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| a | b/talk/GrahamGroup.tex | ||
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| 2 | % Default to the notebook output style |
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| 7 | % Inherit from the specified cell style. |
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| 13 | \documentclass{article} |
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| 17 | \usepackage{graphicx} % Used to insert images |
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| 18 | \usepackage{adjustbox} % Used to constrain images to a maximum size |
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| 19 | \usepackage{color} % Allow colors to be defined |
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| 20 | \usepackage{enumerate} % Needed for markdown enumerations to work |
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| 21 | \usepackage{geometry} % Used to adjust the document margins |
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| 22 | \usepackage{amsmath} % Equations |
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| 23 | \usepackage{amssymb} % Equations |
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| 24 | \usepackage[mathletters]{ucs} % Extended unicode (utf-8) support |
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| 25 | \usepackage[utf8x]{inputenc} % Allow utf-8 characters in the tex document |
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| 26 | \usepackage{fancyvrb} % verbatim replacement that allows latex |
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| 27 | \usepackage{grffile} % extends the file name processing of package graphics |
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| 28 | % to support a larger range |
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| 29 | % The hyperref package gives us a pdf with properly built |
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| 30 | % internal navigation ('pdf bookmarks' for the table of contents, |
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| 31 | % internal cross-reference links, web links for URLs, etc.) |
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| 32 | \usepackage{hyperref} |
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| 33 | \usepackage{longtable} % longtable support required by pandoc >1.10 |
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| 34 | \usepackage{booktabs} % table support for pandoc > 1.12.2 |
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| 39 | \definecolor{orange}{cmyk}{0,0.4,0.8,0.2} |
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| 42 | \definecolor{myteal}{rgb}{.26, .44, .56} |
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| 43 | \definecolor{gray}{gray}{0.45} |
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| 44 | \definecolor{lightgray}{gray}{.95} |
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| 45 | \definecolor{mediumgray}{gray}{.8} |
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| 46 | \definecolor{inputbackground}{rgb}{.95, .95, .85} |
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| 47 | \definecolor{outputbackground}{rgb}{.95, .95, .95} |
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| 48 | \definecolor{traceback}{rgb}{1, .95, .95} |
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| 49 | % ansi colors |
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| 50 | \definecolor{red}{rgb}{.6,0,0} |
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| 52 | \definecolor{brown}{rgb}{0.6,0.6,0} |
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| 54 | \definecolor{purple}{rgb}{.698,.145,.698} |
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| 55 | \definecolor{cyan}{rgb}{0,.698,.698} |
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| 56 | \definecolor{lightgray}{gray}{0.5} |
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| 57 | |||
| 58 | % bright ansi colors |
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| 59 | \definecolor{darkgray}{gray}{0.25} |
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| 60 | \definecolor{lightred}{rgb}{1.0,0.39,0.28} |
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| 61 | \definecolor{lightgreen}{rgb}{0.48,0.99,0.0} |
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| 65 | |||
| 66 | % commands and environments needed by pandoc snippets |
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| 67 | % extracted from the output of `pandoc -s` |
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| 68 | \DefineVerbatimEnvironment{Highlighting}{Verbatim}{commandchars=\\\{\}} |
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| 69 | % Add ',fontsize=\small' for more characters per line |
