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27 changed files with 24 additions and 48740 deletions

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[flake8]
max-line-length = 120

1
.gitattributes vendored
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* text=crlf

132
.gitignore vendored
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# ---> JupyterNotebooks
# gitignore template for Jupyter Notebooks
# website: http://jupyter.org/
# Created by https://www.toptal.com/developers/gitignore/api/python,pycharm+all
# Edit at https://www.toptal.com/developers/gitignore?templates=python,pycharm+all
.ipynb_checkpoints
*/.ipynb_checkpoints/*
### PyCharm+all ###
# Covers JetBrains IDEs: IntelliJ, RubyMine, PhpStorm, AppCode, PyCharm, CLion, Android Studio, WebStorm and Rider
# Reference: https://intellij-support.jetbrains.com/hc/en-us/articles/206544839
# IPython
profile_default/
ipython_config.py
# User-specific stuff
.idea/**/workspace.xml
.idea/**/tasks.xml
.idea/**/usage.statistics.xml
.idea/**/dictionaries
.idea/**/shelf
# Remove previous ipynb_checkpoints
# git rm -r .ipynb_checkpoints/
# AWS User-specific
.idea/**/aws.xml
# Generated files
.idea/**/contentModel.xml
# Sensitive or high-churn files
.idea/**/dataSources/
.idea/**/dataSources.ids
.idea/**/dataSources.local.xml
.idea/**/sqlDataSources.xml
.idea/**/dynamic.xml
.idea/**/uiDesigner.xml
.idea/**/dbnavigator.xml
# Gradle
.idea/**/gradle.xml
.idea/**/libraries
# Gradle and Maven with auto-import
# When using Gradle or Maven with auto-import, you should exclude module files,
# since they will be recreated, and may cause churn. Uncomment if using
# auto-import.
# .idea/artifacts
# .idea/compiler.xml
# .idea/jarRepositories.xml
# .idea/modules.xml
# .idea/*.iml
# .idea/modules
# *.iml
# *.ipr
# CMake
cmake-build-*/
# Mongo Explorer plugin
.idea/**/mongoSettings.xml
# File-based project format
*.iws
# IntelliJ
out/
# mpeltonen/sbt-idea plugin
.idea_modules/
# JIRA plugin
atlassian-ide-plugin.xml
# Cursive Clojure plugin
.idea/replstate.xml
# SonarLint plugin
.idea/sonarlint/
# Crashlytics plugin (for Android Studio and IntelliJ)
com_crashlytics_export_strings.xml
crashlytics.properties
crashlytics-build.properties
fabric.properties
# Editor-based Rest Client
.idea/httpRequests
# Android studio 3.1+ serialized cache file
.idea/caches/build_file_checksums.ser
### PyCharm+all Patch ###
# Ignores the whole .idea folder and all .iml files
# See https://github.com/joeblau/gitignore.io/issues/186 and https://github.com/joeblau/gitignore.io/issues/360
.idea/*
# Reason: https://github.com/joeblau/gitignore.io/issues/186#issuecomment-249601023
*.iml
modules.xml
.idea/misc.xml
*.ipr
# Sonarlint plugin
.idea/sonarlint
### Python ###
# ---> Python
# Byte-compiled / optimized / DLL files
__pycache__/
*.py[cod]
@ -201,7 +116,15 @@ ipython_config.py
# https://python-poetry.org/docs/basic-usage/#commit-your-poetrylock-file-to-version-control
#poetry.lock
# PEP 582; used by e.g. github.com/David-OConnor/pyflow
# pdm
# Similar to Pipfile.lock, it is generally recommended to include pdm.lock in version control.
#pdm.lock
# pdm stores project-wide configurations in .pdm.toml, but it is recommended to not include it
# in version control.
# https://pdm.fming.dev/#use-with-ide
.pdm.toml
# PEP 582; used by e.g. github.com/David-OConnor/pyflow and github.com/pdm-project/pdm
__pypackages__/
# Celery stuff
@ -245,13 +168,13 @@ dmypy.json
cython_debug/
# PyCharm
# JetBrains specific template is maintainted in a separate JetBrains.gitignore that can
# JetBrains specific template is maintained in a separate JetBrains.gitignore that can
# be found at https://github.com/github/gitignore/blob/main/Global/JetBrains.gitignore
# and can be added to the global gitignore or merged into this file. For a more nuclear
# option (not recommended) you can uncomment the following to ignore the entire idea folder.
#.idea/
### VisualStudioCode ###
# ---> VisualStudioCode
.vscode/*
!.vscode/settings.json
!.vscode/tasks.json
@ -265,14 +188,3 @@ cython_debug/
# Built Visual Studio Code Extensions
*.vsix
### VisualStudioCode Patch ###
# Ignore all local history of files
.history
.ionide
# End of https://www.toptal.com/developers/gitignore/api/python,pycharm+all
# JS
node_modules/
test.csv

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{
"recommendations": [
"ms-python.black-formatter",
"ms-python.flake8",
"ms-python.isort",
"ms-toolsai.jupyter",
"ms-toolsai.datawrangler",
"ms-python.python",
"donjayamanne.python-environment-manager",
// optional
"usernamehw.errorlens"
]
}

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.vscode/launch.json vendored
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{
// Use IntelliSense to learn about possible attributes.
// Hover to view descriptions of existing attributes.
// For more information, visit: https://go.microsoft.com/fwlink/?linkid=830387
"version": "0.2.0",
"configurations": [
{
"name": "mai-service",
"type": "debugpy",
"request": "launch",
"program": "run.py",
"console": "integratedTerminal",
"justMyCode": true
}
]
}

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.vscode/settings.json vendored
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{
"files.autoSave": "onFocusChange",
"files.exclude": {
"**/__pycache__": true
},
"editor.detectIndentation": false,
"editor.formatOnType": false,
"editor.formatOnPaste": true,
"editor.formatOnSave": true,
"editor.tabSize": 4,
"editor.insertSpaces": true,
"editor.codeActionsOnSave": {
"source.organizeImports": "explicit",
"source.sortImports": "explicit"
},
"editor.stickyScroll.enabled": false,
"diffEditor.ignoreTrimWhitespace": false,
"debug.showVariableTypes": true,
"workbench.editor.highlightModifiedTabs": true,
"git.suggestSmartCommit": false,
"git.autofetch": true,
"git.openRepositoryInParentFolders": "always",
"git.confirmSync": false,
"errorLens.gutterIconsEnabled": true,
"errorLens.messageEnabled": false,
"[python]": {
"editor.defaultFormatter": "ms-python.black-formatter",
},
"python.languageServer": "Pylance",
"python.analysis.typeCheckingMode": "basic",
"python.analysis.autoImportCompletions": true,
"isort.args": [
"--profile",
"black"
],
"notebook.lineNumbers": "on",
"notebook.output.minimalErrorRendering": true,
}

2
README.md Normal file
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# PIbd-33_Dyakonov_R_R_MAI

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Before

Width:  |  Height:  |  Size: 111 KiB

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import importlib
import os
import traceback
import matplotlib
from apiflask import APIBlueprint, APIFlask
from flask_cors import CORS
matplotlib.use("agg")
cors = CORS()
api_bp = APIBlueprint("api", __name__, url_prefix="/api/v1")
dataset_path: str | None = None
class Config:
SECRET_KEY = "secret!"
SEND_FILE_MAX_AGE_DEFAULT = -1
def create_app():
global dataset_path
# Create and configure app
app = APIFlask(
"MAI Service",
title="MAI Service API",
docs_path="/",
version="1.0",
static_folder="",
template_folder="",
)
app.config.from_object(Config)
dataset_path = os.path.join(app.instance_path, "dataset")
os.makedirs(dataset_path, exist_ok=True)
@app.errorhandler(Exception)
def my_error_processor(error):
traceback.print_exception(error)
return {"message": str(error), "detail": "No details"}, 500
# Import custom REST methods
importlib.import_module("backend.api")
# Enable REST API
app.register_blueprint(api_bp)
# Enable app extensions
cors.init_app(app)
return app

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from apiflask import FileSchema, Schema, fields
from flask import send_file
from backend import api_bp, dataset_path
from backend.service import Service
class FileUpload(Schema):
file = fields.File(required=True)
class ColumnInfoDto(Schema):
datatype = fields.String()
items = fields.List(fields.String())
class TableColumnDto(Schema):
name = fields.String()
datatype = fields.String()
items = fields.List(fields.String())
service = Service(dataset_path)
@api_bp.post("/dataset")
@api_bp.input(FileUpload, location="files")
def upload_dataset(files_data):
uploaded_file = files_data["file"]
return service.upload_dataset(uploaded_file)
@api_bp.get("/dataset")
def get_all_datasets():
return service.get_all_datasets()
@api_bp.get("/dataset/<string:name>")
@api_bp.output(TableColumnDto(many=True))
def get_dataset_info(name: str):
return service.get_dataset_info(name)
@api_bp.get("/dataset/<string:name>/<string:column>")
@api_bp.output(ColumnInfoDto)
def get_column_info(name: str, column: str):
return service.get_column_info(name, column)
@api_bp.get("/dataset/draw/hist/<string:name>/<string:column>")
@api_bp.output(
FileSchema(type="string", format="binary"), content_type="image/png", example=""
)
def get_dataset_hist(name: str, column: str):
data = service.get_hist(name, column)
data.seek(0)
return send_file(data, download_name=f"{name}.hist.png", mimetype="image/png")

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import io
import os
import pathlib
from typing import BinaryIO, Dict, List
import pandas as pd
from matplotlib.figure import Figure
from werkzeug.datastructures import FileStorage
from werkzeug.utils import secure_filename
class Service:
def __init__(self, dataset_path: str | None) -> None:
if dataset_path is None:
raise Exception("Dataset path is not defined")
self.__path: str = dataset_path
def __get_dataset(self, filename: str) -> pd.DataFrame:
full_file_name = os.path.join(self.__path, secure_filename(filename))
return pd.read_csv(full_file_name)
def upload_dataset(self, file: FileStorage) -> str:
if file.filename is None:
raise Exception("Dataset upload error")
file_name: str = file.filename
full_file_name = os.path.join(self.__path, secure_filename(file_name))
file.save(full_file_name)
return file_name
def get_all_datasets(self) -> List[str]:
return [file.name for file in pathlib.Path(self.__path).glob("*.csv")]
def get_dataset_info(self, filename) -> List[Dict]:
dataset = self.__get_dataset(filename)
dataset_info = []
for column in dataset.columns:
items = dataset[column].astype(str)
column_info = {
"name": column,
"datatype": dataset.dtypes[column],
"items": items,
}
dataset_info.append(column_info)
return dataset_info
def get_column_info(self, filename, column) -> Dict:
dataset = self.__get_dataset(filename)
datatype = dataset.dtypes[column]
items = sorted(dataset[column].astype(str).unique())
return {"datatype": datatype, "items": items}
def get_hist(self, filename, column) -> BinaryIO:
dataset = self.__get_dataset(filename)
bytes = io.BytesIO()
plot: Figure | None = dataset.plot.hist(column=[column], bins=80).get_figure()
if plot is None:
raise Exception("Can't create hist plot")
plot.savefig(bytes, dpi=300, format="png")
return bytes

