmZm2CPlrVYrbySOoeEaW7ov0Q2DgiTqhzWB9eQxQRxzZVtxX7XJD6fLmpuis1jp4KjqpnBFaLGOV/o83MzCRNjYj+5eWembFVZQ9JPyI7554FRtQ3HDMzMzMrOs/MmLVTnpkpBs/MmJmZVZ+Z8Q0AzMzMzMyskLzMzKyd6tezHw2jGuodhpmZmVmLeWbGzMzMzMwKycmMmZmZmZkVkpMZMzMzMzMrJN/NzKyd8t3MVj++c5mZmVllvpuZmZmZmZm1KU5mzMzMzMyskJzMmJmZmZlZITmZMTMzMzOzQnIys5qRtETSjNxfr5XY1wJJG9RYdy9Jt+Ve/0jSP3Kv/1vS7c3o+wxJIyuU907HPV3SZrW211KSRkh6KfX5uKQjVnafVeI4UVLXevRtZmZmVlROZlY/iyKib+5vQb0DSh4BBuZeDwTelLRRer0z8HAtDUnq2MjmvYG/RsR2EfF0DW1J0oqexzdGRF9gCPALSR+vZacmjqO5TgSczJiZmZk1g5OZApDUT9KDkqZKGiNp41Q+TtJ5ksZLekLSAEm3SHpK0tm5/W9L+z4m6cgqfXxb0uQ0Q/F7SR3y2yPiJeANSZunok8AN5MlMaTHRyRtKuk+SbPS4yap/dGS/lfSA8Cvyvo+QtLfJO1B9qH+u6kekk6WNCf9nZjKeqXjvQSYBnxK0qmSZkuaKemcVG8zSfekY58gqXdj4xwRLwJPA5s2Mea/kPQgcEIa80dSv5Ml9ZDUQdK5kqakcTgq7Tsk7f8XSXMlXZeSseOBnsADueP+naSG9J6dmRurr6V9H5J0gaQ7U3k3SVemPqdL2quxYzUzMzNrC1rzm2VrHV0kzUjP5wPfBC4E9oqIlyQNB34OHJbqvBcRu0o6Afgr0A94FXha0nkR8QpwWES8KqkLMEXSzakcAEmfA4YDgyLi/ZQkHARcUxbbI8DOKdF5CpgEfDl9oO4DTAFuAq6JiKslHQZcQDbbArAFMCwilkg6I/V9LLA7sHdELJZ0KbAwIn4jqR9wKLAjIODRlES8BmwJHBoR35f01dTHjhHxjqT1Un+XAUdHxFOSdgQuAb5YbeAlfQb4DPAscGsjY75ORHxB0prAXGB4REyR9DFgEXA48EZEDJC0FvCwpLFp3+2AzwP/JpvJGhQRF0g6GRgaES+neqel96wDcJ+kPsCTwO+BXSNivqTrc+GfBtwfEYdJWgeYLOnvEfF2teM1MzMzKzonM6ufRWnJEwCStga2Bu6VBNABeD5Xv3SdymzgsYh4Pu33DPAp4BXgeEn7pHqfAj6bykt2I0uCpqQ+ugAvVojtYbIZmA7ARGAy8FOyD+jzIuJdSQOBb6T61wK/zu1/U0Qsyb0+GHiOLJF5v0J/g4FbSx/IJd0C7JKO+dmImJTqDQOuioh3AFIS0D3FelM6JoC1KvQBMFzSYGAxcBSwIY2P+Y3pcUvg+YiYkvp9M8W5O9BH0n6p3tpkY/4eMDkinkv1ZgC9gIcqxPTNNIvWEdgY2IpsJvWZiJif6lwPlGbadgf21EfXIXUGNgGeyDea2jzyw6jMzMzMCszJzOpPZEnKwCrbF6fHpbnnpdcdJQ0h+7A/MM1ajCP7oFvex9UR8aMmYnkEOI7sw/3lEfGWpM5k15pUu14m/5Pm5bMEc4C+wCfJZqHKqUJZpbZU1g9kH/xfzyeGjbgxIo79sDFpGxof81LflfotlR8XEWOWKczei/x7tIQK/w1K+jQwEhgQEa9JGk32njU2HgL2jYh5jdQhIi4jm7FCPeWfmzczM7NC8zUzq795wIZpxgNJnSR9vhn7rw28lhKZ3sBOFercB+yndDG/pPUkbVqh3uNk13bsAkxPZTOAo8kSHdLjAen5QVSedSiZTjYTcruknhW2jwf2ltRVUjdgH2BChXpjgcOU7gYmab00SzJf0v6pTJK2bSSWvFrHfC7QU9KAVK+HspsCjAG+J6lTKt8ixd+Yt4Ae6fnHyBKmN5TdjOCruf4+o4/ucDc8t/8Y4DilqSRJ29V4rGZmZmaF5WRmNRcR7wH7Ab+SNJMsedi50Z2WdQ/ZDM0s4Cyy61zK+3gcOB0Ym+rdS7a0qbxeAI8CL+eWhU0ku86klMwcDxya2jkYOKGJ43uIbBbiLpXdJjoipgGjyZazPQpcERHTK7RxD9nSs4a0dKu01Oog4PA0bo8BNV0UX+uYp3rDgQtTvXvJZlCuIEv8pkmaQ3adS1OzoJcBf5P0QETMJEv0HgOuJM16RcQi4PvAPZIeAl4A3kj7nwV0AmalPs+q5VjNzMzMikzZ51MzKwJJ3SNiYZqBuRh4KiLOa1FbPRUc1brx2YqJUf732MzMrBJJUyOif3m5Z2bMiuWINPv0GNkSwt/XNxwzMzOz+vENAMwKJM3CtGgmxszMzKyt8cyMmZmZmZkVkmdmzNqpfj370TCqod5hmJmZmbWYZ2bMzMzMzKyQnMyYmZmZmVkhOZkxMzMzM7NC8u/MmLVT/p2ZVc+/I2NmZtYy/p0ZMzMzMzNrU5zMmJmZmZlZITmZMTMzMzOzQnIyY2ZmZmZmheRkxszMzMzMCsnJTBsnaYmkGZLmSLpJUtc6xDBE0s4rqe1ekuasYBvjJM1L4zRD0katFd/KlOJe7q4ekkZIuqgeMZmZmZmtSk5m2r5FEdE3IrYG3gOOrmUnSR1bMYYhwEpJZppLUocqmw5K49Q3Il5cRbG05hibmZmZtTtOZtqXCcDmkrpJulLSFEnTJe0FH36jf5OkO4CxkrpLukrSbEmzJO2b6u0uaaKkaal+91S+QNKZqXy2pN6SepElUCelWY9d8gFJOkPSyNzrOWm2pZekJyRdLukxSWMldUl1+kmaKWkicExu3w6Szk3HNUvSUal8iKQHJP0JmN3cQZO0hqSnJG2Ye/0PSRtI2lDSzanPKZIGpTo7SHokje8jkrasMsYbSxqfmz3bpUL/u6V2Zqf3ba0KdQ6V9KSkB4FBzT1GMzMzsyJyMtNOpFmAr5J9mD8NuD8iBgBDgXMldUtVBwKHRMQXgZ8Ab0TENhHRB7hf0gbA6cCwiNgeaABOznX1cir/HTAyIhYAlwLnpVmPCc0I+7PAxRHxeeB1YN9UfhVwfEQMLKt/eIp3ADAAOELSp9O2HYDTImKrKn1dlRKKn0hSfkNELAX+CByUioYBMyPiZeD8dGwDUnxXpDpzgV0jYjvgp8Avck3mx/hbwJiI6AtsC8zI9y2pMzAaGB4R2wAdge+V1dkYOJMsifkSUO0YkXSkpAZJDbxTrZaZmZlZMXiZS9vXRdKM9HwC8AfgEWDP3IxIZ2CT9PzeiHg1PR8GHFBqKCJek/R1sg/LD6fP/GsCE3P93ZIepwLfWMHY50dEKfapQC9JawPrRMSDqfxasiQNYHegj6T90uu1yRKi94DJETG/Sj8HRcS/JPUAbgYOBq4pq3Ml8Ffgt8BhZAkVZGO0VS7/+VhqZ23gakmfBQLolGsrP8ZTgCsldQJuyx1vyZZpHJ5Mr68mm436ba7OjsC4iHgJQNKNwBaVDjQiLgMuA1BP+efozczMrNCczLR9i9K3/h9KMw/7RsS8svIdgbfzRWQfxCkruzciDqzS3+L0uITazq8PWHaGsHOFtkrtdakSUz624yJizDKF0hCWPa5lRMS/0uNbaSnaDpQlMxHxf5JekPRFsuShNEuzBjAwIhaV9Xkh8EBE7JOW2o3Lbf4wlogYL2lXYA/gWknnRkS+72VmiRrhxMTMzMzaHS8za5/GAMeVllNJ2q5KvbHAsaUXktYFJgGDJG2eyrpKqjgLkPMW0KPKtgXA9qmt7YFPV6kHQES8DrwhaXAqOii3eQzwvTTLgaQtcsvnKpLUMS2dI+33daDa3dGuIFtu9ueIWJLKyseob3q6NvCv9HxEI/1vCrwYEZeTzZptX1ZlLtmM1Obp9cHAg2V1HgWGSFo/HcP+1fozMzMza0uczLRPZ5Ete5ql7LbGZ1WpdzawbrowfSYwNC1lGgFcL2kWWXLTu4n+7gD2qXQDALJlXeulpXDfA54s37mCQ4GL0w0A8jMiVwCPA9PScf2epmeH1gLGpGOZQZaAXF6l7u1Adz5aYgZwPNA/3XDgcT66W9yvgV9Kehiodgc1yO70NkPSdLJrbs7Pb4yId8mO9yZJs4GlZNcg5es8D5xBttzv78C0RvozMzMzazMU4dUpZrVQ9psu50XEcnccKyL1VHBUvaNoX2KU/701MzNrCUlTI2K539fzNTNmNZD0Q7KZo4OaqmtmZmZmq4aXmZnVICLOiYhNI+KhesdiZmZmZhknM2ZmZmZmVkheZmbWTvXr2Y+GUQ31DsPMzMysxTwzY2ZmZmZmheRkxszMzMzMCsnJjJmZmZmZFZJ/Z8asnfLvzKw8/j0ZMzOz1lXtd2Y8M2NmZmZmZoXkZMbMzMzMzArJyYyZmZmZmRWSkxkzMzMzMyskJzMFImmJpBmS5ki6SVLXOsQwRNLOuddnSPpXiqv0t04r9DNC0kUr2k4TfSxMj70kzWnGfqMl7bcC/faStKhszNZsaXtmZmZm7ZWTmWJZFBF9I2Jr4D3g6Fp2ktSxFWMYAuxcVnZeiqv093or9tem5N6Lp8vG7L0a9++wEsMzMzMzKxQnM8U1AdhcUjdJV0qaImm6pL3gw5mNmyTdAYyV1F3SVZJmS5olad9Ub3dJEyVNS/W7p/IFks5M5bMl9ZbUiyyBOinNJuxSLbjU/22S7pA0X9Kxkk5OMU6StF6qN07SbyU9kmacdqjQ1qaS7ktx3ydpE0k9UrudUp2PpZg7SdpM0j2SpkqaIKl3qvPpdKxTJJ3V1ABLOiLVnSnp5rKZsGGp7SclfT3V75wb4+mShlZ6Lxrpb7e03+z0nq6Vey9+KukhYH9JX0nvy0xJ96U6Fc8DMzMzs7bMyUwBpW/3vwrMBk4D7o+IAcBQ4FxJ3VLVgcAhEfFF4CfAGxGxTUT0Ae6XtAFwOjAsIrYHGoCTc129nMp/B4yMiAXApXw0EzMh1SslNzMkPZDbf2vgW8AOwM+BdyJiO2Ai8J1cvW4RsTPwfeDKCod8EXBNivs64IKIeAsYB+yR6hwA3BwR7wOXAcdFRD9gJHBJqnM+8Ls0Vv+pPsIfuiUiBkTEtsATwOG5bb2AL6T+L5XUGTgGICK2AQ4Erk7lsOx7AbBZbswuTvVGA8PT/h2B7+X6ezciBgP3AZcD+6a49k/bGzsPzMzMzNqk1lx+ZCtfF0kz0vMJwB+AR4A9JY1M5Z2BTdLzeyPi1fR8GNkHfgAi4rU0o7AV8LAkgDXJEo2SW9LjVOAbjcR1XkT8pkL5AynpeEvSG8AdqXw20CdX7/oU0/g0w7JOWTsDc/1fC/w6Pb8COBW4DTgUOCLNLO0M3JSOCWCt9DgI2DfXzq8aOSaArSWdDawDdAfG5Lb9OSKWAk9JegboDQwGLkzHMlfSs8AWqX7+vYC0zKz0QtK2wPyIeDIVXU2WHP02vb4xPe4EjI+I+amfUpu7U/k8eCJ/QJKOBI4EYO0mjt7MzMxsNedkplgW5T8AAyj7xL5vRMwrK98ReDtfBJT/LLnIPmQfWKW/xelxCS07Vxbnni/NvV5a1l55XE39fHoARMTDyi6m/wLQISLmSPoY8Hr5ODWj7bzRwN4RMVPSCLLrhRqLWVT3diPbaGLf/P6V3sdS+XLnQbmIuIxs5gr1lH+m3szMzArNy8yKbwxwXEpqkLRdlXpjgWNLLyStC0wCBknaPJV1lbRFlf1L3gJ6rHDUyxqe+h9MthTujbLtj/DRrNJBwEO5bdeQzexcBRARbwLzJe2f2lSa9QB4uKydpvQAnk/X5ZTX31/SGpI2Az4DzAPGl+qlcdwklddiLtCr9F4ABwMPVqg3EfiCpE+nftZL5bWeB2ZmZmZthpOZ4jsL6ATMUnZ74WoXtp8NrJsusp8JDI2Il4ARwPWSZpElN72b6O8OYB8tewOA/DUzM5TdKKA5XpP0CNn1OIdX2H48cGiK8WDghNy264B1SUvVkoOAw9NxPgaULoY/AThG0hSWX2S1paTncn/7k11n9ChwL1mykTePLNn4G3B0RLxLdm1OB0mzyZaFjYiIxdQg7X8o2fK42WSzV5dWqPcS2TKxW9LxlZaf1XoemJmZmbUZivBKE6sfSePIbi7Q0ML99wP2ioiDWzWwdkA9FRxV7yjaphjlf1fNzMxak6SpEdG/vNzXzFhhSbqQ7K5uX6t3LGZmZma26jmZsbqKiCErsO9xrRiKmZmZmRWMr5kxMzMzM7NC8syMWTvVr2c/Gka16FIlMzMzs9WCZ2bMzMzMzKyQnMyYmZmZmVkhOZkxMzMzM7NC8u/MmLVT/p2Z1uHflDEzM1v5qv3OjGdmzMzMzMyskJzMmJmZmZlZITmZMTMzMzOzQnIyY2ZmZmZmheRkxppF0hJJMyTNkXSHpHVase2FTfRZ+uvVWn1W6GuIpDckTZf0hKRRK6GPiseZ276OpO/nXveU9JfWjsPMzMys6JzMWHMtioi+EbE18CpwTK07Suq4gn2W/hbU0JcktfT8nhAR2wH9gW9L6tfCdlpqHeDDZCYi/h0R+63iGMzMzMxWe05mbEVMBD4BIGmcpP7p+QaSFqTnIyTdJOkOYKyk7pLukzRN0mxJezW302ptSOqVZlMuAaYBu0iaK+mKNJN0naRhkh6W9JSkHRrrJyLeBqYCm0nqK2mSpFmSbpW0bu64fyvpkdTHDqn8DEkjczHPKZ9RamQszkl9zpB0bjquOWmfzpKuSvWnSxqaG+dbJN2Tju3XzR1XMzMzs6JxMmMtIqkDsBtwew3VBwKHRMQXgXeBfSJie2Ao8D+S1MT+XXJLzG5too0tgWvSzMqzwObA+UAfoDfwLWAwMBL4cRPHuD6wE/AYcA3wg4joA8wG8svPukXEzmSzKVc2PRwfqnYcPwSeTrNQp5TtcwxARGwDHAhcLalz2tYXGA5sAwyX9KlmxGJmZmZWOC1d9mPtVxdJM4BeZLMW99awz70R8Wp6LuAXknYFlpLN7Hwc+E8j+y+KiL6lF5I6VWkD4NmImJTbd35EzE77PQbcFxEhaXY6hkp2kTQ9tX0O8BywTkQ8mLZfDdyUq389QESMl/SxZlxHVG0sGjMYuDD1N1fSs8AWadt9EfFGOtbHgU2B/1umQ+lI4EgA1q4xSjMzM7PVlJMZa65FEdFX0trAnWQzBRcAH/DRTF/nsn3ezj0/CNgQ6BcR76flaOX1m9JYG2+X1V2ce74093op1c//CRHx9dKLdKyNKf8J+GDZ8YDKx9iSsWhsFit/rEuocHwRcRlwGYB6yj9db2ZmZoXmZWbWImkG4HhgZJopWQCULpRv7GL1tYEX04f3oWSzB83VGm3ULB3ra5J2SUUHAw/mqgwHkDQYeCPVXwBsn8q3Bz5doelqx/EW0KNKOOPJkiAkbQFsAsxr2ZGZmZmZFZtnZqzFImK6pJnAAcBvgD9LOhi4v5HdrgPukNQAzADmtqDr1mijuQ4BLpXUFXgGODS37TVJjwAfAw5LZTcD30lL8qYAT1Zos+JxRMQr6SYFc4C/ARfn9rkkxTGbbPZnREQsbvqyIzMzM7O2RxFeaWLWUpLGASMjoqHesTSXeio4qt5RFF+M8r+hZmZmK5ukqRHRv7zcy8zMzMzMzKyQvMzMbAVExJB6x2BmZmbWXnlmxszMzMzMCsnJjJmZmZmZFZKXmZm1U/169qNhVOHuW2BmZmb2Ic/MmJmZmZlZITmZMTMzMzOzQnIyY2ZmZmZmheQfzTRrp/yjmc3nH8g0MzOrD/9oppmZmZmZtSlOZszMzMzMrJCczJiZmZmZWSE5mTEzMzMzs0JyMmMVSVpY9nqEpItWUd8LJG3QjPpVYys/jma0ebekddLf93PlQyTd2ZI2m9n/uZIek3RuC/dv0XGbmZmZFUnHegdgtjqKiK8BSOoFfB+4ZBWHcBSwYUQsXsX9mpmZmRWGZ2as2SRtKuk+SbPS4yapfLSk/XL1FqbHjSWNlzRD0hxJu6Ty3SVNlDRN0k2Suue6OS6Vz5bUO9VfT9Jtqd9JkvpUiO3Tqc0pks6qEv+pko5Pz8+TdH96vpukP6bnpdmhc4DNUuylWZLukv4iaa6k6ySpQh/jJP1K0mRJT+aOubOkq9JxTZc0tMK+twPdgEclDa82run5KelYZ0k6s9LxmpmZmbVVTmasmi7pA/wMSTOAn+W2XQRcExF9gOuAC5po61vAmIjoC2wLzEiJwunAsIjYHmgATs7t83Iq/x0wMpWdCUxP/f4YuKZCX+cDv4uIAcB/qsQzHtglPe9Plpx0AgYDE8rq/hB4OiL6RsQpqWw74ERgK+AzwKAq/XSMiB1S3VGp7BiAiNgGOBC4WlLn/E4RsSewKPV5Y5W2kbQ78FlgB6Av0E/SrtXqm5mZmbU1TmasmtKH6b4pCflpbttA4E/p+bVkSUBjpgCHSjoD2CYi3gJ2IksGHk7J0iHAprl9bkmPU4Fe6fng1B8RcT+wvqS1y/oaBFyfi62SqWQf/HsAi4GJZEnNLiyfzFQyOSKei4ilwIxcfOWaOoa5wLPAFjX0Wcnu6W86MA3oTZbcVCXpSEkNkhp4p4W9mpmZma0mfM2MtYbSz6J/QEqQ09KrNQEiYnyaMdgDuDYt13oNuDciDqzSZulakSV8dJ4ut5wr13dTZR9tjHhf0gLgUOARYBYwFNgMeKKxfctiK4+vWr2mjqEpFcc1tfXLiPh9rQ1FxGXAZQDqKf+cvZmZmRWaZ2asJR4BDkjPDwIeSs8XAP3S872ATpBdYwO8GBGXA38AtgcmAYMkbZ7qdJXU1AzF+NQfkoaQLUV7s6zOw2WxNdbWyPQ4ATgamBER5R/w3wJ6NBFXc+SPYQtgE2BeE/ssoMK4AmOAw0rXGkn6hKSNWjFWMzMzs9WakxlriePJlo3NAg4GTkjllwNfkDQZ2BF4O5UPIbtOZjqwL3B+RLwEjACuT+1MIlsm1ZgzgP6p/jlkS9PKnQAcI2kKUL4ELW8CsDEwMSJeAN6lwhKziHiFbCncnJbeJrnMJUAHSbOBG4ERNdyxrOK4RsRYsuV+E1N7f6F1Ey8zMzOz1ZqW/yLazNoD9VRwVL2jKJYY5X8vzczM6kHS1IjoX17umRkzMzMzMyskJzNmZmZmZlZITmbMzMzMzKyQfGtms3aqX89+NIxqqHcYZmZmZi3mmRkzMzMzMyskJzNmZmZmZlZITmbMzMzMzKyQ/DszZu2Uf2dmef4dGTMzs9WTf2fGzMzMzMzaFCczZmZmZmZWSE5mzMzMzMyskJzMmJmZmZlZITWZzEhaImmGpDmSbpLUdVUEVhbDEEk7r+p+c/2fIWlkE3X2lrRV7vXPJA1bBbH1lPSX9LyvpK/ltjUZdyv0P0LSRWVl4yT1T8/vlrROE218WL+ROmtIuiCdh7MlTZH06Ubqt9qxS1pYpbz038ZjkmZKOlnSGmlbf0kXNNFuL0lzWiNGMzMzs/aoYw11FkVEXwBJ1wFHA//b1E6SOkbEBysW3oeGAAuBR1qpvZVhb+BO4HGAiPjpqug0Iv4N7Jde9gX6A3evir5rERFfa7pWTYYDPYE+EbFU0ieBt1up7ZbK/7exEfAnYG1gVEQ0AA11jM3MzMyszWvuMrMJwOaSukm6Mn07Pl3SXvDht/Q3SboDGCupu6Sr0jfpsyTtm+rtLmmipGmpfvdUvkDSmal8tqTeknqRJVAnpW/Bd8kHlL6Bv1bS/ZKeknREKpekc3Pf5A9P5UMkjZd0q6THJV2a+zZ9Ya7d/SSNLh8ASUek454p6WZJXdOs0Z7AuSnGzSSNlrRf2me3NE6z07itVe14K/R3t6Q+6fl0ST9Nz8+S9N3St/uS1gR+BgxPMQxPTWyVZj6ekXR8pTdV0kJJP0/HNEnSx1P5ppLuS+/dfZI2aeL8qNT2AkkbpOc/kTRX0r2Sri+bOdlf0mRJT5a/x8nGwPMRsRQgIp6LiNdSu19JYzhT0n25fSoee5pBmZP+TmyqvBYR8SJwJHBsOveGSLoztVvxHC0bp865/1amSxqaykdIuk3SHZLmSzo2xTk9vVfrpXrLnZfNid/MzMysiGpOZiR1BL4KzAZOA+6PiAHAULIP8d1S1YHAIRHxReAnwBsRsU1E9AHuTx9sTweGRcT2ZN9en5zr6uVU/jtgZEQsAC4FzouIvhExoUJ4fYA9Ut8/ldQT+AbZTMW2wLAU48ap/g7A/wO2ATZLdWt1S0QMiIhtgSeAwyPiEeB24JQU49O5cesMjAaGR8Q2ZLNh36t2vBX6Gw/sIuljwAfAoFQ+mCy5BCAi3gN+CtyYYrgxbeoNfDkd8yhJnSr00Q2YlI5pPFD6sH0RcE16764Dqi2bKiVQMyTNIJsdWoayZWT7AtuRjXd5nY4RsQNwIjCqQh9/Bv479fE/krZL7W4IXA7sm+LfP7fPcscuqR9wKLAjsBNwhKTtqpVXOd6KIuIZsv+mNqqwudI5mndMamMb4EDg6nTuAGwNfCsdx8+BdyJiO2Ai8J1UZ7nzsjmxm5mZmRVRLclMl/QBtQH4J/AHYHfgh6l8HNAZKH1rf29EvJqeDwMuLjWUvknfCdgKeDjtfwiwaa6/W9LjVKBXjcfx14hYFBEvAw+QfegbDFwfEUsi4gXgQWBAqj85Ip6JiCXA9alurbaWNEHSbOAg4PNN1N8SmB8RT6bXVwO75rY3dbwTUv3BwF1A9/Ste6+ImFdDvHdFxOI0Ni8CH69Q5z2yJXLlcQwkWzoFcC3Vx6mUQPVNy64qLa8azEfv01vAHWXbGx2HiHiObCx/BCwF7pO0G9n5ND4i5qd6r+Z2q3Tsg4FbI+LtiFiY+t2lkfLmUpXySudo3mCyMSYi5gLPAlukbQ9ExFsR8RLwBh+N3Ww+GquazktJR0pqkNTAO80/ODMzM7PVSbOumSmRJLJvwueVle/IstcxCCj/SW2RJTwHVulvcXpcUmN8VOgjqP6hslr98vLOVDYa2DsiZkoaQXY9T2MaiwOaPt4pZLMYzwD3AhuQzZxMbaLd8vYb6+P9iIgm6sDy49YcKzoORMRi4G/A3yS9QHad0r2NxFXp2KvF0VR8TZL0mdTPi8DnyjZXO+dq6T9/HEtzr5fy0ViNpobzMiIuAy4DUE/55+7NzMys0Fp6a+YxwHEpqaGR5ThjgWNLLyStC0wCBknaPJV1lbRFlf1L3gJ6NLJ9r3TNwfpkH+KmkC2XGi6pQ1qKtCswOdXfQdKnlV0rMxx4KJW/IOlzqXyfKn31AJ5Py7UOqiHGuUCv0vECB5PNEtUkLR/7P+CbZGM3gWw5WqXldk2NU3M9AhyQnh/ER+PUEg+RLRPrrOwaqT2as7Ok7UtLs9L704ds9mIi8AWlO5uVriFpxHhg73TedSN7nyc0Ul5rfBuSLYe8KJcY5lU6R8vjOii1tQXZTGctM28l1c5LMzMzszarpcnMWUAnYJayW8ueVaXe2cC66YLqmcDQtFRmBHC9pFlkH9CXu/C9zB3APqpwA4BkMtkSrEnAWekOX7cCs4CZwP3AqRHxn1R/InAOMAeYn+oC/JBsudX9wPNVYvkJ8CjZjMDcXPkNwCnpwuzNSoUR8S7ZtRg3pSVAS8k+9DbHBOCFiHgnPf8klT9oP0B20Xv+BgAr4njg0PQ+HQyc0NKGImIK2XVFM8mWcDWQLZmq1UbAHel8m0V2/dBF6Xw6ErglnWM3NtIGETGNbBZjMtn7eEVETK9W3kRMXdJYPwb8nSx5P7NK3UrnaN4lQId0jtwIjEgzUbWqdl6amZmZtVmq/CVycUg6A1gYEb+psf4QshsLfH0lhmUVSOoeEQvTNT/jgSNTEtGmNfccXVXUU8FR9Y5i9RKjiv3voZmZWVslaWpELHeTqVqvSTFrDZcp+2HRzsDV7SGRMTMzM7OVp/AzM2bWMp6ZWZ5nZszMzFZP1WZmWnrNjJmZmZmZWV05mTEzMzMzs0LyNTNm7VS/nv1oGFXp903NzMzMisEzM2ZmZmZmVkhOZszMzMzMrJCczJiZmZmZWSH51sxm7VR7vzWzb8NsZmZWHL41s5mZmZmZtSlOZszMzMzMrJCczJiZmZmZWSE5mTEzMzMzs0JyMrOakLSPpJDUu96xNEXSAkmzJc2UNFbSf62E9jdoRv1xkualeB6WtOUK9D1OUv/c616S5rS0vWb2PVrSfs2oXzW28uMwMzMza4uczKw+DgQeAg5ojcYkdWiNdhoxNCK2BRqAH6/kvmpxUIrnauDcWnZQxv8NmJmZmRWUP8itBiR1BwYBh5OSGUlflfTnXJ0hku5Iz3eXNFHSNEk3pf1LMxo/lfQQsL+kIyRNSTMWN0vqmuptJmlS2vYzSQtz/ZySymdJOrOG8McDm0vqIOnc3L5HpfaUyuek2ZzhueMZL+lWSY9LurRSYiHp25ImS5oh6fc1JGnjgc2rHUuazXhC0iXANOBTNRxjKZbOkq5KxzFd0tBUPkLSRbl6d6bj65BmW0rHflLavpmkeyRNlTShbDZuV0mPSHqmNEtTbQzLYusi6YZ0rDcCXWo9LjMzM7OicjKzetgbuCcingRelbQ9cC+wk6Ruqc5w4Ma0/Op0YFhEbE82M3Jyrq13I2JwRNwA3BIRA9KMxRNkyRLA+cD5ETEA+HdpR0m7A58FdgD6Av0k7dpE7F8HZqe230htDgCOkPRp4BuprW2BYcC5kjZO++4A/D9gG2CzVPdDkj6XjntQRPQFlgAHNRHPfwOzmziWLYFrImK7iHi2QhvXpeRpBnB3rvwYgIjYhmwm7WpJnRuJpS/wiYjYOu1zVSq/DDguIvoBI4FLcvtsDAwmG9dzUlljY1jyPeCdiOgD/BzoVykgSUdKapDUwDuNRG5mZmZWAB3rHYAB2Qfj36bnNwAHRsQ0SfcA/y3pL8AewKnAF4CtgIclAawJTMy1dWPu+daSzgbWAboDY1L5QLIECuBPwG/S893T3/T0ujtZQjC+QswPSFoCzCJLrq4A+uSu+Vg77TsYuD4ilgAvSHqQLNl5E5gcEc8ASLo+1f1Lro/dyD6UT0nH2gV4sUIskCUgi4AFwHHACVWO5Z/AsxExqUo7kC1Za0hx9QLuTOWDgQsBImKupGeBLRpp5xngM5IuBO4CxqZZtJ2Bm9IxAayV2+e2iFgKPC7p47l+K43hrNx+uwIXpNhmScpv+1BEXEaWTGU/mmlmZmZWYE5m6kzS+sAXyRKPADoAIelUssTkGOBVYEpEvKXsE/C9EXFglSbfzj0fDewdETMljQCGNBUO8MuI+H0NoQ+NiJdzxyGy2YYx+UqSvtZIG+UfpstfC7g6In5UQzwfJiC5eJY7lpScvE3LqEr5Byw7y9kZICJek7Qt8GWy9/GbwInA62mmqZLFFfqr1m85JydmZmbWrniZWf3tR7bkadOI6BURnwLmk30bPw7YHjiCj2ZcJgGDJJWuC+kqqdrsQA/geUmdWHZ51iRg3/Q8f8OBMcBh+uganE9I2qjG4xgDfC/1haQt0hK58cDwdP3IhmQzCJPTPjtI+nS6VmY42Q0Q8u4D9ivFIGk9SZs2I56WHks140njmMZ8E2Ae2WxQX0lrSPoU2dI20pLANSLiZuAnwPYR8SYwX9L+qY5SwtNUv9XGsFJsWwN9VvBYzczMzFZ7Tmbq70Dg1rKym4FvpWVFdwJfTY9ExEvACOD6tJRoElDtds4/AR4lu/5mbq78ROBkSZPJrtF4I7U9lmzZ2URJs8mWfPWo8TiuAB4Hpim7XfDvyWb+biVbDjUTuB84NSL+k/aZSHZdyByyBG6ZcYiIx8mWsI1Nx3pvirdJK3gs1VwCdEjt3QiMiIjFwMMp/tlkS/ampfqfAMala29GA6UZpoOAwyXNBB4D9mqi38bGsOR3QPc0TqeyfLJjZmZm1uYowitT2htldzVbFBEh6QCya3Sa+kDd2jEMAUZGxNdXZb/2EfVUcFS9o6ifGOV/+8zMzIpC0tSIWO439HzNTPvUD7goXVfyOnBYfcMxMzMzM2s+JzPtUERMILvNbz1jGEd2TZCZmZmZWYv4mhkzMzMzMyskz8yYtVP9evajYVRD0xXNzMzMVlOemTEzMzMzs0JyMmNmZmZmZoXkZMbMzMzMzArJyYyZmZmZmRWSkxkzMzMzMyskJzNmZmZmZlZITmbMzMzMzKyQnMyYmZmZmVkhOZkxMzMzM7NCcjJjZmZmZmaF5GTGzMzMzMwKycmMmZmZmZkVkpMZMzMzMzMrJCczZmZmZmZWSIqIesdgZnUg6S1gXr3jaKc2AF6udxDtmMe/vjz+9eOxry+P/4rZNCI2LC/sWI9IzGy1MC8i+tc7iPZIUoPHvn48/vXl8a8fj319efxXDi8zMzMzMzOzQnIyY2ZmZmZmheRkxqz9uqzeAbRjHvv68vjXl8e/fjz29eXxXwl8AwAzMzMzMyskz8yYmZmZmVkhOZkxMzMzM7NCcjJj1kZJUr1jaM8k+d/XOvG5X18+9+vL5399+fxf9TzgZm2MpO4A4Qvi6kLS9gARsbTesbQ3Pvfry+d+ffn8ry+f//XjZMasDZG0J/AHSTdI+pqkTeodU3siaXfgVklb58r8Lekq4HO/vnzu15fP//ry+V9fvpuZWRshaQvgAeCbQH9gI6A7cElEzKtnbO2BpK8CPwNOjogJkjpGxAf1jqs98LlfXz7368vnf335/K8/JzNmbYSkPsBpETE8vd4e+BqwHvC/EfFcPeNry9I3cHcBa0bEMEk9gWPJPlDcB0yOiOfrGWNbJmkb4HSf+6teOvfvBNbyuV8f/re/fvxv/+rBy8zM2o65wOaSvg8QEdOAvwEfAFuAp71XlrRGfX9gLUk3AjcALwOvAkOBYeDxX4nmAp+R9D3wub8q5c79TpJuwOd+PZT+7ff5v4qV/dvv879OnMyYFZikHSQNkjQ4It4DfgwMkHQAQERMJftH9dvptadiW1HZ+L8NfBnYELgnIv43Is4AngS+CB7/1iRpw9JdgyLifeB0YEdJ30xlPvdXorLxfwf4KvBx4G8+91c+SdtL2knSoPRv/2nAQJ//q0bZ+L8NfAXYGJ//deFkxqygJH0ZuB3YA7hW0tFk39DdB3xF0vGp6r+ANSStVZ9I26ay8b9G0knpQ92XgHNy38S9lVX3+LcWSXsDNwEHSuqQiqeSnft7+NxfuSqNf+7c/7XP/ZUrXaPxR7JrZG6StF9E3AP8HZ//K12F8T84JTS74fO/LnzNjFnBpH8o1wR+D9wdEX+WtB1wLnBb+tsC+B/gaWAAsGdEzKxLwG1MlfHvSzb+9wIXRsSiVPd7wOHAiIiYU6eQ2xRJmwJ3A3OAf6THmyLiA0nrA9uSvRfz8bnf6iqM/2yy8V9SVs/n/kqQro+5ATgiIh5OH6yPBr4BrAv0wef/SlNl/I8CDgYWlmZgfP6vWh3rHYCZNU/6x3KxpCeAPpLujojpkk4ELgTej4jfS9oB2AR4KyJerGPIbUqV8Z+RG/+3gYslfYJsicGh/p9Zq3oFOJTsg/SBwE4Akm6OiFeA+yXtCPQC3vS53+rKx38ggKRbIuI9SWsCG5B9S+1zv/WtBZyRPkivQbaUaV2ga0S8jM//la3a+EdEhKSOZMstff6vQp6ZMSuo9I3QnsClwGPpm+l+wJ+Bb6Y107aSNDH++0TELElrRcTiugbaBknqHBHvSupM9u3nFsCkiLhe0mYR8XSdQ2zTmhj/TSLinz73Vx5JH4+IF3Kv7wYOjIg3JH06IubXMbw2r8r4HxARb0r6ZEQ85/N/1fI1M2YFU1qPGxF/AxYCJwBbS+qeEph7gCWNNGEroMbxL11H4P+ZrQTpg7Qi4l1gNNm3o5+TdB0wQdK6dQ2wjWtk/P8ETJK0rs/91pf7t+eF0ut0PcYnyO4mNwK4WVIP3z2r9TUx/mum8b9dUg/gvboF2g55ZsasACRtSfabAQ3A0vz6dEm/BnoA7wL/B/w/YFBELKhDqG2Sx79+Ko19+iAdpcdU769k1wvs7WsEWo/Hv76qjP8aEbE0V+dGYAEwCDjaS5taTwvG/3sRMbsuwbZjTmbMVnOSvgH8guzONP8i+0d1dES8maszlOyDxBbAxRHxeD1ibYs8/vXT2NiXPlAou5vW5sAEYFhEzKpfxG2Lx7++ahn/VO9OYCtgj4h4om4BtzEe/+JwMmO2GpPUiewWkBekCw73JbvgeTFwbkS8UVa/Y0R8UIdQ2ySPf/20YOw3jIiX6hBqm+Txr6/mjL+k7wCPRMQ/6hNt2+PxLxZfM2O2+vsY8Nn0/FbgTrJbAx8IoOyHu/ZI232tTOvz+NdPU2O/o6SvAfiD9Erh8a+vpsZ/oKShEXGNP0ivFB7/gnAyY7Yai+yXzf8X+IakXdK09kPADGCXdPHhJsC