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| 70 | \newenvironment{Shaded}{}{} |
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| 71 | \newcommand{\KeywordTok}[1]{\textcolor[rgb]{0.00,0.44,0.13}{\textbf{{#1}}}} |
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| 72 | \newcommand{\DataTypeTok}[1]{\textcolor[rgb]{0.56,0.13,0.00}{{#1}}} |
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| 73 | \newcommand{\DecValTok}[1]{\textcolor[rgb]{0.25,0.63,0.44}{{#1}}} |
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| 74 | \newcommand{\BaseNTok}[1]{\textcolor[rgb]{0.25,0.63,0.44}{{#1}}} |
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| 79 | \newcommand{\OtherTok}[1]{\textcolor[rgb]{0.00,0.44,0.13}{{#1}}} |
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| 80 | \newcommand{\AlertTok}[1]{\textcolor[rgb]{1.00,0.00,0.00}{\textbf{{#1}}}} |
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| 81 | \newcommand{\FunctionTok}[1]{\textcolor[rgb]{0.02,0.16,0.49}{{#1}}} |
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| 82 | \newcommand{\RegionMarkerTok}[1]{{#1}} |
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| 83 | \newcommand{\ErrorTok}[1]{\textcolor[rgb]{1.00,0.00,0.00}{\textbf{{#1}}}} |
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| 84 | \newcommand{\NormalTok}[1]{{#1}} |
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| 85 | |||
| 86 | % Define a nice break command that doesn't care if a line doesn't already |
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| 87 | % exist. |
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| 88 | \def\br{\hspace*{\fill} \\* } |
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| 89 | % Math Jax compatability definitions |
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| 90 | \def\gt{>} |
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| 91 | \def\lt{<} |
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| 92 | % Document parameters |
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| 93 | \title{GrahamGroup} |
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| 94 | |||
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| 97 | |||
| 98 | % Pygments definitions |
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| 99 | |||
| 100 | \makeatletter |
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| 101 | \def\PY@reset{\let\PY@it=\relax \let\PY@bf=\relax% |
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| 102 | \let\PY@ul=\relax \let\PY@tc=\relax% |
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| 103 | \let\PY@bc=\relax \let\PY@ff=\relax} |
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| 104 | \def\PY@tok#1{\csname PY@tok@#1\endcsname} |
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| 105 | \def\PY@toks#1+{\ifx\relax#1\empty\else% |
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| 106 | \PY@tok{#1}\expandafter\PY@toks\fi} |
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| 107 | \def\PY@do#1{\PY@bc{\PY@tc{\PY@ul{% |
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| 108 | \PY@it{\PY@bf{\PY@ff{#1}}}}}}} |
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| 109 | \def\PY#1#2{\PY@reset\PY@toks#1+\relax+\PY@do{#2}} |
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| 110 | |||
| 111 | \expandafter\def\csname PY@tok@gd\endcsname{\def\PY@tc##1{\textcolor[rgb]{0.63,0.00,0.00}{##1}}} |
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| 112 | \expandafter\def\csname PY@tok@gu\endcsname{\let\PY@bf=\textbf\def\PY@tc##1{\textcolor[rgb]{0.50,0.00,0.50}{##1}}} |
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| 113 | \expandafter\def\csname PY@tok@gt\endcsname{\def\PY@tc##1{\textcolor[rgb]{0.00,0.27,0.87}{##1}}} |
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| 114 | \expandafter\def\csname PY@tok@gs\endcsname{\let\PY@bf=\textbf} |
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| 115 | \expandafter\def\csname PY@tok@gr\endcsname{\def\PY@tc##1{\textcolor[rgb]{1.00,0.00,0.00}{##1}}} |
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| 116 | \expandafter\def\csname PY@tok@cm\endcsname{\let\PY@it=\textit\def\PY@tc##1{\textcolor[rgb]{0.25,0.50,0.50}{##1}}} |
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| 117 | \expandafter\def\csname PY@tok@vg\endcsname{\def\PY@tc##1{\textcolor[rgb]{0.10,0.09,0.49}{##1}}} |
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| 118 | \expandafter\def\csname PY@tok@m\endcsname{\def\PY@tc##1{\textcolor[rgb]{0.40,0.40,0.40}{##1}}} |
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| 119 | \expandafter\def\csname PY@tok@mh\endcsname{\def\PY@tc##1{\textcolor[rgb]{0.40,0.40,0.40}{##1}}} |