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crim,zn,indus,chas,nox,rm,age,dis,rad,tax,ptratio,b,lstat,medv
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0.03932,0,3.41,0,0.489,6.405,73.9,3.0921,2,270,17.8,393.55,8.2,22
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0.12083,0,2.89,0,0.445,8.069,76,3.4952,2,276,18,396.9,4.21,38.7
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0.14231,0,10.01,0,0.547,6.254,84.2,2.2565,6,432,17.8,388.74,10.45,18.5
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0.13158,0,10.01,0,0.547,6.176,72.5,2.7301,6,432,17.8,393.3,12.04,21.2
0.15098,0,10.01,0,0.547,6.021,82.6,2.7474,6,432,17.8,394.51,10.3,19.2
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0.06899,0,25.65,0,0.581,5.87,69.7,2.2577,2,188,19.1,389.15,14.37,22
0.07165,0,25.65,0,0.581,6.004,84.1,2.1974,2,188,19.1,377.67,14.27,20.3
0.09299,0,25.65,0,0.581,5.961,92.9,2.0869,2,188,19.1,378.09,17.93,20.5
0.15038,0,25.65,0,0.581,5.856,97,1.9444,2,188,19.1,370.31,25.41,17.3
0.09849,0,25.65,0,0.581,5.879,95.8,2.0063,2,188,19.1,379.38,17.58,18.8
0.16902,0,25.65,0,0.581,5.986,88.4,1.9929,2,188,19.1,385.02,14.81,21.4
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0.25915,0,21.89,0,0.624,5.693,96,1.7883,4,437,21.2,392.11,17.19,16.2
0.32543,0,21.89,0,0.624,6.431,98.8,1.8125,4,437,21.2,396.9,15.39,18
0.88125,0,21.89,0,0.624,5.637,94.7,1.9799,4,437,21.2,396.9,18.34,14.3
0.34006,0,21.89,0,0.624,6.458,98.9,2.1185,4,437,21.2,395.04,12.6,19.2
1.19294,0,21.89,0,0.624,6.326,97.7,2.271,4,437,21.2,396.9,12.26,19.6
0.59005,0,21.89,0,0.624,6.372,97.9,2.3274,4,437,21.2,385.76,11.12,23
0.32982,0,21.89,0,0.624,5.822,95.4,2.4699,4,437,21.2,388.69,15.03,18.4
0.97617,0,21.89,0,0.624,5.757,98.4,2.346,4,437,21.2,262.76,17.31,15.6
0.55778,0,21.89,0,0.624,,98.2,2.1107,4,437,21.2,394.67,16.96,18.1
0.32264,0,21.89,0,0.624,5.942,93.5,1.9669,4,437,21.2,378.25,16.9,17.4
0.35233,0,21.89,0,0.624,6.454,98.4,1.8498,4,437,21.2,394.08,14.59,17.1
0.2498,0,21.89,0,0.624,5.857,98.2,1.6686,4,437,21.2,392.04,21.32,13.3
0.54452,0,21.89,0,0.624,6.151,97.9,1.6687,4,437,21.2,396.9,18.46,17.8
0.2909,0,21.89,0,0.624,6.174,93.6,1.6119,4,437,21.2,388.08,24.16,14
1.62864,0,21.89,0,0.624,5.019,100,1.4394,4,437,21.2,396.9,34.41,14.4
3.32105,0,19.58,1,0.871,5.403,100,1.3216,5,403,14.7,396.9,26.82,13.4
4.0974,0,19.58,0,0.871,5.468,100,1.4118,5,403,14.7,396.9,26.42,15.6
2.77974,0,19.58,0,0.871,4.903,97.8,1.3459,5,403,14.7,396.9,29.29,11.8
2.37934,0,19.58,0,0.871,6.13,100,1.4191,5,403,14.7,172.91,27.8,13.8
2.15505,0,19.58,0,0.871,5.628,100,1.5166,5,403,14.7,169.27,16.65,15.6
2.36862,0,19.58,0,0.871,4.926,95.7,1.4608,5,403,14.7,391.71,29.53,14.6
2.33099,0,19.58,0,0.871,5.186,93.8,1.5296,5,403,14.7,356.99,28.32,17.8
2.73397,0,19.58,0,0.871,5.597,94.9,1.5257,5,403,14.7,351.85,21.45,15.4
1.6566,0,19.58,0,0.871,6.122,97.3,1.618,5,403,14.7,372.8,14.1,21.5
1.49632,0,19.58,0,0.871,5.404,100,1.5916,5,403,14.7,341.6,13.28,19.6
1.12658,0,19.58,1,0.871,5.012,88,1.6102,5,403,14.7,343.28,12.12,15.3
2.14918,0,19.58,0,0.871,5.709,98.5,1.6232,5,403,14.7,261.95,15.79,19.4
1.41385,0,19.58,1,0.871,6.129,96,1.7494,5,403,14.7,321.02,15.12,17
3.53501,0,19.58,1,0.871,6.152,82.6,1.7455,5,403,14.7,88.01,15.02,15.6
2.44668,0,19.58,0,0.871,5.272,94,1.7364,5,403,14.7,88.63,16.14,13.1
1.22358,0,19.58,0,0.605,6.943,97.4,1.8773,5,403,14.7,363.43,4.59,41.3
1.34284,0,19.58,0,0.605,6.066,100,1.7573,5,403,14.7,353.89,6.43,24.3
1.42502,0,19.58,0,0.871,6.51,100,1.7659,5,403,14.7,364.31,7.39,23.3
1.27346,0,19.58,1,0.605,6.25,92.6,1.7984,5,403,14.7,338.92,5.5,27
1.46336,0,19.58,0,0.605,7.489,90.8,1.9709,5,403,14.7,374.43,1.73,50
1.83377,0,19.58,1,0.605,7.802,98.2,2.0407,5,403,14.7,389.61,1.92,50
1.51902,0,19.58,1,0.605,8.375,93.9,2.162,5,403,14.7,388.45,3.32,50
2.24236,0,19.58,0,0.605,5.854,91.8,2.422,5,403,14.7,395.11,11.64,22.7
2.924,0,19.58,0,0.605,6.101,93,2.2834,5,403,14.7,240.16,9.81,25
2.01019,0,19.58,0,0.605,7.929,96.2,2.0459,5,403,14.7,369.3,3.7,50
1.80028,0,19.58,0,0.605,5.877,79.2,2.4259,5,403,14.7,227.61,12.14,23.8
2.3004,0,19.58,0,0.605,6.319,96.1,2.1,5,403,14.7,297.09,11.1,23.8
2.44953,0,19.58,0,0.605,6.402,95.2,2.2625,5,403,14.7,330.04,11.32,22.3
1.20742,0,19.58,0,0.605,5.875,94.6,2.4259,5,403,14.7,292.29,14.43,17.4
2.3139,0,19.58,0,0.605,5.88,97.3,2.3887,5,403,14.7,348.13,12.03,19.1
0.13914,0,4.05,0,0.51,5.572,88.5,2.5961,5,296,16.6,396.9,14.69,23.1
0.09178,0,4.05,0,0.51,6.416,84.1,2.6463,5,296,16.6,395.5,9.04,23.6
0.08447,0,4.05,0,0.51,5.859,68.7,2.7019,5,296,16.6,393.23,9.64,22.6
0.06664,0,4.05,0,0.51,6.546,33.1,3.1323,5,296,16.6,390.96,5.33,29.4
0.07022,0,4.05,0,0.51,6.02,47.2,3.5549,5,296,16.6,393.23,10.11,23.2
0.05425,0,4.05,0,0.51,6.315,73.4,3.3175,5,296,16.6,395.6,6.29,24.6
0.06642,0,4.05,0,0.51,6.86,74.4,2.9153,5,296,16.6,391.27,6.92,29.9
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0.09103,0,2.46,0,0.488,7.155,92.2,2.7006,3,193,17.8,394.12,4.82,37.9
0.10008,0,2.46,0,0.488,6.563,95.6,2.847,3,193,17.8,396.9,5.68,32.5
0.08308,0,2.46,0,0.488,5.604,89.8,2.9879,3,193,17.8,391,13.98,26.4
0.06047,0,2.46,0,0.488,6.153,68.8,3.2797,3,193,17.8,387.11,13.15,29.6
0.05602,0,2.46,0,0.488,7.831,53.6,3.1992,3,193,17.8,392.63,4.45,50
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0.09068,45,3.44,0,0.437,6.951,21.5,6.4798,5,398,15.2,377.68,5.1,37
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0.08664,45,3.44,0,0.437,7.178,26.3,6.4798,5,398,15.2,390.49,2.87,36.4
0.02187,60,2.93,0,0.401,6.8,9.9,6.2196,1,265,15.6,393.37,5.03,31.1
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0.31533,0,6.2,0,0.504,8.266,78.3,2.8944,8,307,17.4,385.05,4.14,44.8
0.52693,0,6.2,0,0.504,8.725,83,2.8944,8,307,17.4,382,4.63,50
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0.41238,0,6.2,0,0.504,7.163,79.9,3.2157,8,307,17.4,372.08,6.36,31.6
0.29819,0,6.2,0,0.504,7.686,17,3.3751,8,307,17.4,377.51,3.92,46.7
0.44178,0,6.2,0,0.504,6.552,21.4,3.3751,8,307,17.4,380.34,3.76,31.5
0.537,0,6.2,0,0.504,5.981,68.1,3.6715,8,307,17.4,378.35,11.65,24.3
0.46296,0,6.2,0,0.504,7.412,76.9,3.6715,8,307,17.4,376.14,5.25,31.7
0.57529,0,6.2,0,0.507,8.337,73.3,3.8384,8,307,17.4,385.91,2.47,41.7
0.33147,0,6.2,0,0.507,8.247,70.4,3.6519,8,307,17.4,378.95,3.95,48.3
0.44791,0,6.2,1,0.507,6.726,66.5,3.6519,8,307,17.4,360.2,8.05,29
0.33045,0,6.2,0,0.507,6.086,61.5,3.6519,8,307,17.4,376.75,10.88,24
0.52058,0,6.2,1,0.507,6.631,76.5,4.148,8,307,17.4,388.45,9.54,25.1
0.51183,0,6.2,0,0.507,7.358,71.6,4.148,8,307,17.4,390.07,4.73,31.5
0.08244,30,4.93,0,0.428,6.481,18.5,6.1899,6,300,16.6,379.41,6.36,23.7
0.09252,30,4.93,0,0.428,6.606,42.2,6.1899,6,300,16.6,383.78,7.37,23.3
0.11329,30,4.93,0,0.428,6.897,54.3,6.3361,6,300,16.6,391.25,11.38,22
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38.3518,0,18.1,0,0.693,5.453,100,1.4896,24,666,20.2,396.9,30.59,5
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9.59571,0,18.1,0,0.693,6.404,100,1.639,24,666,20.2,376.11,20.31,12.1
24.8017,0,18.1,0,0.693,5.349,96,1.7028,24,666,20.2,396.9,19.77,8.3
41.5292,0,18.1,0,0.693,5.531,85.4,1.6074,24,666,20.2,329.46,27.38,8.5
67.9208,0,18.1,0,0.693,5.683,100,1.4254,24,666,20.2,384.97,22.98,5
20.7162,0,18.1,0,0.659,4.138,100,1.1781,24,666,20.2,370.22,23.34,11.9
11.9511,0,18.1,0,0.659,5.608,100,1.2852,24,666,20.2,332.09,12.13,27.9
7.40389,0,18.1,0,0.597,5.617,97.9,1.4547,24,666,20.2,314.64,26.4,17.2
14.4383,0,18.1,0,0.597,6.852,100,1.4655,24,666,20.2,179.36,19.78,27.5
51.1358,0,18.1,0,0.597,5.757,100,1.413,24,666,20.2,2.6,10.11,15
14.0507,0,18.1,0,0.597,6.657,100,1.5275,24,666,20.2,35.05,21.22,17.2
18.811,0,18.1,0,0.597,4.628,100,1.5539,24,666,20.2,28.79,34.37,17.9
28.6558,0,18.1,0,0.597,5.155,100,1.5894,24,666,20.2,210.97,20.08,16.3
45.7461,0,18.1,0,0.693,4.519,100,1.6582,24,666,20.2,88.27,36.98,7
18.0846,0,18.1,0,0.679,6.434,100,1.8347,24,666,20.2,27.25,29.05,7.2
10.8342,0,18.1,0,0.679,6.782,90.8,1.8195,24,666,20.2,21.57,25.79,7.5
25.9406,0,18.1,0,0.679,5.304,89.1,1.6475,24,666,20.2,127.36,26.64,10.4
73.5341,0,18.1,0,0.679,5.957,100,1.8026,24,666,20.2,16.45,20.62,8.8
11.8123,0,18.1,0,0.718,6.824,76.5,1.794,24,666,20.2,48.45,22.74,8.4
11.0874,0,18.1,0,0.718,6.411,100,1.8589,24,666,20.2,318.75,15.02,16.7
7.02259,0,18.1,0,0.718,6.006,95.3,1.8746,24,666,20.2,319.98,15.7,14.2
12.0482,0,18.1,0,0.614,5.648,87.6,1.9512,24,666,20.2,291.55,14.1,20.8
7.05042,0,18.1,0,0.614,6.103,85.1,2.0218,24,666,20.2,2.52,23.29,13.4
8.79212,0,18.1,0,0.584,5.565,70.6,2.0635,24,666,20.2,3.65,17.16,11.7