0VN9Tra3I418/NY79psD0+kXZdnn866vG8f8UMK9+UbZdHv9i8TIzs9Vcuv3pd8muyfhjRIxP5Q8AR0XEk/WMr63z+NePx76+PP715fGvL49/cfhHM81Wc+k2qNcBAfxIUm+ydbsbAW80urOtMI9//Xjs68vjX18e//ry+BeHZ2bMCkLZL2sPAo4iuw3w+RHhJR6riMe/fjz29eXxry+Pf315/Fd/TmbMCibdCjXy97m3VcfjXz8e+/ry+NeXx7++PP6rLyczZmZmZmZWSL6bmZmZmZmZFZKTGTMzMzMzKyQnM2ZmZmZmVkhOZszMzMzMrJCczJiZma1Ckhau4v56SfrWquzTzGxVcTJjZmbWRknqCPQCnMyYWZvUsd4BmJmZtUeShgBnAi8AfYFbgNnACUAXYO+IeFrSaLIf6/s88HHg5Ii4U1Jn4HdAf+CDVP6ApBHAHkBnoBvQFficpBnA1cCtwLVpG8CxEfFIiucM4GVga2Aq8O2ICEkDgPPTPouB3YB3gHOAIcBawMUR8fvWHCMzs6Y4mTEzM6ufbYHPAa8CzwBXRMQOkk4AjgNOTPV6AV8ANgMekLQ5cAxARGwjqTcwVtIWqf5AoE9EvJqSlJER8XUASV2BL0XEu5I+C1xPlhABbEeWNP0beBgYJGkycCMwPCKmSPoYsAg4HHgjIgZIWgt4WNLYiJjf6qNkZlaFkxkzM7P6mRIRzwNIehoYm8pnA0Nz9f6cfnn8KUnPAL2BwcCFABExV9KzQCmZuTciXq3SZyfgIkl9gSW5fQAmR8RzKZ4ZZEnUG8DzETEl9fVm2r470EfSfmnftYHPAk5mzGyVcTJjZmZWP4tzz5fmXi9l2f9HR9l+AaiRdt9uZNtJZEvbtiW7dvbdKvEsSTGoQv+k8uMiYkwjfZmZrVS+AYCZmdnqb39Ja0jaDPgMMA8YDxwEkJaXbZLKy70F9Mi9XptspmUpcDDQoYm+5wI903UzSOqRbiwwBviepE6lGCR1a6QdM7NW55kZMzOz1d884EGyGwAcna53uQS4VNJsshsAjIiIxdJyEzazgA8kzQRGA5cAN0vaH3iAxmdxiIj3JA0HLpTUhex6mWHAFWTL0KYp6/QlYO9WOFYzs5opotLMsZmZma0O0t3M7oyIv9Q7FjOz1Y2XmZmZmZmZWSF5ZsbMzMzMzArJMzNmZmZmZlZITmbMzMzMzKyQnMyYmZmZmVkhOZkxMzMzM7NCcjJjZmZmZmaF5GTGzMzMzMwK6f8DXx5OMcQk88UAAAAASUVORK5CYII=\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "best_model, importances = ML.perform_xgb(splits, 'Xar_train', 'yar_train', 'Xar_test', 'yar_test', save_df)" ] }, { "cell_type": "markdown", "id": "82c2e804-0a59-4aa3-8528-cf657b22734b", "metadata": {}, "source": [ "### Vulnerability" ] }, { "cell_type": "code", "execution_count": 31, "id": "bba70173-348a-4f61-bd99-095181a1e5ea", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Best Hyperparameters: {'learning_rate': 0.01, 'max_depth': 3, 'n_estimators': 100}\n", "Best Score: 0.003267869508382093\n", "MSE: 0.00015673538354503029\n", "RMSE: 0.012519400286955853\n", "MAE: 0.0017343333375409498\n" ] }, { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "best_model, importances = ML.perform_xgb(splits, 'Xvr_train', 'yvr_train', 'Xvr_test', 'yvr_test', save_df)" ] }, { "cell_type": "markdown", "id": "7dac38c6-0d78-4ad7-a95d-9935e5ad9a8c", "metadata": {}, "source": [ "### Resilience" ] }, { "cell_type": "code", "execution_count": 32, "id": "d6832861-4ee8-4346-87a1-8586b5275264", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Best Hyperparameters: {'learning_rate': 0.01, 'max_depth': 3, 'n_estimators': 500}\n", "Best Score: 0.05587976298047452\n", "MSE: 0.0005174064539978639\n", "RMSE: 0.02274657015899021\n", "MAE: 0.005098730343540287\n" ] }, { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "best_model, importances = ML.perform_xgb(splits, 'Xrr_train', 'yrr_train', 'Xrr_test', 'yrr_test', save_df)" ] }, { "cell_type": "markdown", "id": "c1023340-d575-4c55-b202-9b1d66a58158", "metadata": {}, "source": [ "## Bayesian Network" ] }, { "cell_type": "markdown", "id": "df612398-90ff-44c9-b51f-aba6caaa1758", "metadata": { "tags": [] }, "source": [ "### Adaptability" ] }, { "cell_type": "code", "execution_count": 33, "id": "5a138d8c-0683-4259-9919-1f4b70c6cb78", "metadata": { "tags": [] }, "outputs": [], "source": [ "inputcd = save_df.drop([\"Y_Class\", \"YA_Class\", \"YV_Class\", \"YR_Value\", \"YV_Value\", \"FIPSstate\", \"uniqueID\"], axis=1)\n", "inputcd.rename(columns={\"YR_Value\": \"Score\"}, inplace=True)\n", "inputcd.to_excel(\"bnlearn/Input_Data.xlsx\", index=False)" ] }, { "cell_type": "markdown", "id": "257344a8-024f-416f-9843-339e6987c45d", "metadata": {}, "source": [ "Using CyberGIS-Compute HPC" ] }, { "cell_type": "code", "execution_count": 34, "id": "84cdb9fe-c908-477b-adf2-8617a677a0bc", "metadata": {}, "outputs": [], "source": [ "from cybergis_compute_client import CyberGISCompute" ] }, { "cell_type": "code", "execution_count": 35, "id": "7388d633-51e3-4251-b25d-b8b020fad95d", "metadata": {}, "outputs": [], "source": [ "cybergis = CyberGISCompute(url='cgjobsup.cigi.illinois.edu', isJupyter=True, protocol='HTTPS', port=443, suffix='v2')" ] }, { "cell_type": "markdown", "id": "50aa4472-1544-46f5-b631-e476ba88ff55", "metadata": {}, "source": [ "
    \n", "
  1. From the \"Job Template” dropdown, select your model “Customized_Resilience_Inference_Measurement_Framework”\n", "
  2. Configure your parameters and input file\n", "
  3. Submit job\n", "
  4. After job is finished, download the results from \"/\" \n", "
" ] }, { "cell_type": "code", "execution_count": 36, "id": "0982c363-ab0d-4de9-89f2-b830fcb7142f", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "📃 Found \"cybergis_compute_user.json! NOTE: if you want to login as another user, please remove this file\n", "🎯 Logged in as rohan_debayan@cybergisx.cigi.illinois.edu\n" ] }, { "data": { "application/vnd.jupyter.widget-view+json": { "model_id": "81637766941f44919bf62fdb4e4c858f", "version_major": 2, "version_minor": 0 }, "text/plain": [ "Tab(children=(Output(), Output(), Output(), Output(), Output()), _titles={'0': 'Job Configuration', '1': 'Your…" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "cybergis.show_ui()" ] }, { "cell_type": "markdown", "id": "9866b647-c888-4176-9a4d-7c44dd36af90", "metadata": {}, "source": [ "For specific use cases please run the code through the respective HPC. It will be a time intensive process depending on the choice of parameters. The results will be downloadable as comma seperated values files. At folder to download select \"/\".