15.8603,0,18.1,0,0.679,5.896,95.4,1.9096,24,666,20.2,7.68,24.39,8.3
12.2472,0,18.1,0,0.584,5.837,59.7,1.9976,24,666,20.2,24.65,15.69,10.2
37.6619,0,18.1,0,0.679,6.202,78.7,1.8629,24,666,20.2,18.82,14.52,10.9
7.36711,0,18.1,0,0.679,6.193,78.1,1.9356,24,666,20.2,96.73,21.52,11
9.33889,0,18.1,0,0.679,6.38,95.6,1.9682,24,666,20.2,60.72,24.08,9.5
8.49213,0,18.1,0,0.584,6.348,86.1,2.0527,24,666,20.2,83.45,17.64,14.5
10.0623,0,18.1,0,0.584,6.833,94.3,2.0882,24,666,20.2,81.33,19.69,14.1
6.44405,0,18.1,0,0.584,6.425,74.8,2.2004,24,666,20.2,97.95,12.03,16.1
5.58107,0,18.1,0,0.713,6.436,87.9,2.3158,24,666,20.2,100.19,16.22,14.3
13.9134,0,18.1,0,0.713,6.208,95,2.2222,24,666,20.2,100.63,15.17,11.7
11.1604,0,18.1,0,0.74,6.629,94.6,2.1247,24,666,20.2,109.85,23.27,13.4
14.4208,0,18.1,0,0.74,6.461,93.3,2.0026,24,666,20.2,27.49,18.05,9.6
15.1772,0,18.1,0,0.74,6.152,100,1.9142,24,666,20.2,9.32,26.45,8.7
13.6781,0,18.1,0,0.74,5.935,87.9,1.8206,24,666,20.2,68.95,34.02,8.4
9.39063,0,18.1,0,0.74,5.627,93.9,1.8172,24,666,20.2,396.9,22.88,12.8
22.0511,0,18.1,0,0.74,5.818,92.4,1.8662,24,666,20.2,391.45,22.11,10.5
9.72418,0,18.1,0,0.74,6.406,97.2,2.0651,24,666,20.2,385.96,19.52,17.1
5.66637,0,18.1,0,0.74,6.219,100,2.0048,24,666,20.2,395.69,16.59,18.4
9.96654,0,18.1,0,0.74,6.485,100,1.9784,24,666,20.2,386.73,18.85,15.4
12.8023,0,18.1,0,0.74,5.854,96.6,1.8956,24,666,20.2,240.52,23.79,10.8
10.6718,0,18.1,0,0.74,6.459,94.8,1.9879,24,666,20.2,43.06,23.98,11.8
6.28807,0,18.1,0,0.74,6.341,96.4,2.072,24,666,20.2,318.01,17.79,14.9
9.92485,0,18.1,0,0.74,6.251,96.6,2.198,24,666,20.2,388.52,16.44,12.6
9.32909,0,18.1,0,0.713,6.185,98.7,2.2616,24,666,20.2,396.9,18.13,14.1
7.52601,0,18.1,0,0.713,6.417,98.3,2.185,24,666,20.2,304.21,19.31,13
6.71772,0,18.1,0,0.713,6.749,92.6,2.3236,24,666,20.2,0.32,17.44,13.4
5.44114,0,18.1,0,0.713,6.655,98.2,2.3552,24,666,20.2,355.29,17.73,15.2
5.09017,0,18.1,0,0.713,6.297,91.8,2.3682,24,666,20.2,385.09,17.27,16.1
8.24809,0,18.1,0,0.713,7.393,99.3,2.4527,24,666,20.2,375.87,16.74,17.8
9.51363,0,18.1,0,0.713,6.728,94.1,2.4961,24,666,20.2,6.68,18.71,14.9
4.75237,0,18.1,0,0.713,6.525,86.5,2.4358,24,666,20.2,50.92,18.13,14.1
4.66883,0,18.1,0,0.713,5.976,87.9,2.5806,24,666,20.2,10.48,19.01,12.7
8.20058,0,18.1,0,0.713,5.936,80.3,2.7792,24,666,20.2,3.5,16.94,13.5
7.75223,0,18.1,0,0.713,6.301,83.7,2.7831,24,666,20.2,272.21,16.23,14.9
6.80117,0,18.1,0,0.713,6.081,84.4,2.7175,24,666,20.2,396.9,14.7,20
4.81213,0,18.1,0,0.713,6.701,90,2.5975,24,666,20.2,255.23,16.42,16.4
3.69311,0,18.1,0,0.713,6.376,88.4,2.5671,24,666,20.2,391.43,14.65,17.7
6.65492,0,18.1,0,0.713,6.317,83,2.7344,24,666,20.2,396.9,13.99,19.5
5.82115,0,18.1,0,0.713,6.513,89.9,2.8016,24,666,20.2,393.82,10.29,20.2
7.83932,0,18.1,0,0.655,6.209,65.4,2.9634,24,666,20.2,396.9,13.22,21.4
3.1636,0,18.1,0,0.655,5.759,48.2,3.0665,24,666,20.2,334.4,14.13,19.9
3.77498,0,18.1,0,0.655,5.952,84.7,2.8715,24,666,20.2,22.01,17.15,19
4.42228,0,18.1,0,0.584,6.003,94.5,2.5403,24,666,20.2,331.29,21.32,19.1
15.5757,0,18.1,0,0.58,5.926,71,2.9084,24,666,20.2,368.74,18.13,19.1
13.0751,0,18.1,0,0.58,5.713,56.7,2.8237,24,666,20.2,396.9,14.76,20.1
4.34879,0,18.1,0,0.58,6.167,84,3.0334,24,666,20.2,396.9,16.29,19.9
4.03841,0,18.1,0,0.532,6.229,90.7,3.0993,24,666,20.2,395.33,12.87,19.6
3.56868,0,18.1,0,0.58,6.437,75,2.8965,24,666,20.2,393.37,14.36,23.2
4.64689,0,18.1,0,0.614,6.98,67.6,2.5329,24,666,20.2,374.68,11.66,29.8
8.05579,0,18.1,0,0.584,5.427,95.4,2.4298,24,666,20.2,352.58,18.14,13.8
6.39312,0,18.1,0,0.584,6.162,97.4,2.206,24,666,20.2,302.76,24.1,13.3
4.87141,0,18.1,0,0.614,6.484,93.6,2.3053,24,666,20.2,396.21,18.68,16.7
15.0234,0,18.1,0,0.614,5.304,97.3,2.1007,24,666,20.2,349.48,24.91,12
10.233,0,18.1,0,0.614,6.185,96.7,2.1705,24,666,20.2,379.7,18.03,14.6
14.3337,0,18.1,0,0.614,6.229,88,1.9512,24,666,20.2,383.32,13.11,21.4
5.82401,0,18.1,0,0.532,6.242,64.7,3.4242,24,666,20.2,396.9,10.74,23
5.70818,0,18.1,0,0.532,6.75,74.9,3.3317,24,666,20.2,393.07,7.74,23.7
5.73116,0,18.1,0,0.532,7.061,77,3.4106,24,666,20.2,395.28,7.01,25
2.81838,0,18.1,0,0.532,5.762,40.3,4.0983,24,666,20.2,392.92,10.42,21.8
2.37857,0,18.1,0,0.583,5.871,41.9,3.724,24,666,20.2,370.73,13.34,20.6
3.67367,0,18.1,0,0.583,6.312,51.9,3.9917,24,666,20.2,388.62,10.58,21.2
5.69175,0,18.1,0,0.583,6.114,79.8,3.5459,24,666,20.2,392.68,14.98,19.1
4.83567,0,18.1,0,0.583,5.905,53.2,3.1523,24,666,20.2,388.22,11.45,20.6
0.15086,0,27.74,0,0.609,5.454,92.7,1.8209,4,711,20.1,395.09,18.06,15.2
0.18337,0,27.74,0,0.609,5.414,98.3,1.7554,4,711,20.1,344.05,23.97,7
0.20746,0,27.74,0,0.609,5.093,98,1.8226,4,711,20.1,318.43,29.68,8.1
0.10574,0,27.74,0,0.609,5.983,98.8,1.8681,4,711,20.1,390.11,18.07,13.6
0.11132,0,27.74,0,0.609,5.983,83.5,2.1099,4,711,20.1,396.9,13.35,20.1
0.17331,0,9.69,0,0.585,5.707,54,2.3817,6,391,19.2,396.9,12.01,21.8
0.27957,0,9.69,0,0.585,5.926,42.6,2.3817,6,391,19.2,396.9,13.59,24.5
0.17899,0,9.69,0,0.585,5.67,28.8,2.7986,6,391,19.2,393.29,17.6,23.1
0.2896,0,9.69,0,0.585,5.39,72.9,2.7986,6,391,19.2,396.9,21.14,19.7
0.26838,0,9.69,0,0.585,5.794,70.6,2.8927,6,391,19.2,396.9,14.1,18.3
0.23912,0,9.69,0,0.585,6.019,65.3,2.4091,6,391,19.2,396.9,12.92,21.2
0.17783,0,9.69,0,0.585,5.569,73.5,2.3999,6,391,19.2,395.77,15.1,17.5
0.22438,0,9.69,0,0.585,6.027,79.7,2.4982,6,391,19.2,396.9,14.33,16.8
0.06263,0,11.93,0,0.573,6.593,69.1,2.4786,1,273,21,391.99,9.67,22.4
0.04527,0,11.93,0,0.573,6.12,76.7,2.2875,1,273,21,396.9,9.08,20.6
0.06076,0,11.93,0,0.573,6.976,91,2.1675,1,273,21,396.9,5.64,23.9
0.10959,0,11.93,0,0.573,6.794,89.3,2.3889,1,273,21,393.45,6.48,22
0.04741,0,11.93,0,0.573,6.03,80.8,2.505,1,273,21,396.9,7.88,11.9
1 crim zn indus chas nox rm age dis rad tax ptratio b lstat medv
2 0.00632 18 2.31 0 0.538 6.575 65.2 4.09 1 296 15.3 396.9 4.98 24
3 0.02731 0 7.07 0 0.469 6.421 78.9 4.9671 2 242 17.8 396.9 9.14 21.6
4 0.02729 0 7.07 0 0.469 7.185 61.1 4.9671 2 242 17.8 392.83 4.03 34.7
5 0.03237 0 2.18 0 0.458 6.998 45.8 6.0622 3 222 18.7 394.63 2.94 33.4
6 0.06905 0 2.18 0 0.458 7.147 54.2 6.0622 3 222 18.7 396.9 5.33 36.2
7 0.02985 0 2.18 0 0.458 6.43 58.7 6.0622 3 222 18.7 394.12 5.21 28.7
8 0.08829 12.5 7.87 0 0.524 6.012 66.6 5.5605 5 311 15.2 395.6 12.43 22.9
9 0.14455 12.5 7.87 0 0.524 6.172 96.1 5.9505 5 311 15.2 396.9 19.15 27.1
10 0.21124 12.5 7.87 0 0.524 5.631 100 6.0821 5 311 15.2 386.63 29.93 16.5
11 0.17004 12.5 7.87 0 0.524 6.004 85.9 6.5921 5 311 15.2 386.71 17.1 18.9
12 0.22489 12.5 7.87 0 0.524 94.3 6.3467 5 311 15.2 392.52 20.45 15
13 0.11747 12.5 7.87 0 0.524 6.009 82.9 6.2267 5 311 15.2 396.9 13.27 18.9
14 0.09378 12.5 7.87 0 0.524 5.889 39 5.4509 5 311 15.2 390.5 15.71 21.7
15 0.62976 0 8.14 0 0.538 5.949 61.8 4.7075 4 307 21 396.9 8.26 20.4
16 0.63796 0 8.14 0 0.538 6.096 84.5 4.4619 4 307 21 380.02 10.26 18.2
17 0.62739 0 8.14 0 0.538 5.834 56.5 4.4986 4 307 21 395.62 8.47 19.9
18 1.05393 0 8.14 0 0.538 5.935 29.3 4.4986 4 307 21 386.85 6.58 23.1
19 0.7842 0 8.14 0 0.538 5.99 81.7 4.2579 4 307 21 386.75 14.67 17.5
20 0.80271 0 8.14 0 0.538 5.456 36.6 3.7965 4 307 21 288.99 11.69 20.2
21 0.7258 0 8.14 0 0.538 5.727 69.5 3.7965 4 307 21 390.95 11.28 18.2
22 1.25179 0 8.14 0 0.538 5.57 98.1 3.7979 4 307 21 376.57 21.02 13.6
23 0.85204 0 8.14 0 0.538 5.965 89.2 4.0123 4 307 21 392.53 13.83 19.6
24 1.23247 0 8.14 0 0.538 6.142 91.7 3.9769 4 307 21 396.9 18.72 15.2
25 0.98843 0 8.14 0 0.538 5.813 100 4.0952 4 307 21 394.54 19.88 14.5
26 0.75026 0 8.14 0 0.538 5.924 94.1 4.3996 4 307 21 394.33 16.3 15.6
27 0.84054 0 8.14 0 0.538 5.599 85.7 4.4546 4 307 21 303.42 16.51 13.9
28 0.67191 0 8.14 0 0.538 5.813 90.3 4.682 4 307 21 376.88 14.81 16.6
29 0.95577 0 8.14 0 0.538 6.047 88.8 4.4534 4 307 21 306.38 17.28 14.8
30 0.77299 0 8.14 0 0.538 6.495 94.4 4.4547 4 307 21 387.94 12.8 18.4
31 1.00245 0 8.14 0 0.538 6.674 87.3 4.239 4 307 21 380.23 11.98 21
32 1.13081 0 8.14 0 0.538 5.713 94.1 4.233 4 307 21 360.17 22.6 12.7
33 1.35472 0 8.14 0 0.538 6.072 100 4.175 4 307 21 376.73 13.04 14.5
34 1.38799 0 8.14 0 0.538 5.95 82 3.99 4 307 21 232.6 27.71 13.2
35 1.15172 0 8.14 0 0.538 5.701 95 3.7872 4 307 21 358.77 18.35 13.1
36 1.61282 0 8.14 0 0.538 6.096 96.9 3.7598 4 307 21 248.31 20.34 13.5
37 0.06417 0 5.96 0 0.499 68.2 3.3603 5 279 19.2 396.9 9.68 18.9
38 0.09744 0 5.96 0 0.499 5.841 61.4 3.3779 5 279 19.2 377.56 11.41 20
39 0.08014 0 5.96 0 0.499 5.85 41.5 3.9342 5 279 19.2 396.9 8.77 21
40 0.17505 0 5.96 0 0.499 5.966 30.2 3.8473 5 279 19.2 393.43 10.13 24.7
41 0.02763 75 2.95 0 0.428 6.595 21.8 5.4011 3 252 18.3 395.63 4.32 30.8