In our analysis, for incorporating all the disasters in all the counties, the resultant directed arcs for adaptability are: " ] }, { "cell_type": "markdown", "id": "50723170-816e-46bd-a2b9-c517595729de", "metadata": {}, "source": [ "
\n", " \"Image\"\n", "
" ] }, { "cell_type": "markdown", "id": "fe476858-44e6-4e7e-901e-0cfac141a934", "metadata": { "tags": [] }, "source": [ "### Vulnerability" ] }, { "cell_type": "code", "execution_count": 20, "id": "365658d0-e1fa-4d54-9dfa-58b929acebae", "metadata": { "tags": [] }, "outputs": [], "source": [ "inputcd = save_df.drop([\"Y_Class\", \"YA_Class\", \"YV_Class\", \"YR_Value\", \"YA_Value\", \"FIPSstate\", \"uniqueID\"], axis=1)\n", "inputcd.rename(columns={\"YA_Value\": \"Score\"}, inplace=True)\n", "inputcd.to_excel(\"bnlearn/Input_Data.xlsx\", index=False)" ] }, { "cell_type": "markdown", "id": "7be9921e-fff3-4278-b8c7-979d2016e6ed", "metadata": {}, "source": [ "Using CyberGIS-Compute HPC" ] }, { "cell_type": "code", "execution_count": 4, "id": "abdcd486-7e1c-48b9-9195-10fc97953644", "metadata": {}, "outputs": [], "source": [ "from cybergis_compute_client import CyberGISCompute" ] }, { "cell_type": "code", "execution_count": 5, "id": "711d9cd7-47cd-4a79-94e7-3924bd99dd81", "metadata": {}, "outputs": [], "source": [ "cybergis = CyberGISCompute(url='cgjobsup.cigi.illinois.edu', isJupyter=True, protocol='HTTPS', port=443, suffix='v2')" ] }, { "cell_type": "markdown", "id": "cce2f772-808a-4520-ab1c-e0e2110637ea", "metadata": {}, "source": [ "
    \n", "
  1. From the \"Job Template” dropdown, select your model “Customized_Resilience_Inference_Measurement_Framework”\n", "
  2. Configure your parameters and input file\n", "
  3. Submit job\n", "
" ] }, { "cell_type": "code", "execution_count": 7, "id": "b73ce638-fbf4-4eda-ac68-f87e8755cb82", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "🎯 Logged in as rohan_debayan@cybergisx.cigi.illinois.edu\n" ] }, { "data": { "application/vnd.jupyter.widget-view+json": { "model_id": "922491f5d97f452aa13bc8730d8172ff", "version_major": 2, "version_minor": 0 }, "text/plain": [ "Tab(children=(Output(), Output(), Output(), Output(), Output()), _titles={'0': 'Job Configuration', '1': 'Your…" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "cybergis.show_ui()" ] }, { "cell_type": "markdown", "id": "fcbd7a79-c22e-4315-81ab-ad9c3740344b", "metadata": {}, "source": [ "For specific use cases please run the code through the respective HPC. It will be a time intensive process depending on the choice of parameters. The results will be downloadable as comma seperated values files.
In our analysis, for incorporating all the disasters in all the counties, the resultant directed arcs for vulnerability are:" ] }, { "cell_type": "markdown", "id": "0a61f661-e798-45cc-bba6-e502761a4585", "metadata": {}, "source": [ "
\n", " \"Image\"/\n", "
" ] }, { "cell_type": "markdown", "id": "387e5108-e16d-43fe-b729-d58819c8c880", "metadata": { "tags": [] }, "source": [ "### Resilience" ] }, { "cell_type": "code", "execution_count": 20, "id": "4f0a6eb8-b69d-4e23-895c-62d5f19107d7", "metadata": { "tags": [] }, "outputs": [], "source": [ "inputcd = save_df.drop([\"Y_Class\", \"YA_Class\", \"YV_Class\", \"YV_Value\", \"YA_Value\", \"FIPSstate\", \"uniqueID\"], axis=1)\n", "inputcd.rename(columns={\"YA_Value\": \"Score\"}, inplace=True)\n", "inputcd.to_excel(\"bnlearn/Input_Data.xlsx\", index=False)" ] }, { "cell_type": "markdown", "id": "8b877a62-cf81-4085-9e24-02ecebef3333", "metadata": {}, "source": [ "Using CyberGIS-Compute HPC" ] }, { "cell_type": "code", "execution_count": 2, "id": "cf6081dd-859e-45c0-9b84-ec6d3c6767c2", "metadata": {}, "outputs": [], "source": [ "from cybergis_compute_client import CyberGISCompute" ] }, { "cell_type": "code", "execution_count": 3, "id": "87c839d9-8d86-427b-84b4-27dfd38aace4", "metadata": {}, "outputs": [], "source": [ "cybergis = CyberGISCompute(url='cgjobsup.cigi.illinois.edu', isJupyter=True, protocol='HTTPS', port=443, suffix='v2')" ] }, { "cell_type": "markdown", "id": "687645da-f24d-4396-9143-f7e36c67adb0", "metadata": {}, "source": [ "
    \n", "
  1. From the \"Job Template” dropdown, select your model “Customized_Resilience_Inference_Measurement_Framework”\n", "
  2. Configure your parameters and input file\n", "
  3. Submit job\n", "
" ] }, { "cell_type": "code", "execution_count": 4, "id": "4221526a-5789-4fe7-a849-34acae4535f4", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "📃 Found \"cybergis_compute_user.json! NOTE: if you want to login as another user, please remove this file\n", "🎯 Logged in as rohan_debayan@cybergisx.cigi.illinois.edu\n" ] }, { "data": { "application/vnd.jupyter.widget-view+json": { "model_id": "bb1697c729814ba3a4e8daa33a4f6b9b", "version_major": 2, "version_minor": 0 }, "text/plain": [ "Tab(children=(Output(), Output(), Output(), Output(), Output()), _titles={'0': 'Job Configuration', '1': 'Your…" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "cybergis.show_ui()" ] }, { "cell_type": "markdown", "id": "62edf383-480c-4325-b169-da5d05c8ebb8", "metadata": {}, "source": [ "For specific use cases please run the code through the respective HPC. It will be a time intensive process depending on the choice of parameters. The results will be downloadable as comma seperated values files.
In our analysis, for incorporating all the disasters in all the counties, the resultant directed arcs for overall resilience are:" ] }, { "cell_type": "markdown", "id": "0ee2d38f-189d-4381-923c-a8593bcd6693", "metadata": {}, "source": [ "
\n", " \"Image\"/\n", "
" ] }, { "cell_type": "markdown", "id": "6a74b676-e251-4d0d-8c90-e18066e0b79f", "metadata": {}, "source": [ "This is the tool module for usage purposes. Please check out our inferences from this result in our paper: \t\n", "https://doi.org/10.48550/arXiv.2404.09463" ] }, { "cell_type": "markdown", "id": "3d745b2c-e9a2-418b-adcb-2db52ec7e8ac", "metadata": {}, "source": [ "---" ] } ], "metadata": { "kernelspec": { "display_name": "Python 3-0.9.0", "language": "python", "name": "python3-0.9.0" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.8.12" }, "toc-autonumbering": true, "toc-showcode": false, "toc-showmarkdowntxt": false, "toc-showtags": false, "widgets": { "application/vnd.jupyter.widget-state+json": { "state": { "006cefdd0bf34696baabf7d893edf0d7": { "model_module": "@jupyter-widgets/controls", "model_module_version": "1.5.0", "model_name": "ButtonStyleModel", "state": {} }, "0081598914c04f6c87de3f03091dd220": { "model_module": "@jupyter-widgets/base", "model_module_version": "1.2.0", "model_name": "LayoutModel", "state": {} }, "008552f9fd1244eebffe0fc93403abc6": { "model_module": "@jupyter-widgets/controls", "model_module_version": "1.5.0", "model_name": "ButtonModel", "state": { "description": "Submit Job", "layout": "IPY_MODEL_3a052bbbda0f4a58905d7c9c4b541550", "style": "IPY_MODEL_26b1b8fbd6834b6e9a369d536c915fe2" } }, "008740cf107748e3b14e6177a909614d": { "model_module": "@jupyter-widgets/controls", "model_module_version": "1.5.0", "model_name": "DropdownModel", "state": { "_options_labels": [ "aces_community", "anvil_community", "expanse_community", "keeling_community" ], "description": "🖥 Computing Resource:", "index": 3, "layout": "IPY_MODEL_5aba9abe33a24e59954486c044a2b8c9", "style": "IPY_MODEL_ada9c384dc7c48b88ce63deaa47d6782" } }, "009edc1fd72745548b029adac12efafd": { "model_module": "@jupyter-widgets/base", "model_module_version": "1.2.0", "model_name": "LayoutModel", "state": {} }, "00acfe27f59245b295b1616214d8d57c": { "model_module": "@jupyter-widgets/controls", "model_module_version": "1.5.0", "model_name": "ButtonModel", "state": { "description": "Cancel", "layout": "IPY_MODEL_b8fe0a38378a423f8c26601e1c5daa99", "style": "IPY_MODEL_d0ccb3812ca14436a0bdaaecbdebf67c" } }, "00e10654c8ba4bb09df92a9613b1cb14": { "model_module": "@jupyter-widgets/base", "model_module_version": "1.2.0", "model_name": "LayoutModel", "state": {} }, "0110b702a9024db4a1260ccf89ce268b": { "model_module": "@jupyter-widgets/base", "model_module_version": "1.2.0", "model_name": "LayoutModel", "state": {} }, "011e5403c57b41e8a4a2b49f21fbb1ef": { "model_module": "@jupyter-widgets/output", "model_module_version": "1.0.0", "model_name": "OutputModel", "state": { "layout": "IPY_MODEL_9544aaef779f47489cf5b9867e1ea290", "outputs": [ { "data": { "text/markdown": "# ⏳ Waiting for Job to Finish...", "text/plain": "" }, "metadata": {}, "output_type": "display_data" }, { "data": { "application/vnd.jupyter.widget-view+json": { "model_id": "5c672a3e3acb4feca4d21561f3f125da", "version_major": 2, "version_minor": 0 }, "text/plain": "Button(description='Download', disabled=True, style=ButtonStyle())" }, "metadata": {}, "output_type": "display_data" } ] } }, "0147e9973b6448b2b49249bda406ff19": { "model_module": "@jupyter-widgets/base", "model_module_version": "1.2.0", "model_name": "LayoutModel", "state": {} }, "019ab039867b45269bcf9300779d32f2": { "model_module": "@jupyter-widgets/base", "model_module_version": "1.2.0", "model_name": "LayoutModel", "state": {} }, "01a9348fbb6f4f1cb11a742c4d67f1f1": { "model_module": "@jupyter-widgets/controls", "model_module_version": "1.5.0", "model_name": "DescriptionStyleModel", "state": { "description_width": "auto" } }, "01c55f4cad4d4b288e0364bb388cdf1f": { "model_module": "@jupyter-widgets/base", "model_module_version": "1.2.0", "model_name": "LayoutModel", "state": {} }, "01e556f3d42e422e880a33b516991e5e": { "model_module": "@jupyter-widgets/controls", "model_module_version": "1.5.0", "model_name": "ButtonStyleModel", "state": {} }, "02614b78b15b43449e0e658bc8f1e1af": { "model_module": "@jupyter-widgets/base", "model_module_version": "1.2.0", "model_name": "LayoutModel", "state": {} }, "0278549a970a4ea8abdb5cbbf198a0eb": { "model_module": "@jupyter-widgets/base", "model_module_version": "1.2.0", "model_name": "LayoutModel", "state": {} }, "02b922de346b47cb814730bf3af1d85d": { "model_module": "@jupyter-widgets/base", "model_module_version": "1.2.0", "model_name": "LayoutModel", "state": {} }, "03486a0d6d5b48859c4eaaa6f8c6ae01": { "model_module": "@jupyter-widgets/controls", "model_module_version": "1.5.0", "model_name": "LabelModel", "state": { "layout": "IPY_MODEL_ca2cdffa3fd14896998721ebf8eb23bc", "style": "IPY_MODEL_c3910b1934044f33bf499fb6ae5087e1", "value": "All configs are optional. 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' and ' _ '. Other characters will be removed from your input.", "text/plain": "" }, "metadata": {}, "output_type": "display_data" }, { "data": { "text/markdown": "