42 0.03359 75 2.95 0 0.428 7.024 15.8 5.4011 3 252 18.3 395.62 1.98 34.9
43 0.12744 0 6.91 0 0.448 6.77 2.9 5.7209 3 233 17.9 385.41 4.84 26.6
44 0.1415 0 6.91 0 0.448 6.169 6.6 5.7209 3 233 17.9 383.37 5.81 25.3
45 0.15936 0 6.91 0 0.448 6.211 6.5 5.7209 3 233 17.9 394.46 7.44 24.7
46 0.12269 0 6.91 0 0.448 6.069 40 5.7209 3 233 17.9 389.39 9.55 21.2
47 0.17142 0 6.91 0 0.448 5.682 33.8 5.1004 3 233 17.9 396.9 10.21 19.3
48 0.18836 0 6.91 0 0.448 5.786 33.3 5.1004 3 233 17.9 396.9 14.15 20
49 0.22927 0 6.91 0 0.448 6.03 85.5 5.6894 3 233 17.9 392.74 18.8 16.6
50 0.25387 0 6.91 0 0.448 5.399 95.3 5.87 3 233 17.9 396.9 30.81 14.4
51 0.21977 0 6.91 0 0.448 5.602 62 6.0877 3 233 17.9 396.9 16.2 19.4
52 0.08873 21 5.64 0 0.439 5.963 45.7 6.8147 4 243 16.8 395.56 13.45 19.7
53 0.04337 21 5.64 0 0.439 6.115 63 6.8147 4 243 16.8 393.97 9.43 20.5
54 0.0536 21 5.64 0 0.439 6.511 21.1 6.8147 4 243 16.8 396.9 5.28 25
55 0.04981 21 5.64 0 0.439 5.998 21.4 6.8147 4 243 16.8 396.9 8.43 23.4
56 0.0136 75 4 0 0.41 5.888 47.6 7.3197 3 469 21.1 396.9 14.8 18.9
57 0.01311 90 1.22 0 0.403 7.249 21.9 8.6966 5 226 17.9 395.93 4.81 35.4
58 0.02055 85 0.74 0 0.41 6.383 35.7 9.1876 2 313 17.3 396.9 5.77 24.7
59 0.01432 100 1.32 0 0.411 6.816 40.5 8.3248 5 256 15.1 392.9 3.95 31.6
60 0.15445 25 5.13 0 0.453 6.145 29.2 7.8148 8 284 19.7 390.68 6.86 23.3
61 0.10328 25 5.13 0 0.453 5.927 47.2 6.932 8 284 19.7 396.9 9.22 19.6
62 0.14932 25 5.13 0 0.453 5.741 66.2 7.2254 8 284 19.7 395.11 13.15 18.7
63 0.17171 25 5.13 0 0.453 5.966 93.4 6.8185 8 284 19.7 378.08 14.44 16
64 0.11027 25 5.13 0 0.453 6.456 67.8 7.2255 8 284 19.7 396.9 6.73 22.2
65 0.1265 25 5.13 0 0.453 43.4 7.9809 8 284 19.7 395.58 9.5 25
66 0.01951 17.5 1.38 0 0.4161 7.104 59.5 9.2229 3 216 18.6 393.24 8.05 33
67 0.03584 80 3.37 0 0.398 6.29 17.8 6.6115 4 337 16.1 396.9 4.67 23.5
68 0.04379 80 3.37 0 0.398 5.787 31.1 6.6115 4 337 16.1 396.9 10.24 19.4
69 0.05789 12.5 6.07 0 0.409 5.878 21.4 6.498 4 345 18.9 396.21 8.1 22
70 0.13554 12.5 6.07 0 0.409 5.594 36.8 6.498 4 345 18.9 396.9 13.09 17.4
71 0.12816 12.5 6.07 0 0.409 5.885 33 6.498 4 345 18.9 396.9 8.79 20.9
72 0.08826 0 10.81 0 0.413 6.417 6.6 5.2873 4 305 19.2 383.73 6.72 24.2
73 0.15876 0 10.81 0 0.413 5.961 17.5 5.2873 4 305 19.2 376.94 9.88 21.7
74 0.09164 0 10.81 0 0.413 6.065 7.8 5.2873 4 305 19.2 390.91 5.52 22.8
75 0.19539 0 10.81 0 0.413 6.245 6.2 5.2873 4 305 19.2 377.17 7.54 23.4
76 0.07896 0 12.83 0 0.437 6.273 6 4.2515 5 398 18.7 394.92 6.78 24.1
77 0.09512 0 12.83 0 0.437 6.286 45 4.5026 5 398 18.7 383.23 8.94 21.4
78 0.10153 0 12.83 0 0.437 6.279 74.5 4.0522 5 398 18.7 373.66 11.97 20
79 0.08707 0 12.83 0 0.437 6.14 45.8 4.0905 5 398 18.7 386.96 10.27 20.8
80 0.05646 0 12.83 0 0.437 6.232 53.7 5.0141 5 398 18.7 386.4 12.34 21.2
81 0.08387 0 12.83 0 0.437 5.874 36.6 4.5026 5 398 18.7 396.06 9.1 20.3
82 0.04113 25 4.86 0 0.426 6.727 33.5 5.4007 4 281 19 396.9 5.29 28
83 0.04462 25 4.86 0 0.426 6.619 70.4 5.4007 4 281 19 395.63 7.22 23.9
84 0.03659 25 4.86 0 0.426 6.302 32.2 5.4007 4 281 19 396.9 6.72 24.8
85 0.03551 25 4.86 0 0.426 6.167 46.7 5.4007 4 281 19 390.64 7.51 22.9
86 0.05059 0 4.49 0 0.449 6.389 48 4.7794 3 247 18.5 396.9 9.62 23.9
87 0.05735 0 4.49 0 0.449 6.63 56.1 4.4377 3 247 18.5 392.3 6.53 26.6
88 0.05188 0 4.49 0 0.449 6.015 45.1 4.4272 3 247 18.5 395.99 12.86 22.5
89 0.07151 0 4.49 0 0.449 6.121 56.8 3.7476 3 247 18.5 395.15 8.44 22.2
90 0.0566 0 3.41 0 0.489 7.007 86.3 3.4217 2 270 17.8 396.9 5.5 23.6
91 0.05302 0 3.41 0 0.489 7.079 63.1 3.4145 2 270 17.8 396.06 5.7 28.7
92 0.04684 0 3.41 0 0.489 6.417 66.1 3.0923 2 270 17.8 392.18 8.81 22.6
93 0.03932 0 3.41 0 0.489 6.405 73.9 3.0921 2 270 17.8 393.55 8.2 22
94 0.04203 28 15.04 0 0.464 6.442 53.6 3.6659 4 270 18.2 395.01 8.16 22.9
95 0.02875 28 15.04 0 0.464 6.211 28.9 3.6659 4 270 18.2 396.33 6.21 25
96 0.04294 28 15.04 0 0.464 6.249 77.3 3.615 4 270 18.2 396.9 10.59 20.6
97 0.12204 0 2.89 0 0.445 6.625 57.8 3.4952 2 276 18 357.98 6.65 28.4
98 0.11504 0 2.89 0 0.445 69.6 3.4952 2 276 18 391.83 11.34 21.4
99 0.12083 0 2.89 0 0.445 8.069 76 3.4952 2 276 18 396.9 4.21 38.7
100 0.08187 0 2.89 0 0.445 7.82 36.9 3.4952 2 276 18 393.53 3.57 43.8
101 0.0686 0 2.89 0 0.445 7.416 62.5 3.4952 2 276 18 396.9 6.19 33.2
102 0.14866 0 8.56 0 0.52 6.727 79.9 2.7778 5 384 20.9 394.76 9.42 27.5
103 0.11432 0 8.56 0 0.52 6.781 71.3 2.8561 5 384 20.9 395.58 7.67 26.5
104 0.22876 0 8.56 0 0.52 6.405 85.4 2.7147 5 384 20.9 70.8 10.63 18.6
105 0.21161 0 8.56 0 0.52 6.137 87.4 2.7147 5 384 20.9 394.47 13.44 19.3
106 0.1396 0 8.56 0 0.52 6.167 90 2.421 5 384 20.9 392.69 12.33 20.1
107 0.13262 0 8.56 0 0.52 5.851 96.7 2.1069 5 384 20.9 394.05 16.47 19.5
108 0.1712 0 8.56 0 0.52 5.836 91.9 2.211 5 384 20.9 395.67 18.66 19.5
109 0.13117 0 8.56 0 0.52 6.127 85.2 2.1224 5 384 20.9 387.69 14.09 20.4
110 0.12802 0 8.56 0 0.52 6.474 97.1 2.4329 5 384 20.9 395.24 12.27 19.8
111 0.26363 0 8.56 0 0.52 6.229 91.2 2.5451 5 384 20.9 391.23 15.55 19.4
112 0.10793 0 8.56 0 0.52 6.195 54.4 2.7778 5 384 20.9 393.49 13 21.7
113 0.10084 0 10.01 0 0.547 6.715 81.6 2.6775 6 432 17.8 395.59 10.16 22.8
114 0.12329 0 10.01 0 0.547 5.913 92.9 2.3534 6 432 17.8 394.95 16.21 18.8
115 0.22212 0 10.01 0 0.547 6.092 95.4 2.548 6 432 17.8 396.9 17.09 18.7
116 0.14231 0 10.01 0 0.547 6.254 84.2 2.2565 6 432 17.8 388.74 10.45 18.5
117 0.17134 0 10.01 0 0.547 5.928 88.2 2.4631 6 432 17.8 344.91 15.76 18.3
118 0.13158 0 10.01 0 0.547 6.176 72.5 2.7301 6 432 17.8 393.3 12.04 21.2
119 0.15098 0 10.01 0 0.547 6.021 82.6 2.7474 6 432 17.8 394.51 10.3 19.2
120 0.13058 0 10.01 0 0.547 5.872 73.1 2.4775 6 432 17.8 338.63 15.37 20.4
121 0.14476 0 10.01 0 0.547 5.731 65.2 2.7592 6 432 17.8 391.5 13.61 19.3
122 0.06899 0 25.65 0 0.581 5.87 69.7 2.2577 2 188 19.1 389.15 14.37 22
123 0.07165 0 25.65 0 0.581 6.004 84.1 2.1974 2 188 19.1 377.67 14.27 20.3
124 0.09299 0 25.65 0 0.581 5.961 92.9 2.0869 2 188 19.1 378.09 17.93 20.5
125 0.15038 0 25.65 0 0.581 5.856 97 1.9444 2 188 19.1 370.31 25.41 17.3
126 0.09849 0 25.65 0 0.581 5.879 95.8 2.0063 2 188 19.1 379.38 17.58 18.8
127 0.16902 0 25.65 0 0.581 5.986 88.4 1.9929 2 188 19.1 385.02 14.81 21.4
128 0.38735 0 25.65 0 0.581 5.613 95.6 1.7572 2 188 19.1 359.29 27.26 15.7
129 0.25915 0 21.89 0 0.624 5.693 96 1.7883 4 437 21.2 392.11 17.19 16.2
130 0.32543 0 21.89 0 0.624 6.431 98.8 1.8125 4 437 21.2 396.9 15.39 18
131 0.88125 0 21.89 0 0.624 5.637 94.7 1.9799 4 437 21.2 396.9 18.34 14.3
132 0.34006 0 21.89 0 0.624 6.458 98.9 2.1185 4 437 21.2 395.04 12.6 19.2
133 1.19294 0 21.89 0 0.624 6.326 97.7 2.271 4 437 21.2 396.9 12.26 19.6
134 0.59005 0 21.89 0 0.624 6.372 97.9 2.3274 4 437 21.2 385.76 11.12 23
135 0.32982 0 21.89 0 0.624 5.822 95.4 2.4699 4 437 21.2 388.69 15.03 18.4
136 0.97617 0 21.89 0 0.624 5.757 98.4 2.346 4 437 21.2 262.76 17.31 15.6
137 0.55778 0 21.89 0 0.624 98.2 2.1107 4 437 21.2 394.67 16.96 18.1
138 0.32264 0 21.89 0 0.624 5.942 93.5 1.9669 4 437 21.2 378.25 16.9 17.4
139 0.35233 0 21.89 0 0.624 6.454 98.4 1.8498 4 437 21.2 394.08 14.59 17.1
140 0.2498 0 21.89 0 0.624 5.857 98.2 1.6686 4 437 21.2 392.04 21.32 13.3
141 0.54452 0 21.89 0 0.624 6.151 97.9 1.6687 4 437 21.2 396.9 18.46 17.8
142 0.2909 0 21.89 0 0.624 6.174 93.6 1.6119 4 437 21.2 388.08 24.16 14
143 1.62864 0 21.89 0 0.624 5.019 100 1.4394 4 437 21.2 396.9 34.41 14.4
144 3.32105 0 19.58 1 0.871 5.403 100 1.3216 5 403 14.7 396.9 26.82 13.4
145 4.0974 0 19.58 0 0.871 5.468 100 1.4118 5 403 14.7 396.9 26.42 15.6
146 2.77974 0 19.58 0 0.871 4.903 97.8 1.3459 5 403 14.7 396.9 29.29 11.8
147 2.37934 0 19.58 0 0.871 6.13 100 1.4191 5 403 14.7 172.91 27.8 13.8
148 2.15505 0 19.58 0 0.871 5.628 100 1.5166 5 403 14.7 169.27 16.65 15.6
149 2.36862 0 19.58 0 0.871 4.926 95.7 1.4608 5 403 14.7 391.71 29.53 14.6
150 2.33099 0 19.58 0 0.871 5.186 93.8 1.5296 5 403 14.7 356.99 28.32 17.8
151 2.73397 0 19.58 0 0.871 5.597 94.9 1.5257 5 403 14.7 351.85 21.45 15.4
152 1.6566 0 19.58 0 0.871 6.122 97.3 1.618 5 403 14.7 372.8 14.1 21.5
153 1.49632 0 19.58 0 0.871 5.404 100 1.5916 5 403 14.7 341.6 13.28 19.6
154 1.12658 0 19.58 1 0.871 5.012 88 1.6102 5 403 14.7 343.28 12.12 15.3
155 2.14918 0 19.58 0 0.871 5.709 98.5 1.6232 5 403 14.7 261.95 15.79 19.4
156 1.41385 0 19.58 1 0.871 6.129 96 1.7494 5 403 14.7 321.02 15.12 17
157 3.53501 0 19.58 1 0.871 6.152 82.6 1.7455 5 403 14.7 88.01 15.02 15.6
158 2.44668 0 19.58 0 0.871 5.272 94 1.7364 5 403 14.7 88.63 16.14 13.1