**Showing folders 1 to 10 of 13 for rohan_debayan**", "text/plain": "" }, "metadata": {}, "output_type": "display_data" }, { "data": { "application/vnd.jupyter.widget-view+json": { "model_id": "d1526716a0094395882a11d7c2662f72", "version_major": 2, "version_minor": 0 }, "text/plain": "HBox(children=(Button(description='Previous Page', style=ButtonStyle()), Button(description='Next Page', style…" }, "metadata": {}, "output_type": "display_data" }, { "data": { "text/markdown": "| id | name | hpc | userId | isWritable | createdAt | updatedAt | deletedAt | \n| --- | --- | --- | --- | --- | --- | --- | --- | \n| 1694387466YBHG8 | None | keeling_community | rohan_debayan@cybergisx.cigi.illinois.edu | False | 2023-09-10T23:11:59.116Z | None | None | ", "text/plain": "" }, "metadata": {}, "output_type": "display_data" }, { "data": { "application/vnd.jupyter.widget-view+json": { "model_id": "476a323606b34ba58ece2d4482df1986", "version_major": 2, "version_minor": 0 }, "text/plain": 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"IPY_MODEL_f9305dc908c541bba935aca688946587", "style": "IPY_MODEL_b3301495687143d7972fdf25da7c78b6" } }, "1b41a2f84d554bb4999c846a02058132": { "model_module": "@jupyter-widgets/output", "model_module_version": "1.0.0", "model_name": "OutputModel", "state": { "layout": "IPY_MODEL_33a9a86ec1d64b23a0595447b2e15c5a", "outputs": [ { "name": "stdout", "output_type": "stream", "text": "\u001b[H\u001b[2J" }, { "ename": "gaierror", "evalue": "[Errno -5] No address associated with hostname", "output_type": "error", "traceback": [ "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", "\u001b[0;31mgaierror\u001b[0m Traceback (most recent call last)", "File \u001b[0;32m/cvmfs/cybergis.illinois.edu/software/conda/cybergisx/python3-0.9.0/lib/python3.8/site-packages/cybergis_compute_client/UI.py:534\u001b[0m, in \u001b[0;36mUI.renderResultEvents\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m 532\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m\n\u001b[1;32m 533\u001b[0m \u001b[38;5;28;01mwith\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mresultEvents[\u001b[38;5;124m'\u001b[39m\u001b[38;5;124moutput\u001b[39m\u001b[38;5;124m'\u001b[39m]:\n\u001b[0;32m--> 534\u001b[0m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mcompute\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mjob\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mevents\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 535\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m\n", "File \u001b[0;32m/cvmfs/cybergis.illinois.edu/software/conda/cybergisx/python3-0.9.0/lib/python3.8/site-packages/cybergis_compute_client/Job.py:145\u001b[0m, in \u001b[0;36mJob.events\u001b[0;34m(self, raw, basic, refreshRateInSeconds)\u001b[0m\n\u001b[1;32m 143\u001b[0m \u001b[38;5;28;01mwhile\u001b[39;00m (\u001b[38;5;129;01mnot\u001b[39;00m isEnd):\n\u001b[1;32m 144\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_clear()\n\u001b[0;32m--> 145\u001b[0m status \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mstatus\u001b[49m\u001b[43m(\u001b[49m\u001b[43mraw\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;28;43;01mTrue\u001b[39;49;00m\u001b[43m)\u001b[49m\n\u001b[1;32m 146\u001b[0m out \u001b[38;5;241m=\u001b[39m status[\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mevents\u001b[39m\u001b[38;5;124m'\u001b[39m]\n\u001b[1;32m 147\u001b[0m headers \u001b[38;5;241m=\u001b[39m [\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mtypes\u001b[39m\u001b[38;5;124m'\u001b[39m, \u001b[38;5;124m'\u001b[39m\u001b[38;5;124mmessage\u001b[39m\u001b[38;5;124m'\u001b[39m, \u001b[38;5;124m'\u001b[39m\u001b[38;5;124mtime\u001b[39m\u001b[38;5;124m'\u001b[39m]\n", "File \u001b[0;32m/cvmfs/cybergis.illinois.edu/software/conda/cybergisx/python3-0.9.0/lib/python3.8/site-packages/cybergis_compute_client/Job.py:244\u001b[0m, in \u001b[0;36mJob.status\u001b[0;34m(self, raw)\u001b[0m\n\u001b[1;32m 241\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mid \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m:\n\u001b[1;32m 242\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mException\u001b[39;00m(\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mmissing job ID, submit/register job first\u001b[39m\u001b[38;5;124m'\u001b[39m)\n\u001b[0;32m--> 244\u001b[0m job \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mclient\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mrequest\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43mGET\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43m/job/\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[43m \u001b[49m\u001b[38;5;241;43m+\u001b[39;49m\u001b[43m \u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mid\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43m{\u001b[49m\n\u001b[1;32m 245\u001b[0m \u001b[43m \u001b[49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43mjupyterhubApiToken\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[43m:\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mjupyterhubApiToken\u001b[49m\n\u001b[1;32m 246\u001b[0m \u001b[43m\u001b[49m\u001b[43m}\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 248\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m raw:\n\u001b[1;32m 249\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m job\n", "File \u001b[0;32m/cvmfs/cybergis.illinois.edu/software/conda/cybergisx/python3-0.9.0/lib/python3.8/site-packages/cybergis_compute_client/Client.py:53\u001b[0m, in \u001b[0;36mClient.request\u001b[0;34m(self, method, uri, body)\u001b[0m\n\u001b[1;32m 51\u001b[0m connection \u001b[38;5;241m=\u001b[39m client\u001b[38;5;241m.\u001b[39mHTTPSConnection(\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39murl)\n\u001b[1;32m 52\u001b[0m headers \u001b[38;5;241m=\u001b[39m {\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mContent-type\u001b[39m\u001b[38;5;124m'\u001b[39m: \u001b[38;5;124m'\u001b[39m\u001b[38;5;124mapplication/json\u001b[39m\u001b[38;5;124m'\u001b[39m}\n\u001b[0;32m---> 53\u001b[0m \u001b[43mconnection\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mrequest\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m 54\u001b[0m \u001b[43m \u001b[49m\u001b[43mmethod\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43m/\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[43m \u001b[49m\u001b[38;5;241;43m+\u001b[39;49m\u001b[43m \u001b[49m\u001b[43mpath\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mjoin\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43msuffix\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mstrip\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43m/\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43muri\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mstrip\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43m/\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[43m)\u001b[49m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 55\u001b[0m \u001b[43m \u001b[49m\u001b[43mjson\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mdumps\u001b[49m\u001b[43m(\u001b[49m\u001b[43mbody\u001b[49m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mheaders\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 56\u001b[0m response \u001b[38;5;241m=\u001b[39m connection\u001b[38;5;241m.\u001b[39mgetresponse()\n\u001b[1;32m 57\u001b[0m out \u001b[38;5;241m=\u001b[39m response\u001b[38;5;241m.\u001b[39mread()\u001b[38;5;241m.\u001b[39mdecode()\n", "File \u001b[0;32m/cvmfs/cybergis.illinois.edu/software/conda/cybergisx/python3-0.9.0/lib/python3.8/http/client.py:1256\u001b[0m, in \u001b[0;36mHTTPConnection.request\u001b[0;34m(self, method, url, body, headers, encode_chunked)\u001b[0m\n\u001b[1;32m 1253\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mrequest\u001b[39m(\u001b[38;5;28mself\u001b[39m, method, url, body\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mNone\u001b[39;00m, headers\u001b[38;5;241m=\u001b[39m{}, \u001b[38;5;241m*\u001b[39m,\n\u001b[1;32m 1254\u001b[0m encode_chunked\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mFalse\u001b[39;00m):\n\u001b[1;32m 1255\u001b[0m \u001b[38;5;124;03m\"\"\"Send a complete request to the server.\"\"\"\u001b[39;00m\n\u001b[0;32m-> 1256\u001b[0m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_send_request\u001b[49m\u001b[43m(\u001b[49m\u001b[43mmethod\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43murl\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mbody\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mheaders\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mencode_chunked\u001b[49m\u001b[43m)\u001b[49m\n", "File \u001b[0;32m/cvmfs/cybergis.illinois.edu/software/conda/cybergisx/python3-0.9.0/lib/python3.8/http/client.py:1302\u001b[0m, in \u001b[0;36mHTTPConnection._send_request\u001b[0;34m(self, method, url, body, headers, encode_chunked)\u001b[0m\n\u001b[1;32m 1298\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28misinstance\u001b[39m(body, \u001b[38;5;28mstr\u001b[39m):\n\u001b[1;32m 1299\u001b[0m \u001b[38;5;66;03m# RFC 2616 Section 3.7.1 says that text default has a\u001b[39;00m\n\u001b[1;32m 1300\u001b[0m \u001b[38;5;66;03m# default charset of iso-8859-1.\u001b[39;00m\n\u001b[1;32m 1301\u001b[0m body \u001b[38;5;241m=\u001b[39m _encode(body, \u001b[38;5;124m'\u001b[39m\u001b[38;5;124mbody\u001b[39m\u001b[38;5;124m'\u001b[39m)\n\u001b[0;32m-> 1302\u001b[0m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mendheaders\u001b[49m\u001b[43m(\u001b[49m\u001b[43mbody\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mencode_chunked\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mencode_chunked\u001b[49m\u001b[43m)\u001b[49m\n", "File \u001b[0;32m/cvmfs/cybergis.illinois.edu/software/conda/cybergisx/python3-0.9.0/lib/python3.8/http/client.py:1251\u001b[0m, in \u001b[0;36mHTTPConnection.endheaders\u001b[0;34m(self, message_body, encode_chunked)\u001b[0m\n\u001b[1;32m 1249\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[1;32m 1250\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m CannotSendHeader()\n\u001b[0;32m-> 1251\u001b[0m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_send_output\u001b[49m\u001b[43m(\u001b[49m\u001b[43mmessage_body\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mencode_chunked\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mencode_chunked\u001b[49m\u001b[43m)\u001b[49m\n", "File \u001b[0;32m/cvmfs/cybergis.illinois.edu/software/conda/cybergisx/python3-0.9.0/lib/python3.8/http/client.py:1011\u001b[0m, in \u001b[0;36mHTTPConnection._send_output\u001b[0;34m(self, message_body, encode_chunked)\u001b[0m\n\u001b[1;32m 1009\u001b[0m msg \u001b[38;5;241m=\u001b[39m \u001b[38;5;124mb\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;130;01m\\r\u001b[39;00m\u001b[38;5;130;01m\\n\u001b[39;00m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;241m.\u001b[39mjoin(\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_buffer)\n\u001b[1;32m 1010\u001b[0m \u001b[38;5;28;01mdel\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_buffer[:]\n\u001b[0;32m-> 1011\u001b[0m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43msend\u001b[49m\u001b[43m(\u001b[49m\u001b[43mmsg\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 1013\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m message_body \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m:\n\u001b[1;32m 1014\u001b[0m \n\u001b[1;32m 1015\u001b[0m \u001b[38;5;66;03m# create a consistent interface to message_body\u001b[39;00m\n\u001b[1;32m 1016\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mhasattr\u001b[39m(message_body, \u001b[38;5;124m'\u001b[39m\u001b[38;5;124mread\u001b[39m\u001b[38;5;124m'\u001b[39m):\n\u001b[1;32m 1017\u001b[0m \u001b[38;5;66;03m# Let file-like take precedence over byte-like. This\u001b[39;00m\n\u001b[1;32m 1018\u001b[0m \u001b[38;5;66;03m# is needed to allow the current position of mmap'ed\u001b[39;00m\n\u001b[1;32m 1019\u001b[0m \u001b[38;5;66;03m# files to be taken into account.