159 1.22358 0 19.58 0 0.605 6.943 97.4 1.8773 5 403 14.7 363.43 4.59 41.3
160 1.34284 0 19.58 0 0.605 6.066 100 1.7573 5 403 14.7 353.89 6.43 24.3
161 1.42502 0 19.58 0 0.871 6.51 100 1.7659 5 403 14.7 364.31 7.39 23.3
162 1.27346 0 19.58 1 0.605 6.25 92.6 1.7984 5 403 14.7 338.92 5.5 27
163 1.46336 0 19.58 0 0.605 7.489 90.8 1.9709 5 403 14.7 374.43 1.73 50
164 1.83377 0 19.58 1 0.605 7.802 98.2 2.0407 5 403 14.7 389.61 1.92 50
165 1.51902 0 19.58 1 0.605 8.375 93.9 2.162 5 403 14.7 388.45 3.32 50
166 2.24236 0 19.58 0 0.605 5.854 91.8 2.422 5 403 14.7 395.11 11.64 22.7
167 2.924 0 19.58 0 0.605 6.101 93 2.2834 5 403 14.7 240.16 9.81 25
168 2.01019 0 19.58 0 0.605 7.929 96.2 2.0459 5 403 14.7 369.3 3.7 50
169 1.80028 0 19.58 0 0.605 5.877 79.2 2.4259 5 403 14.7 227.61 12.14 23.8
170 2.3004 0 19.58 0 0.605 6.319 96.1 2.1 5 403 14.7 297.09 11.1 23.8
171 2.44953 0 19.58 0 0.605 6.402 95.2 2.2625 5 403 14.7 330.04 11.32 22.3
172 1.20742 0 19.58 0 0.605 5.875 94.6 2.4259 5 403 14.7 292.29 14.43 17.4
173 2.3139 0 19.58 0 0.605 5.88 97.3 2.3887 5 403 14.7 348.13 12.03 19.1
174 0.13914 0 4.05 0 0.51 5.572 88.5 2.5961 5 296 16.6 396.9 14.69 23.1
175 0.09178 0 4.05 0 0.51 6.416 84.1 2.6463 5 296 16.6 395.5 9.04 23.6
176 0.08447 0 4.05 0 0.51 5.859 68.7 2.7019 5 296 16.6 393.23 9.64 22.6
177 0.06664 0 4.05 0 0.51 6.546 33.1 3.1323 5 296 16.6 390.96 5.33 29.4
178 0.07022 0 4.05 0 0.51 6.02 47.2 3.5549 5 296 16.6 393.23 10.11 23.2
179 0.05425 0 4.05 0 0.51 6.315 73.4 3.3175 5 296 16.6 395.6 6.29 24.6
180 0.06642 0 4.05 0 0.51 6.86 74.4 2.9153 5 296 16.6 391.27 6.92 29.9
181 0.0578 0 2.46 0 0.488 6.98 58.4 2.829 3 193 17.8 396.9 5.04 37.2
182 0.06588 0 2.46 0 0.488 7.765 83.3 2.741 3 193 17.8 395.56 7.56 39.8
183 0.06888 0 2.46 0 0.488 6.144 62.2 2.5979 3 193 17.8 396.9 9.45 36.2
184 0.09103 0 2.46 0 0.488 7.155 92.2 2.7006 3 193 17.8 394.12 4.82 37.9
185 0.10008 0 2.46 0 0.488 6.563 95.6 2.847 3 193 17.8 396.9 5.68 32.5
186 0.08308 0 2.46 0 0.488 5.604 89.8 2.9879 3 193 17.8 391 13.98 26.4
187 0.06047 0 2.46 0 0.488 6.153 68.8 3.2797 3 193 17.8 387.11 13.15 29.6
188 0.05602 0 2.46 0 0.488 7.831 53.6 3.1992 3 193 17.8 392.63 4.45 50
189 0.07875 45 3.44 0 0.437 6.782 41.1 3.7886 5 398 15.2 393.87 6.68 32
190 0.12579 45 3.44 0 0.437 6.556 29.1 4.5667 5 398 15.2 382.84 4.56 29.8
191 0.0837 45 3.44 0 0.437 7.185 38.9 4.5667 5 398 15.2 396.9 5.39 34.9
192 0.09068 45 3.44 0 0.437 6.951 21.5 6.4798 5 398 15.2 377.68 5.1 37
193 0.06911 45 3.44 0 0.437 6.739 30.8 6.4798 5 398 15.2 389.71 4.69 30.5
194 0.08664 45 3.44 0 0.437 7.178 26.3 6.4798 5 398 15.2 390.49 2.87 36.4
195 0.02187 60 2.93 0 0.401 6.8 9.9 6.2196 1 265 15.6 393.37 5.03 31.1
196 0.01439 60 2.93 0 0.401 6.604 18.8 6.2196 1 265 15.6 376.7 4.38 29.1
197 0.01381 80 0.46 0 0.422 7.875 32 5.6484 4 255 14.4 394.23 2.97 50
198 0.04011 80 1.52 0 0.404 7.287 34.1 7.309 2 329 12.6 396.9 4.08 33.3
199 0.04666 80 1.52 0 0.404 7.107 36.6 7.309 2 329 12.6 354.31 8.61 30.3
200 0.03768 80 1.52 0 0.404 7.274 38.3 7.309 2 329 12.6 392.2 6.62 34.6
201 0.0315 95 1.47 0 0.403 6.975 15.3 7.6534 3 402 17 396.9 4.56 34.9
202 0.01778 95 1.47 0 0.403 7.135 13.9 7.6534 3 402 17 384.3 4.45 32.9
203 0.03445 82.5 2.03 0 0.415 6.162 38.4 6.27 2 348 14.7 393.77 7.43 24.1
204 0.02177 82.5 2.03 0 0.415 7.61 15.7 6.27 2 348 14.7 395.38 3.11 42.3
205 0.0351 95 2.68 0 0.4161 7.853 33.2 5.118 4 224 14.7 392.78 3.81 48.5
206 0.02009 95 2.68 0 0.4161 8.034 31.9 5.118 4 224 14.7 390.55 2.88 50
207 0.13642 0 10.59 0 0.489 5.891 22.3 3.9454 4 277 18.6 396.9 10.87 22.6
208 0.22969 0 10.59 0 0.489 6.326 52.5 4.3549 4 277 18.6 394.87 10.97 24.4
209 0.25199 0 10.59 0 0.489 5.783 72.7 4.3549 4 277 18.6 389.43 18.06 22.5
210 0.13587 0 10.59 1 0.489 6.064 59.1 4.2392 4 277 18.6 381.32 14.66 24.4
211 0.43571 0 10.59 1 0.489 5.344 100 3.875 4 277 18.6 396.9 23.09 20
212 0.17446 0 10.59 1 0.489 5.96 92.1 3.8771 4 277 18.6 393.25 17.27 21.7
213 0.37578 0 10.59 1 0.489 5.404 88.6 3.665 4 277 18.6 395.24 23.98 19.3
214 0.21719 0 10.59 1 0.489 5.807 53.8 3.6526 4 277 18.6 390.94 16.03 22.4
215 0.14052 0 10.59 0 0.489 6.375 32.3 3.9454 4 277 18.6 385.81 9.38 28.1
216 0.28955 0 10.59 0 0.489 5.412 9.8 3.5875 4 277 18.6 348.93 29.55 23.7
217 0.19802 0 10.59 0 0.489 6.182 42.4 3.9454 4 277 18.6 393.63 9.47 25
218 0.0456 0 13.89 1 0.55 5.888 56 3.1121 5 276 16.4 392.8 13.51 23.3
219 0.07013 0 13.89 0 0.55 6.642 85.1 3.4211 5 276 16.4 392.78 9.69 28.7
220 0.11069 0 13.89 1 0.55 5.951 93.8 2.8893 5 276 16.4 396.9 17.92 21.5
221 0.11425 0 13.89 1 0.55 6.373 92.4 3.3633 5 276 16.4 393.74 10.5 23
222 0.35809 0 6.2 1 0.507 6.951 88.5 2.8617 8 307 17.4 391.7 9.71 26.7
223 0.40771 0 6.2 1 0.507 6.164 91.3 3.048 8 307 17.4 395.24 21.46 21.7
224 0.62356 0 6.2 1 0.507 6.879 77.7 3.2721 8 307 17.4 390.39 9.93 27.5
225 0.6147 0 6.2 0 0.507 6.618 80.8 3.2721 8 307 17.4 396.9 7.6 30.1
226 0.31533 0 6.2 0 0.504 8.266 78.3 2.8944 8 307 17.4 385.05 4.14 44.8
227 0.52693 0 6.2 0 0.504 8.725 83 2.8944 8 307 17.4 382 4.63 50
228 0.38214 0 6.2 0 0.504 8.04 86.5 3.2157 8 307 17.4 387.38 3.13 37.6
229 0.41238 0 6.2 0 0.504 7.163 79.9 3.2157 8 307 17.4 372.08 6.36 31.6
230 0.29819 0 6.2 0 0.504 7.686 17 3.3751 8 307 17.4 377.51 3.92 46.7
231 0.44178 0 6.2 0 0.504 6.552 21.4 3.3751 8 307 17.4 380.34 3.76 31.5
232 0.537 0 6.2 0 0.504 5.981 68.1 3.6715 8 307 17.4 378.35 11.65 24.3
233 0.46296 0 6.2 0 0.504 7.412 76.9 3.6715 8 307 17.4 376.14 5.25 31.7
234 0.57529 0 6.2 0 0.507 8.337 73.3 3.8384 8 307 17.4 385.91 2.47 41.7
235 0.33147 0 6.2 0 0.507 8.247 70.4 3.6519 8 307 17.4 378.95 3.95 48.3
236 0.44791 0 6.2 1 0.507 6.726 66.5 3.6519 8 307 17.4 360.2 8.05 29
237 0.33045 0 6.2 0 0.507 6.086 61.5 3.6519 8 307 17.4 376.75 10.88 24
238 0.52058 0 6.2 1 0.507 6.631 76.5 4.148 8 307 17.4 388.45 9.54 25.1
239 0.51183 0 6.2 0 0.507 7.358 71.6 4.148 8 307 17.4 390.07 4.73 31.5
240 0.08244 30 4.93 0 0.428 6.481 18.5 6.1899 6 300 16.6 379.41 6.36 23.7
241 0.09252 30 4.93 0 0.428 6.606 42.2 6.1899 6 300 16.6 383.78 7.37 23.3
242 0.11329 30 4.93 0 0.428 6.897 54.3 6.3361 6 300 16.6 391.25 11.38 22
243 0.10612 30 4.93 0 0.428 6.095 65.1 6.3361 6 300 16.6 394.62 12.4 20.1
244 0.1029 30 4.93 0 0.428 6.358 52.9 7.0355 6 300 16.6 372.75 11.22 22.2
245 0.12757 30 4.93 0 0.428 6.393 7.8 7.0355 6 300 16.6 374.71 5.19 23.7
246 0.20608 22 5.86 0 0.431 5.593 76.5 7.9549 7 330 19.1 372.49 12.5 17.6
247 0.19133 22 5.86 0 0.431 5.605 70.2 7.9549 7 330 19.1 389.13 18.46 18.5
248 0.33983 22 5.86 0 0.431 6.108 34.9 8.0555 7 330 19.1 390.18 9.16 24.3
249 0.19657 22 5.86 0 0.431 6.226 79.2 8.0555 7 330 19.1 376.14 10.15 20.5
250 0.16439 22 5.86 0 0.431 6.433 49.1 7.8265 7 330 19.1 374.71 9.52 24.5
251 0.19073 22 5.86 0 0.431 6.718 17.5 7.8265 7 330 19.1 393.74 6.56 26.2
252 0.1403 22 5.86 0 0.431 6.487 13 7.3967 7 330 19.1 396.28 5.9 24.4
253 0.21409 22 5.86 0 0.431 6.438 8.9 7.3967 7 330 19.1 377.07 3.59 24.8
254 0.08221 22 5.86 0 0.431 6.957 6.8 8.9067 7 330 19.1 386.09 3.53 29.6
255 0.36894 22 5.86 0 0.431 8.259 8.4 8.9067 7 330 19.1 396.9 3.54 42.8
256 0.04819 80 3.64 0 0.392 6.108 32 9.2203 1 315 16.4 392.89 6.57 21.9
257 0.03548 80 3.64 0 0.392 5.876 19.1 9.2203 1 315 16.4 395.18 9.25 20.9
258 0.01538 90 3.75 0 0.394 7.454 34.2 6.3361 3 244 15.9 386.34 3.11 44
259 0.61154 20 3.97 0 0.647 8.704 86.9 1.801 5 264 13 389.7 5.12 50
260 0.66351 20 3.97 0 0.647 7.333 100 1.8946 5 264 13 383.29 7.79 36
261 0.65665 20 3.97 0 0.647 6.842 100 2.0107 5 264 13 391.93 6.9 30.1
262 0.54011 20 3.97 0 0.647 7.203 81.8 2.1121 5 264 13 392.8 9.59 33.8
263 0.53412 20 3.97 0 0.647 7.52 89.4 2.1398 5 264 13 388.37 7.26 43.1
264 0.52014 20 3.97 0 0.647 8.398 91.5 2.2885 5 264 13 386.86 5.91 48.8
265 0.82526 20 3.97 0 0.647 7.327 94.5 2.0788 5 264 13 393.42 11.25 31
266 0.55007 20 3.97 0 0.647 7.206 91.6 1.9301 5 264 13 387.89 8.1 36.5
267 0.76162 20 3.97 0 0.647 5.56 62.8 1.9865 5 264 13 392.4 10.45 22.8
268 0.7857 20 3.97 0 0.647 7.014 84.6 2.1329 5 264 13 384.07 14.79 30.7
269 0.57834 20 3.97 0 0.575 8.297 67 2.4216 5 264 13 384.54 7.44 50
270 0.5405 20 3.97 0 0.575 7.47 52.6 2.872 5 264 13 390.3 3.16 43.5
271 0.09065 20 6.96 1 0.464 5.92 61.5 3.9175 3 223 18.6 391.34 13.65 20.7
272 0.29916 20 6.96 0 0.464 5.856 42.1 4.429 3 223 18.6 388.65 13 21.1
273 0.16211 20 6.96 0 0.464 6.24 16.3 4.429 3 223 18.6 396.9 6.59 25.2
274 0.1146 20 6.96 0 0.464 6.538 58.7 3.9175 3 223 18.6 394.96 7.73 24.4
275 0.22188 20 6.96 1 0.464 7.691 51.8 4.3665 3 223 18.6 390.77 6.58 35.2