\u001b[39;00m\n", "File \u001b[0;32m/cvmfs/cybergis.illinois.edu/software/conda/cybergisx/python3-0.9.0/lib/python3.8/http/client.py:951\u001b[0m, in \u001b[0;36mHTTPConnection.send\u001b[0;34m(self, data)\u001b[0m\n\u001b[1;32m 949\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39msock \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m:\n\u001b[1;32m 950\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mauto_open:\n\u001b[0;32m--> 951\u001b[0m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mconnect\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 952\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[1;32m 953\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m NotConnected()\n", "File \u001b[0;32m/cvmfs/cybergis.illinois.edu/software/conda/cybergisx/python3-0.9.0/lib/python3.8/http/client.py:1418\u001b[0m, in \u001b[0;36mHTTPSConnection.connect\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m 1415\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mconnect\u001b[39m(\u001b[38;5;28mself\u001b[39m):\n\u001b[1;32m 1416\u001b[0m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mConnect to a host on a given (SSL) port.\u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[0;32m-> 1418\u001b[0m \u001b[38;5;28;43msuper\u001b[39;49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mconnect\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 1420\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_tunnel_host:\n\u001b[1;32m 1421\u001b[0m server_hostname \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_tunnel_host\n", "File \u001b[0;32m/cvmfs/cybergis.illinois.edu/software/conda/cybergisx/python3-0.9.0/lib/python3.8/http/client.py:922\u001b[0m, in \u001b[0;36mHTTPConnection.connect\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m 920\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mconnect\u001b[39m(\u001b[38;5;28mself\u001b[39m):\n\u001b[1;32m 921\u001b[0m \u001b[38;5;124;03m\"\"\"Connect to the host and port specified in __init__.\"\"\"\u001b[39;00m\n\u001b[0;32m--> 922\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39msock \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_create_connection\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m 923\u001b[0m \u001b[43m \u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mhost\u001b[49m\u001b[43m,\u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mport\u001b[49m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mtimeout\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43msource_address\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 924\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39msock\u001b[38;5;241m.\u001b[39msetsockopt(socket\u001b[38;5;241m.\u001b[39mIPPROTO_TCP, socket\u001b[38;5;241m.\u001b[39mTCP_NODELAY, \u001b[38;5;241m1\u001b[39m)\n\u001b[1;32m 926\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_tunnel_host:\n", "File \u001b[0;32m/cvmfs/cybergis.illinois.edu/software/conda/cybergisx/python3-0.9.0/lib/python3.8/socket.py:787\u001b[0m, in \u001b[0;36mcreate_connection\u001b[0;34m(address, timeout, source_address)\u001b[0m\n\u001b[1;32m 785\u001b[0m host, port \u001b[38;5;241m=\u001b[39m address\n\u001b[1;32m 786\u001b[0m err \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;01mNone\u001b[39;00m\n\u001b[0;32m--> 787\u001b[0m \u001b[38;5;28;01mfor\u001b[39;00m res \u001b[38;5;129;01min\u001b[39;00m \u001b[43mgetaddrinfo\u001b[49m\u001b[43m(\u001b[49m\u001b[43mhost\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mport\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m0\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mSOCK_STREAM\u001b[49m\u001b[43m)\u001b[49m:\n\u001b[1;32m 788\u001b[0m af, socktype, proto, canonname, sa \u001b[38;5;241m=\u001b[39m res\n\u001b[1;32m 789\u001b[0m sock \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;01mNone\u001b[39;00m\n", "File \u001b[0;32m/cvmfs/cybergis.illinois.edu/software/conda/cybergisx/python3-0.9.0/lib/python3.8/socket.py:918\u001b[0m, in \u001b[0;36mgetaddrinfo\u001b[0;34m(host, port, family, type, proto, flags)\u001b[0m\n\u001b[1;32m 915\u001b[0m \u001b[38;5;66;03m# We override this function since we want to translate the numeric family\u001b[39;00m\n\u001b[1;32m 916\u001b[0m \u001b[38;5;66;03m# and socket type values to enum constants.\u001b[39;00m\n\u001b[1;32m 917\u001b[0m addrlist \u001b[38;5;241m=\u001b[39m []\n\u001b[0;32m--> 918\u001b[0m \u001b[38;5;28;01mfor\u001b[39;00m res \u001b[38;5;129;01min\u001b[39;00m \u001b[43m_socket\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mgetaddrinfo\u001b[49m\u001b[43m(\u001b[49m\u001b[43mhost\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mport\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mfamily\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43mtype\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mproto\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mflags\u001b[49m\u001b[43m)\u001b[49m:\n\u001b[1;32m 919\u001b[0m af, socktype, proto, canonname, sa \u001b[38;5;241m=\u001b[39m res\n\u001b[1;32m 920\u001b[0m addrlist\u001b[38;5;241m.\u001b[39mappend((_intenum_converter(af, AddressFamily),\n\u001b[1;32m 921\u001b[0m _intenum_converter(socktype, SocketKind),\n\u001b[1;32m 922\u001b[0m proto, canonname, sa))\n", "\u001b[0;31mgaierror\u001b[0m: [Errno -5] No address associated with hostname" ] } ] } }, "1bb8f7f7c9824b2e8a9071f2f93b9ac8": { "model_module": "@jupyter-widgets/base", "model_module_version": "1.2.0", "model_name": "LayoutModel", "state": {} }, "1c207e29071b4da996f2632c30e3dcf0": { "model_module": "@jupyter-widgets/base", "model_module_version": "1.2.0", "model_name": "LayoutModel", "state": {} }, "1c3058d905e64ae18f7d67397e60a13b": { "model_module": "@jupyter-widgets/base", "model_module_version": "1.2.0", "model_name": "LayoutModel", 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"67de9d7cb73e401a97680b685d82e5a4": { "model_module": "@jupyter-widgets/base", "model_module_version": "1.2.0", "model_name": "LayoutModel", "state": {} }, "681eae88635d445a9ae05ebd41eb4c4b": { "model_module": "@jupyter-widgets/controls", "model_module_version": "1.5.0", "model_name": "ButtonModel", "state": { "description": "Download Results", "layout": "IPY_MODEL_20f4153d172444c4b72d54a3826d56ce", "style": "IPY_MODEL_36e64dddceef43e9b86e62dea0b3cc48" } }, "68e557dc1399422da5f3503364db975d": { "model_module": "@jupyter-widgets/controls", "model_module_version": "1.5.0", "model_name": "ButtonStyleModel", "state": {} }, "69c3e1ff62bf46ef872fde410cbe43c0": { "model_module": "@jupyter-widgets/output", "model_module_version": "1.0.0", "model_name": "OutputModel", "state": { "layout": "IPY_MODEL_d71dbe11c87649449d4959674d400a71", "outputs": [ { "name": "stdout", "output_type": "stream", "text": "\u001b[H\u001b[2J" }, { "ename": "gaierror", "evalue": "[Errno -5] No address associated with hostname", "output_type": "error", "traceback": [ "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", "\u001b[0;31mgaierror\u001b[0m Traceback (most recent call last)", "File \u001b[0;32m/cvmfs/cybergis.illinois.edu/software/conda/cybergisx/python3-0.9.0/lib/python3.8/site-packages/cybergis_compute_client/UI.py:547\u001b[0m, in \u001b[0;36mUI.renderResultLogs\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m 545\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m\n\u001b[1;32m 546\u001b[0m \u001b[38;5;28;01mwith\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mresultLogs[\u001b[38;5;124m'\u001b[39m\u001b[38;5;124moutput\u001b[39m\u001b[38;5;124m'\u001b[39m]:\n\u001b[0;32m--> 547\u001b[0m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mcompute\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mjob\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mlogs\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 548\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mtab\u001b[38;5;241m.\u001b[39mset_title(\u001b[38;5;241m2\u001b[39m, \u001b[38;5;124m'\u001b[39m\u001b[38;5;124m✅ Download Job Result\u001b[39m\u001b[38;5;124m'\u001b[39m)\n\u001b[1;32m 549\u001b[0m display(Markdown(\u001b[38;5;124m'\u001b[39m\u001b[38;5;124m***\u001b[39m\u001b[38;5;124m'\u001b[39m))\n", "File \u001b[0;32m/cvmfs/cybergis.illinois.edu/software/conda/cybergisx/python3-0.9.0/lib/python3.8/site-packages/cybergis_compute_client/Job.py:198\u001b[0m, in \u001b[0;36mJob.logs\u001b[0;34m(self, raw, liveOutput, refreshRateInSeconds)\u001b[0m\n\u001b[1;32m 196\u001b[0m \u001b[38;5;28;01mwhile\u001b[39;00m (\u001b[38;5;129;01mnot\u001b[39;00m isEnd):\n\u001b[1;32m 197\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_clear()\n\u001b[0;32m--> 198\u001b[0m status \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mstatus\u001b[49m\u001b[43m(\u001b[49m\u001b[43mraw\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;28;43;01mTrue\u001b[39;49;00m\u001b[43m)\u001b[49m\n\u001b[1;32m 199\u001b[0m headers \u001b[38;5;241m=\u001b[39m [\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mmessage\u001b[39m\u001b[38;5;124m'\u001b[39m, \u001b[38;5;124m'\u001b[39m\u001b[38;5;124mtime\u001b[39m\u001b[38;5;124m'\u001b[39m]\n\u001b[1;32m 200\u001b[0m logs \u001b[38;5;241m=\u001b[39m []\n", "File \u001b[0;32m/cvmfs/cybergis.illinois.edu/software/conda/cybergisx/python3-0.9.0/lib/python3.8/site-packages/cybergis_compute_client/Job.py:244\u001b[0m, in \u001b[0;36mJob.status\u001b[0;34m(self, raw)\u001b[0m\n\u001b[1;32m 241\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mid \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m:\n\u001b[1;32m 242\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mException\u001b[39;00m(\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mmissing job ID, submit/register job first\u001b[39m\u001b[38;5;124m'\u001b[39m)\n\u001b[0;32m--> 244\u001b[0m job \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mclient\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mrequest\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43mGET\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43m/job/\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[43m \u001b[49m\u001b[38;5;241;43m+\u001b[39;49m\u001b[43m \u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mid\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43m{\u001b[49m\n\u001b[1;32m 245\u001b[0m \u001b[43m \u001b[49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43mjupyterhubApiToken\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[43m:\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mjupyterhubApiToken\u001b[49m\n\u001b[1;32m 246\u001b[0m \u001b[43m\u001b[49m\u001b[43m}\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 248\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m raw:\n\u001b[1;32m 249\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m job\n", "File \u001b[0;32m/cvmfs/cybergis.illinois.edu/software/conda/cybergisx/python3-0.9.0/lib/python3.8/site-packages/cybergis_compute_client/Client.py:53\u001b[0m, in \u001b[0;36mClient.request\u001b[0;34m(self, method, uri, body)\u001b[0m\n\u001b[1;32m 51\u001b[0m connection \u001b[38;5;241m=\u001b[39m client\u001b[38;5;241m.