276 0.05644 40 6.41 1 0.447 6.758 32.9 4.0776 4 254 17.6 396.9 3.53 32.4
277 0.09604 40 6.41 0 0.447 6.854 42.8 4.2673 4 254 17.6 396.9 2.98 32
278 0.10469 40 6.41 1 0.447 7.267 49 4.7872 4 254 17.6 389.25 6.05 33.2
279 0.06127 40 6.41 1 0.447 6.826 27.6 4.8628 4 254 17.6 393.45 4.16 33.1
280 0.07978 40 6.41 0 0.447 6.482 32.1 4.1403 4 254 17.6 396.9 7.19 29.1
281 0.21038 20 3.33 0 0.4429 6.812 32.2 4.1007 5 216 14.9 396.9 4.85 35.1
282 0.03578 20 3.33 0 0.4429 7.82 64.5 4.6947 5 216 14.9 387.31 3.76 45.4
283 0.03705 20 3.33 0 0.4429 6.968 37.2 5.2447 5 216 14.9 392.23 4.59 35.4
284 0.06129 20 3.33 1 0.4429 7.645 49.7 5.2119 5 216 14.9 377.07 3.01 46
285 0.01501 90 1.21 1 0.401 7.923 24.8 5.885 1 198 13.6 395.52 3.16 50
286 0.00906 90 2.97 0 0.4 7.088 20.8 7.3073 1 285 15.3 394.72 7.85 32.2
287 0.01096 55 2.25 0 0.389 6.453 31.9 7.3073 1 300 15.3 394.72 8.23 22
288 0.01965 80 1.76 0 0.385 6.23 31.5 9.0892 1 241 18.2 341.6 12.93 20.1
289 0.03871 52.5 5.32 0 0.405 6.209 31.3 7.3172 6 293 16.6 396.9 7.14 23.2
290 0.0459 52.5 5.32 0 0.405 6.315 45.6 7.3172 6 293 16.6 396.9 7.6 22.3
291 0.04297 52.5 5.32 0 0.405 6.565 22.9 7.3172 6 293 16.6 371.72 9.51 24.8
292 0.03502 80 4.95 0 0.411 6.861 27.9 5.1167 4 245 19.2 396.9 3.33 28.5
293 0.07886 80 4.95 0 0.411 7.148 27.7 5.1167 4 245 19.2 396.9 3.56 37.3
294 0.03615 80 4.95 0 0.411 6.63 23.4 5.1167 4 245 19.2 396.9 4.7 27.9
295 0.08265 0 13.92 0 0.437 6.127 18.4 5.5027 4 289 16 396.9 8.58 23.9
296 0.08199 0 13.92 0 0.437 6.009 42.3 5.5027 4 289 16 396.9 10.4 21.7
297 0.12932 0 13.92 0 0.437 6.678 31.1 5.9604 4 289 16 396.9 6.27 28.6
298 0.05372 0 13.92 0 0.437 6.549 51 5.9604 4 289 16 392.85 7.39 27.1
299 0.14103 0 13.92 0 0.437 5.79 58 6.32 4 289 16 396.9 15.84 20.3
300 0.06466 70 2.24 0 0.4 6.345 20.1 7.8278 5 358 14.8 368.24 4.97 22.5
301 0.05561 70 2.24 0 0.4 7.041 10 7.8278 5 358 14.8 371.58 4.74 29
302 0.04417 70 2.24 0 0.4 6.871 47.4 7.8278 5 358 14.8 390.86 6.07 24.8
303 0.03537 34 6.09 0 0.433 6.59 40.4 5.4917 7 329 16.1 395.75 9.5 22
304 0.09266 34 6.09 0 0.433 6.495 18.4 5.4917 7 329 16.1 383.61 8.67 26.4
305 0.1 34 6.09 0 0.433 6.982 17.7 5.4917 7 329 16.1 390.43 4.86 33.1
306 0.05515 33 2.18 0 0.472 7.236 41.1 4.022 7 222 18.4 393.68 6.93 36.1
307 0.05479 33 2.18 0 0.472 6.616 58.1 3.37 7 222 18.4 393.36 8.93 28.4
308 0.07503 33 2.18 0 0.472 7.42 71.9 3.0992 7 222 18.4 396.9 6.47 33.4
309 0.04932 33 2.18 0 0.472 6.849 70.3 3.1827 7 222 18.4 396.9 7.53 28.2
310 0.49298 0 9.9 0 0.544 6.635 82.5 3.3175 4 304 18.4 396.9 4.54 22.8
311 0.3494 0 9.9 0 0.544 5.972 76.7 3.1025 4 304 18.4 396.24 9.97 20.3
312 2.63548 0 9.9 0 0.544 4.973 37.8 2.5194 4 304 18.4 350.45 12.64 16.1
313 0.79041 0 9.9 0 0.544 6.122 52.8 2.6403 4 304 18.4 396.9 5.98 22.1
314 0.26169 0 9.9 0 0.544 6.023 90.4 2.834 4 304 18.4 396.3 11.72 19.4
315 0.26938 0 9.9 0 0.544 6.266 82.8 3.2628 4 304 18.4 393.39 7.9 21.6
316 0.3692 0 9.9 0 0.544 6.567 87.3 3.6023 4 304 18.4 395.69 9.28 23.8
317 0.25356 0 9.9 0 0.544 5.705 77.7 3.945 4 304 18.4 396.42 11.5 16.2
318 0.31827 0 9.9 0 0.544 5.914 83.2 3.9986 4 304 18.4 390.7 18.33 17.8
319 0.24522 0 9.9 0 0.544 5.782 71.7 4.0317 4 304 18.4 396.9 15.94 19.8
320 0.40202 0 9.9 0 0.544 6.382 67.2 3.5325 4 304 18.4 395.21 10.36 23.1
321 0.47547 0 9.9 0 0.544 6.113 58.8 4.0019 4 304 18.4 396.23 12.73 21
322 0.1676 0 7.38 0 0.493 6.426 52.3 4.5404 5 287 19.6 396.9 7.2 23.8
323 0.18159 0 7.38 0 0.493 6.376 54.3 4.5404 5 287 19.6 396.9 6.87 23.1
324 0.35114 0 7.38 0 0.493 6.041 49.9 4.7211 5 287 19.6 396.9 7.7 20.4
325 0.28392 0 7.38 0 0.493 5.708 74.3 4.7211 5 287 19.6 391.13 11.74 18.5
326 0.34109 0 7.38 0 0.493 6.415 40.1 4.7211 5 287 19.6 396.9 6.12 25
327 0.19186 0 7.38 0 0.493 6.431 14.7 5.4159 5 287 19.6 393.68 5.08 24.6
328 0.30347 0 7.38 0 0.493 6.312 28.9 5.4159 5 287 19.6 396.9 6.15 23
329 0.24103 0 7.38 0 0.493 6.083 43.7 5.4159 5 287 19.6 396.9 12.79 22.2
330 0.06617 0 3.24 0 0.46 5.868 25.8 5.2146 4 430 16.9 382.44 9.97 19.3
331 0.06724 0 3.24 0 0.46 6.333 17.2 5.2146 4 430 16.9 375.21 7.34 22.6
332 0.04544 0 3.24 0 0.46 6.144 32.2 5.8736 4 430 16.9 368.57 9.09 19.8
333 0.05023 35 6.06 0 0.4379 5.706 28.4 6.6407 1 304 16.9 394.02 12.43 17.1
334 0.03466 35 6.06 0 0.4379 6.031 23.3 6.6407 1 304 16.9 362.25 7.83 19.4
335 0.05083 0 5.19 0 0.515 6.316 38.1 6.4584 5 224 20.2 389.71 5.68 22.2
336 0.03738 0 5.19 0 0.515 6.31 38.5 6.4584 5 224 20.2 389.4 6.75 20.7
337 0.03961 0 5.19 0 0.515 6.037 34.5 5.9853 5 224 20.2 396.9 8.01 21.1
338 0.03427 0 5.19 0 0.515 5.869 46.3 5.2311 5 224 20.2 396.9 9.8 19.5
339 0.03041 0 5.19 0 0.515 5.895 59.6 5.615 5 224 20.2 394.81 10.56 18.5
340 0.03306 0 5.19 0 0.515 6.059 37.3 4.8122 5 224 20.2 396.14 8.51 20.6
341 0.05497 0 5.19 0 0.515 5.985 45.4 4.8122 5 224 20.2 396.9 9.74 19
342 0.06151 0 5.19 0 0.515 5.968 58.5 4.8122 5 224 20.2 396.9 9.29 18.7
343 0.01301 35 1.52 0 0.442 7.241 49.3 7.0379 1 284 15.5 394.74 5.49 32.7
344 0.02498 0 1.89 0 0.518 6.54 59.7 6.2669 1 422 15.9 389.96 8.65 16.5
345 0.02543 55 3.78 0 0.484 6.696 56.4 5.7321 5 370 17.6 396.9 7.18 23.9
346 0.03049 55 3.78 0 0.484 6.874 28.1 6.4654 5 370 17.6 387.97 4.61 31.2
347 0.03113 0 4.39 0 0.442 6.014 48.5 8.0136 3 352 18.8 385.64 10.53 17.5
348 0.06162 0 4.39 0 0.442 5.898 52.3 8.0136 3 352 18.8 364.61 12.67 17.2
349 0.0187 85 4.15 0 0.429 6.516 27.7 8.5353 4 351 17.9 392.43 6.36 23.1
350 0.01501 80 2.01 0 0.435 6.635 29.7 8.344 4 280 17 390.94 5.99 24.5
351 0.02899 40 1.25 0 0.429 6.939 34.5 8.7921 1 335 19.7 389.85 5.89 26.6
352 0.06211 40 1.25 0 0.429 6.49 44.4 8.7921 1 335 19.7 396.9 5.98 22.9
353 0.0795 60 1.69 0 0.411 6.579 35.9 10.7103 4 411 18.3 370.78 5.49 24.1
354 0.07244 60 1.69 0 0.411 5.884 18.5 10.7103 4 411 18.3 392.33 7.79 18.6
355 0.01709 90 2.02 0 0.41 6.728 36.1 12.1265 5 187 17 384.46 4.5 30.1
356 0.04301 80 1.91 0 0.413 5.663 21.9 10.5857 4 334 22 382.8 8.05 18.2
357 0.10659 80 1.91 0 0.413 5.936 19.5 10.5857 4 334 22 376.04 5.57 20.6
358 8.98296 0 18.1 1 0.77 6.212 97.4 2.1222 24 666 20.2 377.73 17.6 17.8
359 3.8497 0 18.1 1 0.77 6.395 91 2.5052 24 666 20.2 391.34 13.27 21.7
360 5.20177 0 18.1 1 0.77 6.127 83.4 2.7227 24 666 20.2 395.43 11.48 22.7
361 4.26131 0 18.1 0 0.77 6.112 81.3 2.5091 24 666 20.2 390.74 12.67 22.6
362 4.54192 0 18.1 0 0.77 6.398 88 2.5182 24 666 20.2 374.56 7.79 25
363 3.83684 0 18.1 0 0.77 6.251 91.1 2.2955 24 666 20.2 350.65 14.19 19.9
364 3.67822 0 18.1 0 0.77 5.362 96.2 2.1036 24 666 20.2 380.79 10.19 20.8
365 4.22239 0 18.1 1 0.77 5.803 89 1.9047 24 666 20.2 353.04 14.64 16.8
366 3.47428 0 18.1 1 0.718 8.78 82.9 1.9047 24 666 20.2 354.55 5.29 21.9
367 4.55587 0 18.1 0 0.718 3.561 87.9 1.6132 24 666 20.2 354.7 7.12 27.5
368 3.69695 0 18.1 0 0.718 4.963 91.4 1.7523 24 666 20.2 316.03 14 21.9
369 13.5222 0 18.1 0 0.631 3.863 100 1.5106 24 666 20.2 131.42 13.33 23.1
370 4.89822 0 18.1 0 0.631 4.97 100 1.3325 24 666 20.2 375.52 3.26 50
371 5.66998 0 18.1 1 0.631 6.683 96.8 1.3567 24 666 20.2 375.33 3.73 50
372 6.53876 0 18.1 1 0.631 7.016 97.5 1.2024 24 666 20.2 392.05 2.96 50
373 9.2323 0 18.1 0 0.631 6.216 100 1.1691 24 666 20.2 366.15 9.53 50
374 8.26725 0 18.1 1 0.668 5.875 89.6 1.1296 24 666 20.2 347.88 8.88 50
375 11.1081 0 18.1 0 0.668 4.906 100 1.1742 24 666 20.2 396.9 34.77 13.8
376 18.4982 0 18.1 0 0.668 4.138 100 1.137 24 666 20.2 396.9 37.97 13.8
377 19.6091 0 18.1 0 0.671 7.313 97.9 1.3163 24 666 20.2 396.9 13.44 15
378 15.288 0 18.1 0 0.671 6.649 93.3 1.3449 24 666 20.2 363.02 23.24 13.9
379 9.82349 0 18.1 0 0.671 6.794 98.8 1.358 24 666 20.2 396.9 21.24 13.3
380 23.6482 0 18.1 0 0.671 6.38 96.2 1.3861 24 666 20.2 396.9 23.69 13.1
381 17.8667 0 18.1 0 0.671 6.223 100 1.3861 24 666 20.2 393.74 21.78 10.2
382 88.9762 0 18.1 0 0.671 6.968 91.9 1.4165 24 666 20.2 396.9 17.21 10.4
383 15.8744 0 18.1 0 0.671 6.545 99.1 1.5192 24 666 20.2 396.9 21.08 10.9
384 9.18702 0 18.1 0 0.7 5.536 100 1.5804 24 666 20.2 396.9 23.6 11.3
385 7.99248 0 18.1 0 0.7 5.52 100 1.5331 24 666 20.2 396.9 24.56 12.3
386 20.0849 0 18.1 0 0.7 4.368 91.2 1.4395 24 666 20.2 285.83 30.63 8.8
387 16.8118 0 18.1 0 0.7 5.277 98.1 1.4261 24 666 20.2 396.9 30.81 7.2
388 24.3938 0 18.1 0 0.7 4.652 100 1.4672 24 666 20.2 396.9 28.28 10.5
389 22.5971 0 18.1 0 0.7 5 89.5 1.5184 24 666 20.2 396.9 31.99 7.4
390 14.3337 0 18.1 0 0.7 4.88 100 1.5895 24 666 20.2 372.92 30.62 10.2
391 8.15174 0 18.1 0 0.7 5.39 98.9 1.7281 24 666 20.2 396.9 20.85 11.5