\u001b[39mHTTPSConnection(\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39murl)\n\u001b[1;32m 52\u001b[0m headers \u001b[38;5;241m=\u001b[39m {\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mContent-type\u001b[39m\u001b[38;5;124m'\u001b[39m: \u001b[38;5;124m'\u001b[39m\u001b[38;5;124mapplication/json\u001b[39m\u001b[38;5;124m'\u001b[39m}\n\u001b[0;32m---> 53\u001b[0m \u001b[43mconnection\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mrequest\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m 54\u001b[0m \u001b[43m \u001b[49m\u001b[43mmethod\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43m/\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[43m \u001b[49m\u001b[38;5;241;43m+\u001b[39;49m\u001b[43m 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complete request to the server.\"\"\"\u001b[39;00m\n\u001b[0;32m-> 1256\u001b[0m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_send_request\u001b[49m\u001b[43m(\u001b[49m\u001b[43mmethod\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43murl\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mbody\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mheaders\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mencode_chunked\u001b[49m\u001b[43m)\u001b[49m\n", "File \u001b[0;32m/cvmfs/cybergis.illinois.edu/software/conda/cybergisx/python3-0.9.0/lib/python3.8/http/client.py:1302\u001b[0m, in \u001b[0;36mHTTPConnection._send_request\u001b[0;34m(self, method, url, body, headers, encode_chunked)\u001b[0m\n\u001b[1;32m 1298\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28misinstance\u001b[39m(body, \u001b[38;5;28mstr\u001b[39m):\n\u001b[1;32m 1299\u001b[0m \u001b[38;5;66;03m# RFC 2616 Section 3.7.1 says that text default has a\u001b[39;00m\n\u001b[1;32m 1300\u001b[0m \u001b[38;5;66;03m# default charset of iso-8859-1.\u001b[39;00m\n\u001b[1;32m 1301\u001b[0m body \u001b[38;5;241m=\u001b[39m _encode(body, \u001b[38;5;124m'\u001b[39m\u001b[38;5;124mbody\u001b[39m\u001b[38;5;124m'\u001b[39m)\n\u001b[0;32m-> 1302\u001b[0m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mendheaders\u001b[49m\u001b[43m(\u001b[49m\u001b[43mbody\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mencode_chunked\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mencode_chunked\u001b[49m\u001b[43m)\u001b[49m\n", "File \u001b[0;32m/cvmfs/cybergis.illinois.edu/software/conda/cybergisx/python3-0.9.0/lib/python3.8/http/client.py:1251\u001b[0m, in \u001b[0;36mHTTPConnection.endheaders\u001b[0;34m(self, message_body, encode_chunked)\u001b[0m\n\u001b[1;32m 1249\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[1;32m 1250\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m CannotSendHeader()\n\u001b[0;32m-> 1251\u001b[0m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_send_output\u001b[49m\u001b[43m(\u001b[49m\u001b[43mmessage_body\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mencode_chunked\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mencode_chunked\u001b[49m\u001b[43m)\u001b[49m\n", "File \u001b[0;32m/cvmfs/cybergis.illinois.edu/software/conda/cybergisx/python3-0.9.0/lib/python3.8/http/client.py:1011\u001b[0m, in \u001b[0;36mHTTPConnection._send_output\u001b[0;34m(self, message_body, encode_chunked)\u001b[0m\n\u001b[1;32m 1009\u001b[0m msg \u001b[38;5;241m=\u001b[39m \u001b[38;5;124mb\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;130;01m\\r\u001b[39;00m\u001b[38;5;130;01m\\n\u001b[39;00m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;241m.\u001b[39mjoin(\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_buffer)\n\u001b[1;32m 1010\u001b[0m \u001b[38;5;28;01mdel\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_buffer[:]\n\u001b[0;32m-> 1011\u001b[0m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43msend\u001b[49m\u001b[43m(\u001b[49m\u001b[43mmsg\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 1013\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m message_body \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m:\n\u001b[1;32m 1014\u001b[0m \n\u001b[1;32m 1015\u001b[0m \u001b[38;5;66;03m# create a consistent interface to message_body\u001b[39;00m\n\u001b[1;32m 1016\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mhasattr\u001b[39m(message_body, \u001b[38;5;124m'\u001b[39m\u001b[38;5;124mread\u001b[39m\u001b[38;5;124m'\u001b[39m):\n\u001b[1;32m 1017\u001b[0m \u001b[38;5;66;03m# Let file-like take precedence over byte-like. This\u001b[39;00m\n\u001b[1;32m 1018\u001b[0m \u001b[38;5;66;03m# is needed to allow the current position of mmap'ed\u001b[39;00m\n\u001b[1;32m 1019\u001b[0m \u001b[38;5;66;03m# files to be taken into account.\u001b[39;00m\n", "File \u001b[0;32m/cvmfs/cybergis.illinois.edu/software/conda/cybergisx/python3-0.9.0/lib/python3.8/http/client.py:951\u001b[0m, in \u001b[0;36mHTTPConnection.send\u001b[0;34m(self, data)\u001b[0m\n\u001b[1;32m 949\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39msock \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m:\n\u001b[1;32m 950\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mauto_open:\n\u001b[0;32m--> 951\u001b[0m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mconnect\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 952\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[1;32m 953\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m NotConnected()\n", "File \u001b[0;32m/cvmfs/cybergis.illinois.edu/software/conda/cybergisx/python3-0.9.0/lib/python3.8/http/client.py:1418\u001b[0m, in \u001b[0;36mHTTPSConnection.connect\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m 1415\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mconnect\u001b[39m(\u001b[38;5;28mself\u001b[39m):\n\u001b[1;32m 1416\u001b[0m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mConnect to a host on a given (SSL) port.\u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[0;32m-> 1418\u001b[0m \u001b[38;5;28;43msuper\u001b[39;49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mconnect\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 1420\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_tunnel_host:\n\u001b[1;32m 1421\u001b[0m server_hostname \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_tunnel_host\n", "File \u001b[0;32m/cvmfs/cybergis.illinois.edu/software/conda/cybergisx/python3-0.9.0/lib/python3.8/http/client.py:922\u001b[0m, in \u001b[0;36mHTTPConnection.connect\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m 920\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mconnect\u001b[39m(\u001b[38;5;28mself\u001b[39m):\n\u001b[1;32m 921\u001b[0m \u001b[38;5;124;03m\"\"\"Connect to the host and port specified in __init__.\"\"\"\u001b[39;00m\n\u001b[0;32m--> 922\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39msock \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_create_connection\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m 923\u001b[0m \u001b[43m \u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mhost\u001b[49m\u001b[43m,\u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mport\u001b[49m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mtimeout\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43msource_address\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 924\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39msock\u001b[38;5;241m.\u001b[39msetsockopt(socket\u001b[38;5;241m.\u001b[39mIPPROTO_TCP, socket\u001b[38;5;241m.\u001b[39mTCP_NODELAY, \u001b[38;5;241m1\u001b[39m)\n\u001b[1;32m 926\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_tunnel_host:\n", "File \u001b[0;32m/cvmfs/cybergis.illinois.edu/software/conda/cybergisx/python3-0.9.0/lib/python3.8/socket.py:787\u001b[0m, in \u001b[0;36mcreate_connection\u001b[0;34m(address, timeout, source_address)\u001b[0m\n\u001b[1;32m 785\u001b[0m host, port \u001b[38;5;241m=\u001b[39m address\n\u001b[1;32m 786\u001b[0m err \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;01mNone\u001b[39;00m\n\u001b[0;32m--> 787\u001b[0m \u001b[38;5;28;01mfor\u001b[39;00m res \u001b[38;5;129;01min\u001b[39;00m \u001b[43mgetaddrinfo\u001b[49m\u001b[43m(\u001b[49m\u001b[43mhost\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mport\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m0\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mSOCK_STREAM\u001b[49m\u001b[43m)\u001b[49m:\n\u001b[1;32m 788\u001b[0m af, socktype, proto, canonname, sa \u001b[38;5;241m=\u001b[39m res\n\u001b[1;32m 789\u001b[0m sock \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;01mNone\u001b[39;00m\n", "File \u001b[0;32m/cvmfs/cybergis.illinois.edu/software/conda/cybergisx/python3-0.9.0/lib/python3.8/socket.py:918\u001b[0m, in \u001b[0;36mgetaddrinfo\u001b[0;34m(host, port, family, type, proto, flags)\u001b[0m\n\u001b[1;32m 915\u001b[0m \u001b[38;5;66;03m# We override this function since we want to translate the numeric family\u001b[39;00m\n\u001b[1;32m 916\u001b[0m \u001b[38;5;66;03m# and socket type values to enum constants.\u001b[39;00m\n\u001b[1;32m 917\u001b[0m addrlist \u001b[38;5;241m=\u001b[39m []\n\u001b[0;32m--> 918\u001b[0m \u001b[38;5;28;01mfor\u001b[39;00m res \u001b[38;5;129;01min\u001b[39;00m \u001b[43m_socket\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mgetaddrinfo\u001b[49m\u001b[43m(\u001b[49m\u001b[43mhost\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mport\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mfamily\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43mtype\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mproto\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mflags\u001b[49m\u001b[43m)\u001b[49m:\n\u001b[1;32m 919\u001b[0m af, socktype, proto, canonname, sa \u001b[38;5;241m=\u001b[39m res\n\u001b[1;32m 920\u001b[0m addrlist\u001b[38;5;241m.\u001b[39mappend((_intenum_converter(af, AddressFamily),\n\u001b[1;32m 921\u001b[0m _intenum_converter(socktype, SocketKind),\n\u001b[1;32m 922\u001b[0m proto, canonname, sa))\n", "\u001b[0;31mgaierror\u001b[0m: [Errno -5] No address associated with hostname" ] } ] } }, "6a2b92ebe2964c83b74f8396f4abfcb4": { "model_module": "@jupyter-widgets/controls", "model_module_version": "1.5.0", "model_name": "GridBoxModel", "state": { "children": [ "IPY_MODEL_72f3ddd18ac74a3bbb89a6bc2b822f07", "IPY_MODEL_dc599cab6cce4575a11dd026075ecab3", "IPY_MODEL_6ccfe8524ee7416890e56bd1bb32eb14" ], "layout": "IPY_MODEL_2ad28e0006314aeb90c204a61ee8ced8" } }, "6a41543b77a74bd1962f90ed3ea5be4e": { "model_module": "@jupyter-widgets/controls", "model_module_version": "1.5.0", "model_name": "ButtonStyleModel", "state": {} }, "6a4ac1af02c44431b29d3522f1c0821f": { "model_module": "@jupyter-widgets/controls", "model_module_version": "1.5.0", "model_name": "ComboboxModel", "state": { "description": "Enter Name:", "ensure_option": false, "layout": "IPY_MODEL_f13d184214c24fbd8aa458aae7d30fad", "placeholder": "Select new name", "style": "IPY_MODEL_1f4e857f32cd4f248b73fb8e35778bb2" } }, "6ad603ca46934d07b2ea5f57ac5f17ab": { "model_module": "@jupyter-widgets/controls", "model_module_version": "1.5.0", "model_name": "SliderStyleModel", "state": { "description_width": "auto" } }, "6ae8a6fe296e4d2abc96e3850ba13ab9": { "model_module": "@jupyter-widgets/base", "model_module_version": "1.2.0", "model_name": "LayoutModel", "state": {} }, "6b33092a1a3b41ebae0497258c270573": { "model_module": "@jupyter-widgets/controls", "model_module_version": "1.5.0", "model_name": "DescriptionStyleModel", "state": { "description_width": "" } }, 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