392 6.96215 0 18.1 0 0.7 5.713 97 1.9265 24 666 20.2 394.43 17.11 15.1
393 5.29305 0 18.1 0 0.7 6.051 82.5 2.1678 24 666 20.2 378.38 18.76 23.2
394 11.5779 0 18.1 0 0.7 5.036 97 1.77 24 666 20.2 396.9 25.68 9.7
395 8.64476 0 18.1 0 0.693 6.193 92.6 1.7912 24 666 20.2 396.9 15.17 13.8
396 13.3598 0 18.1 0 0.693 5.887 94.7 1.7821 24 666 20.2 396.9 16.35 12.7
397 8.71675 0 18.1 0 0.693 6.471 98.8 1.7257 24 666 20.2 391.98 17.12 13.1
398 5.87205 0 18.1 0 0.693 6.405 96 1.6768 24 666 20.2 396.9 19.37 12.5
399 7.67202 0 18.1 0 0.693 5.747 98.9 1.6334 24 666 20.2 393.1 19.92 8.5
400 38.3518 0 18.1 0 0.693 5.453 100 1.4896 24 666 20.2 396.9 30.59 5
401 9.91655 0 18.1 0 0.693 5.852 77.8 1.5004 24 666 20.2 338.16 29.97 6.3
402 25.0461 0 18.1 0 0.693 5.987 100 1.5888 24 666 20.2 396.9 26.77 5.6
403 14.2362 0 18.1 0 0.693 6.343 100 1.5741 24 666 20.2 396.9 20.32 7.2
404 9.59571 0 18.1 0 0.693 6.404 100 1.639 24 666 20.2 376.11 20.31 12.1
405 24.8017 0 18.1 0 0.693 5.349 96 1.7028 24 666 20.2 396.9 19.77 8.3
406 41.5292 0 18.1 0 0.693 5.531 85.4 1.6074 24 666 20.2 329.46 27.38 8.5
407 67.9208 0 18.1 0 0.693 5.683 100 1.4254 24 666 20.2 384.97 22.98 5
408 20.7162 0 18.1 0 0.659 4.138 100 1.1781 24 666 20.2 370.22 23.34 11.9
409 11.9511 0 18.1 0 0.659 5.608 100 1.2852 24 666 20.2 332.09 12.13 27.9
410 7.40389 0 18.1 0 0.597 5.617 97.9 1.4547 24 666 20.2 314.64 26.4 17.2
411 14.4383 0 18.1 0 0.597 6.852 100 1.4655 24 666 20.2 179.36 19.78 27.5
412 51.1358 0 18.1 0 0.597 5.757 100 1.413 24 666 20.2 2.6 10.11 15
413 14.0507 0 18.1 0 0.597 6.657 100 1.5275 24 666 20.2 35.05 21.22 17.2
414 18.811 0 18.1 0 0.597 4.628 100 1.5539 24 666 20.2 28.79 34.37 17.9
415 28.6558 0 18.1 0 0.597 5.155 100 1.5894 24 666 20.2 210.97 20.08 16.3
416 45.7461 0 18.1 0 0.693 4.519 100 1.6582 24 666 20.2 88.27 36.98 7
417 18.0846 0 18.1 0 0.679 6.434 100 1.8347 24 666 20.2 27.25 29.05 7.2
418 10.8342 0 18.1 0 0.679 6.782 90.8 1.8195 24 666 20.2 21.57 25.79 7.5
419 25.9406 0 18.1 0 0.679 5.304 89.1 1.6475 24 666 20.2 127.36 26.64 10.4
420 73.5341 0 18.1 0 0.679 5.957 100 1.8026 24 666 20.2 16.45 20.62 8.8
421 11.8123 0 18.1 0 0.718 6.824 76.5 1.794 24 666 20.2 48.45 22.74 8.4
422 11.0874 0 18.1 0 0.718 6.411 100 1.8589 24 666 20.2 318.75 15.02 16.7
423 7.02259 0 18.1 0 0.718 6.006 95.3 1.8746 24 666 20.2 319.98 15.7 14.2
424 12.0482 0 18.1 0 0.614 5.648 87.6 1.9512 24 666 20.2 291.55 14.1 20.8
425 7.05042 0 18.1 0 0.614 6.103 85.1 2.0218 24 666 20.2 2.52 23.29 13.4
426 8.79212 0 18.1 0 0.584 5.565 70.6 2.0635 24 666 20.2 3.65 17.16 11.7
427 15.8603 0 18.1 0 0.679 5.896 95.4 1.9096 24 666 20.2 7.68 24.39 8.3
428 12.2472 0 18.1 0 0.584 5.837 59.7 1.9976 24 666 20.2 24.65 15.69 10.2
429 37.6619 0 18.1 0 0.679 6.202 78.7 1.8629 24 666 20.2 18.82 14.52 10.9
430 7.36711 0 18.1 0 0.679 6.193 78.1 1.9356 24 666 20.2 96.73 21.52 11
431 9.33889 0 18.1 0 0.679 6.38 95.6 1.9682 24 666 20.2 60.72 24.08 9.5
432 8.49213 0 18.1 0 0.584 6.348 86.1 2.0527 24 666 20.2 83.45 17.64 14.5
433 10.0623 0 18.1 0 0.584 6.833 94.3 2.0882 24 666 20.2 81.33 19.69 14.1
434 6.44405 0 18.1 0 0.584 6.425 74.8 2.2004 24 666 20.2 97.95 12.03 16.1
435 5.58107 0 18.1 0 0.713 6.436 87.9 2.3158 24 666 20.2 100.19 16.22 14.3
436 13.9134 0 18.1 0 0.713 6.208 95 2.2222 24 666 20.2 100.63 15.17 11.7
437 11.1604 0 18.1 0 0.74 6.629 94.6 2.1247 24 666 20.2 109.85 23.27 13.4
438 14.4208 0 18.1 0 0.74 6.461 93.3 2.0026 24 666 20.2 27.49 18.05 9.6
439 15.1772 0 18.1 0 0.74 6.152 100 1.9142 24 666 20.2 9.32 26.45 8.7
440 13.6781 0 18.1 0 0.74 5.935 87.9 1.8206 24 666 20.2 68.95 34.02 8.4
441 9.39063 0 18.1 0 0.74 5.627 93.9 1.8172 24 666 20.2 396.9 22.88 12.8
442 22.0511 0 18.1 0 0.74 5.818 92.4 1.8662 24 666 20.2 391.45 22.11 10.5
443 9.72418 0 18.1 0 0.74 6.406 97.2 2.0651 24 666 20.2 385.96 19.52 17.1
444 5.66637 0 18.1 0 0.74 6.219 100 2.0048 24 666 20.2 395.69 16.59 18.4
445 9.96654 0 18.1 0 0.74 6.485 100 1.9784 24 666 20.2 386.73 18.85 15.4
446 12.8023 0 18.1 0 0.74 5.854 96.6 1.8956 24 666 20.2 240.52 23.79 10.8
447 10.6718 0 18.1 0 0.74 6.459 94.8 1.9879 24 666 20.2 43.06 23.98 11.8
448 6.28807 0 18.1 0 0.74 6.341 96.4 2.072 24 666 20.2 318.01 17.79 14.9
449 9.92485 0 18.1 0 0.74 6.251 96.6 2.198 24 666 20.2 388.52 16.44 12.6
450 9.32909 0 18.1 0 0.713 6.185 98.7 2.2616 24 666 20.2 396.9 18.13 14.1
451 7.52601 0 18.1 0 0.713 6.417 98.3 2.185 24 666 20.2 304.21 19.31 13
452 6.71772 0 18.1 0 0.713 6.749 92.6 2.3236 24 666 20.2 0.32 17.44 13.4
453 5.44114 0 18.1 0 0.713 6.655 98.2 2.3552 24 666 20.2 355.29 17.73 15.2
454 5.09017 0 18.1 0 0.713 6.297 91.8 2.3682 24 666 20.2 385.09 17.27 16.1
455 8.24809 0 18.1 0 0.713 7.393 99.3 2.4527 24 666 20.2 375.87 16.74 17.8
456 9.51363 0 18.1 0 0.713 6.728 94.1 2.4961 24 666 20.2 6.68 18.71 14.9
457 4.75237 0 18.1 0 0.713 6.525 86.5 2.4358 24 666 20.2 50.92 18.13 14.1
458 4.66883 0 18.1 0 0.713 5.976 87.9 2.5806 24 666 20.2 10.48 19.01 12.7
459 8.20058 0 18.1 0 0.713 5.936 80.3 2.7792 24 666 20.2 3.5 16.94 13.5
460 7.75223 0 18.1 0 0.713 6.301 83.7 2.7831 24 666 20.2 272.21 16.23 14.9
461 6.80117 0 18.1 0 0.713 6.081 84.4 2.7175 24 666 20.2 396.9 14.7 20
462 4.81213 0 18.1 0 0.713 6.701 90 2.5975 24 666 20.2 255.23 16.42 16.4
463 3.69311 0 18.1 0 0.713 6.376 88.4 2.5671 24 666 20.2 391.43 14.65 17.7
464 6.65492 0 18.1 0 0.713 6.317 83 2.7344 24 666 20.2 396.9 13.99 19.5
465 5.82115 0 18.1 0 0.713 6.513 89.9 2.8016 24 666 20.2 393.82 10.29 20.2
466 7.83932 0 18.1 0 0.655 6.209 65.4 2.9634 24 666 20.2 396.9 13.22 21.4
467 3.1636 0 18.1 0 0.655 5.759 48.2 3.0665 24 666 20.2 334.4 14.13 19.9
468 3.77498 0 18.1 0 0.655 5.952 84.7 2.8715 24 666 20.2 22.01 17.15 19
469 4.42228 0 18.1 0 0.584 6.003 94.5 2.5403 24 666 20.2 331.29 21.32 19.1
470 15.5757 0 18.1 0 0.58 5.926 71 2.9084 24 666 20.2 368.74 18.13 19.1
471 13.0751 0 18.1 0 0.58 5.713 56.7 2.8237 24 666 20.2 396.9 14.76 20.1
472 4.34879 0 18.1 0 0.58 6.167 84 3.0334 24 666 20.2 396.9 16.29 19.9
473 4.03841 0 18.1 0 0.532 6.229 90.7 3.0993 24 666 20.2 395.33 12.87 19.6
474 3.56868 0 18.1 0 0.58 6.437 75 2.8965 24 666 20.2 393.37 14.36 23.2
475 4.64689 0 18.1 0 0.614 6.98 67.6 2.5329 24 666 20.2 374.68 11.66 29.8
476 8.05579 0 18.1 0 0.584 5.427 95.4 2.4298 24 666 20.2 352.58 18.14 13.8
477 6.39312 0 18.1 0 0.584 6.162 97.4 2.206 24 666 20.2 302.76 24.1 13.3
478 4.87141 0 18.1 0 0.614 6.484 93.6 2.3053 24 666 20.2 396.21 18.68 16.7
479 15.0234 0 18.1 0 0.614 5.304 97.3 2.1007 24 666 20.2 349.48 24.91 12
480 10.233 0 18.1 0 0.614 6.185 96.7 2.1705 24 666 20.2 379.7 18.03 14.6
481 14.3337 0 18.1 0 0.614 6.229 88 1.9512 24 666 20.2 383.32 13.11 21.4
482 5.82401 0 18.1 0 0.532 6.242 64.7 3.4242 24 666 20.2 396.9 10.74 23
483 5.70818 0 18.1 0 0.532 6.75 74.9 3.3317 24 666 20.2 393.07 7.74 23.7
484 5.73116 0 18.1 0 0.532 7.061 77 3.4106 24 666 20.2 395.28 7.01 25
485 2.81838 0 18.1 0 0.532 5.762 40.3 4.0983 24 666 20.2 392.92 10.42 21.8
486 2.37857 0 18.1 0 0.583 5.871 41.9 3.724 24 666 20.2 370.73 13.34 20.6
487 3.67367 0 18.1 0 0.583 6.312 51.9 3.9917 24 666 20.2 388.62 10.58 21.2
488 5.69175 0 18.1 0 0.583 6.114 79.8 3.5459 24 666 20.2 392.68 14.98 19.1
489 4.83567 0 18.1 0 0.583 5.905 53.2 3.1523 24 666 20.2 388.22 11.45 20.6
490 0.15086 0 27.74 0 0.609 5.454 92.7 1.8209 4 711 20.1 395.09 18.06 15.2
491 0.18337 0 27.74 0 0.609 5.414 98.3 1.7554 4 711 20.1 344.05 23.97 7
492 0.20746 0 27.74 0 0.609 5.093 98 1.8226 4 711 20.1 318.43 29.68 8.1
493 0.10574 0 27.74 0 0.609 5.983 98.8 1.8681 4 711 20.1 390.11 18.07 13.6
494 0.11132 0 27.74 0 0.609 5.983 83.5 2.1099 4 711 20.1 396.9 13.35 20.1
495 0.17331 0 9.69 0 0.585 5.707 54 2.3817 6 391 19.2 396.9 12.01 21.8
496 0.27957 0 9.69 0 0.585 5.926 42.6 2.3817 6 391 19.2 396.9 13.59 24.5
497 0.17899 0 9.69 0 0.585 5.67 28.8 2.7986 6 391 19.2 393.29 17.6 23.1
498 0.2896 0 9.69 0 0.585 5.39 72.9 2.7986 6 391 19.2 396.9 21.14 19.7
499 0.26838 0 9.69 0 0.585 5.794 70.6 2.8927 6 391 19.2 396.9 14.1 18.3
500 0.23912 0 9.69 0 0.585 6.019 65.3 2.4091 6 391 19.2 396.9 12.92 21.2
501 0.17783 0 9.69 0 0.585 5.569 73.5 2.3999 6 391 19.2 395.77 15.1 17.5
502 0.22438 0 9.69 0 0.585 6.027 79.7 2.4982 6 391 19.2 396.9 14.33 16.8
503 0.06263 0 11.93 0 0.573 6.593 69.1 2.4786 1 273 21 391.99 9.67 22.4
504 0.04527 0 11.93 0 0.573 6.12 76.7 2.2875 1 273 21 396.9 9.08 20.6
505 0.06076 0 11.93 0 0.573 6.976 91 2.1675 1 273 21 396.9 5.64 23.9
506 0.10959 0 11.93 0 0.573 6.794 89.3 2.3889 1 273 21 393.45 6.48 22
507 0.04741 0 11.93 0 0.573 6.03 80.8 2.505 1 273 21 396.9 7.88 11.9

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lab1.ipynb

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{
"cells": [
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"import numpy as np\n",
"import pandas as pd\n",
"from sklearn.feature_selection import mutual_info_regression\n",
"from sklearn.model_selection import train_test_split\n",
"from imblearn.over_sampling import ADASYN\n",
"from sklearn.preprocessing import LabelEncoder\n",
"import matplotlib.pyplot as plt\n",
"import seaborn as sns\n",
"\n",
"# Загрузка датасета с мобильными телефонами\n",
"df = pd.read_csv(\"data/mobile_prices.csv\")\n",
"print(df.columns)\n",
"\n",
"# Кодируем все строковые столбцы в числовые\n",
"label_encoders = {}\n",
"for col in df.select_dtypes(include=[\"object\"]).columns:\n",
" le = LabelEncoder()\n",
" df[col] = le.fit_transform(df[col])\n",
" label_encoders[col] = le\n",
"\n",
"# Проверка на пропуски и \"зашумленные\" столбцы\n",
"noisy_features = []\n",
"for col in df.columns:\n",
" if df[col].isnull().sum() / len(df) > 0.1: # Если более 10% пропусков\n",
" noisy_features.append(col)\n",
"print(f\"Зашумленные столбцы: {noisy_features}\")\n",
"\n",
"# Проверка на смещение\n",
"skewness = df.skew()\n",
"print(f\"Смещение: {skewness}\")\n",
"\n",
"skewed_features = skewness[abs(skewness) > 1].index.tolist()\n",
"print(f\"Сильно смещенные столбцы: {skewed_features}\")\n",
"\n",
"# Поиск выбросов\n",
"for col in df.select_dtypes(include=[\"number\"]).columns:\n",
" Q1 = df[col].quantile(0.25)\n",
" Q3 = df[col].quantile(0.75)\n",
" IQR = Q3 - Q1\n",
" lower_bound = Q1 - 1.5 * IQR\n",
" upper_bound = Q3 + 1.5 * IQR\n",
" outliers = df[col][(df[col] < lower_bound) | (df[col] > upper_bound)]\n",
" print(f\"Выбросы в столбце '{col}':\\n{outliers}\\n\")\n",
"\n",
"# Визуализация выбросов\n",
"numeric_cols = df.select_dtypes(include=[\"number\"]).columns\n",
"\n",
"plt.figure(figsize=(12, 8))\n",
"for i, col in enumerate(numeric_cols, 1):\n",
" plt.subplot(len(numeric_cols) // 3 + 1, 3, i)\n",
" sns.boxplot(data=df, x=col)\n",
" plt.title(f\"Boxplot for {col}\")\n",
"plt.tight_layout()\n",
"plt.show()\n",
"\n",
"# Логарифмирование признака 'Battery'\n",
"df[\"log_Battery\"] = np.log(df[\"Battery\"] + 1)\n",
"\n",
"# Заполнение пропусков\n",
"df[\"Battery\"] = df[\"Battery\"].fillna(df[\"Battery\"].mean())\n",
"\n",
"\n",
"# Функция для разбиения на train/val/test\n",
"def split_stratified_into_train_val_test(\n",
" df_input,\n",
" stratify_colname=\"y\",\n",
" frac_train=0.6,\n",
" frac_val=0.15,\n",
" frac_test=0.25,\n",
" random_state=None,\n",
"):\n",
" if frac_train + frac_val + frac_test != 1.0:\n",
" raise ValueError(\n",
" \"fractions %f, %f, %f do not add up to 1.0\"\n",
" % (frac_train, frac_val, frac_test)\n",
" )\n",
"\n",
" if stratify_colname not in df_input.columns:\n",
" raise ValueError(\"%s is not a column in the dataframe\" % (stratify_colname))\n",
"\n",
" X = df_input\n",
" y = df_input[[stratify_colname]]\n",
"\n",
" df_train, df_temp, y_train, y_temp = train_test_split(\n",
" X, y, stratify=y, test_size=(1.0 - frac_train), random_state=random_state\n",
" )\n",
" relative_frac_test = frac_test / (frac_val + frac_test)\n",
" df_val, df_test, y_val, y_test = train_test_split(\n",
" df_temp,\n",
" y_temp,\n",
" stratify=y_temp,\n",
" test_size=relative_frac_test,\n",
" random_state=random_state,\n",
" )\n",
"\n",
" assert len(df_input) == len(df_train) + len(df_val) + len(df_test)\n",
"\n",
" return df_train, df_val, df_test\n",
"\n",
"\n",
"# Разбиение на train/val/test\n",
"data = df[[\"Ram\", \"Price\", \"company\"]].copy()\n",
"\n",
"print(\"@data\", data)\n",
"\n",
"data = data.groupby(\"company\").filter(\n",
" lambda x: len(x) > 4\n",
") # убираем классы с одним элементом\n",
"\n",
"df_train, df_val, df_test = split_stratified_into_train_val_test(\n",
" data, stratify_colname=\"company\", frac_train=0.60, frac_val=0.20, frac_test=0.20\n",
")\n",
"\n",
"print(\"Обучающая выборка: \", df_train.shape)\n",
"print(df_train[\"Ram\"].value_counts())\n",
"\n",
"print(\"Контрольная выборка: \", df_val.shape)\n",
"print(df_val[\"Ram\"].value_counts())\n",
"\n",
"print(\"Тестовая выборка: \", df_test.shape)\n",
"print(df_test[\"Ram\"].value_counts())\n",
"\n",
"# # Применение ADASYN для oversampling\n",
"# ada = ADASYN(n_neighbors=2)\n",
"# X_resampled, y_resampled = ada.fit_resample(df_train, df_train[\"company\"])\n",
"# df_train_adasyn = pd.DataFrame(X_resampled)\n",
"\n",
"# print(\"Обучающая выборка после oversampling: \", df_train_adasyn.shape)\n",
"# print(df_train_adasyn[\"Ram\"].value_counts())"
]
}
],
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"kernelspec": {
"display_name": ".venv",
"language": "python",
"name": "python3"
},
"language_info": {
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2975
poetry.lock generated

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[virtualenvs]
in-project = true

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[tool.poetry]
name = "mai"
version = "1.0.0"
description = "MAI Examples"
authors = ["Aleksey Filippov <al.filippov@ulstu.ru>"]
readme = "readme.md"
package-mode = false
[tool.poetry.dependencies]
python = "^3.12"
jupyter = "^1.1.1"
numpy = "^2.1.0"
pandas = "^2.2.2"
matplotlib = "^3.9.2"
flask = "^3.0.3"
apiflask = "^2.2.0"
flask-cors = "^5.0.0"
[tool.poetry.group.dev.dependencies]
ipykernel = "^6.29.5"
[build-system]
requires = ["poetry-core"]
build-backend = "poetry.core.masonry.api"

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## Окружение и примеры для выполнения лабораторных работ по дисциплине "Методы ИИ"
### Python
Используется Python версии 3.12
Установщик https://www.python.org/ftp/python/3.12.5/python-3.12.5-amd64.exe
### Poetry
Для создания и настройки окружения проекта необходимо установить poetry
**Для Windows (Powershell)**
```
(Invoke-WebRequest -Uri https://install.python-poetry.org -UseBasicParsing).Content | python -
```
**Linux, macOS, Windows (WSL)**
```
curl -sSL https://install.python-poetry.org | python3 -
```
**Добавление poetry в PATH**
1. Открыть настройки переменных среды \
\
<img src="docs/path1.png" width="300"> \
\
<img src="docs/path2.png" width="400"> \
2. Изменить переменную Path текущего пользователя \
\
<img src="docs/path3.png" width="500"> \
3. Добавление пути `%APPDATA%\Python\Scripts` до исполняемого файла poetry \
\
<img src="docs/path4.png" width="400">
### Создание окружения
```
poetry install
```
### Запуск тестового сервиса
Запустить тестовый сервис можно с помощью VSCode (см. launch.json в каталоге .vscode).
Также запустить тестовый сервис можно с помощью командной строки:
1. Активация виртуального окружения -- `poetry shell`
2. Запуск сервиса -- `python run.py`
Для выходы из виртуального окружения используется команду `exit`

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run.py
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from backend import create_app
app = create_app()
def __main():
app.run(
host="127.0.0.1",
port=8080,
debug=True,
use_reloader=False,
)
if __name__ == "__main__":
__main()