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| 120 | \expandafter\def\csname PY@tok@go\endcsname{\def\PY@tc##1{\textcolor[rgb]{0.53,0.53,0.53}{##1}}} |
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| 121 | \expandafter\def\csname PY@tok@ge\endcsname{\let\PY@it=\textit} |
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| 122 | \expandafter\def\csname PY@tok@vc\endcsname{\def\PY@tc##1{\textcolor[rgb]{0.10,0.09,0.49}{##1}}} |
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| 123 | \expandafter\def\csname PY@tok@il\endcsname{\def\PY@tc##1{\textcolor[rgb]{0.40,0.40,0.40}{##1}}} |
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| 124 | \expandafter\def\csname PY@tok@cs\endcsname{\let\PY@it=\textit\def\PY@tc##1{\textcolor[rgb]{0.25,0.50,0.50}{##1}}} |
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| 125 | \expandafter\def\csname PY@tok@cp\endcsname{\def\PY@tc##1{\textcolor[rgb]{0.74,0.48,0.00}{##1}}} |
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| 126 | \expandafter\def\csname PY@tok@gi\endcsname{\def\PY@tc##1{\textcolor[rgb]{0.00,0.63,0.00}{##1}}} |
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| 127 | \expandafter\def\csname PY@tok@gh\endcsname{\let\PY@bf=\textbf\def\PY@tc##1{\textcolor[rgb]{0.00,0.00,0.50}{##1}}} |
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| 128 | \expandafter\def\csname PY@tok@ni\endcsname{\let\PY@bf=\textbf\def\PY@tc##1{\textcolor[rgb]{0.60,0.60,0.60}{##1}}} |
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| 129 | \expandafter\def\csname PY@tok@nl\endcsname{\def\PY@tc##1{\textcolor[rgb]{0.63,0.63,0.00}{##1}}} |
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| 130 | \expandafter\def\csname PY@tok@nn\endcsname{\let\PY@bf=\textbf\def\PY@tc##1{\textcolor[rgb]{0.00,0.00,1.00}{##1}}} |
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| 131 | \expandafter\def\csname PY@tok@no\endcsname{\def\PY@tc##1{\textcolor[rgb]{0.53,0.00,0.00}{##1}}} |
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| 132 | \expandafter\def\csname PY@tok@na\endcsname{\def\PY@tc##1{\textcolor[rgb]{0.49,0.56,0.16}{##1}}} |
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| 133 | \expandafter\def\csname PY@tok@nb\endcsname{\def\PY@tc##1{\textcolor[rgb]{0.00,0.50,0.00}{##1}}} |
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| 134 | \expandafter\def\csname PY@tok@nc\endcsname{\let\PY@bf=\textbf\def\PY@tc##1{\textcolor[rgb]{0.00,0.00,1.00}{##1}}} |
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| 135 | \expandafter\def\csname PY@tok@nd\endcsname{\def\PY@tc##1{\textcolor[rgb]{0.67,0.13,1.00}{##1}}} |
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| 136 | \expandafter\def\csname PY@tok@ne\endcsname{\let\PY@bf=\textbf\def\PY@tc##1{\textcolor[rgb]{0.82,0.25,0.23}{##1}}} |
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| 137 | \expandafter\def\csname PY@tok@nf\endcsname{\def\PY@tc##1{\textcolor[rgb]{0.00,0.00,1.00}{##1}}} |
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| 138 | \expandafter\def\csname PY@tok@si\endcsname{\let\PY@bf=\textbf\def\PY@tc##1{\textcolor[rgb]{0.73,0.40,0.53}{##1}}} |
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| 139 | \expandafter\def\csname PY@tok@s2\endcsname{\def\PY@tc##1{\textcolor[rgb]{0.73,0.13,0.13}{##1}}} |
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| 140 | \expandafter\def\csname PY@tok@vi\endcsname{\def\PY@tc##1{\textcolor[rgb]{0.10,0.09,0.49}{##1}}} |
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| 141 | \expandafter\def\csname PY@tok@nt\endcsname{\let\PY@bf=\textbf\def\PY@tc##1{\textcolor[rgb]{0.00,0.50,0.00}{##1}}} |
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| 142 | \expandafter\def\csname PY@tok@nv\endcsname{\def\PY@tc##1{\textcolor[rgb]{0.10,0.09,0.49}{##1}}} |
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| 143 | \expandafter\def\csname PY@tok@s1\endcsname{\def\PY@tc##1{\textcolor[rgb]{0.73,0.13,0.13}{##1}}} |
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| 144 | \expandafter\def\csname PY@tok@sh\endcsname{\def\PY@tc##1{\textcolor[rgb]{0.73,0.13,0.13}{##1}}} |
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| 145 | \expandafter\def\csname PY@tok@sc\endcsname{\def\PY@tc##1{\textcolor[rgb]{0.73,0.13,0.13}{##1}}} |
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| 146 | \expandafter\def\csname PY@tok@sx\endcsname{\def\PY@tc##1{\textcolor[rgb]{0.00,0.50,0.00}{##1}}} |
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| 147 | \expandafter\def\csname PY@tok@bp\endcsname{\def\PY@tc##1{\textcolor[rgb]{0.00,0.50,0.00}{##1}}} |
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| 148 | \expandafter\def\csname PY@tok@c1\endcsname{\let\PY@it=\textit\def\PY@tc##1{\textcolor[rgb]{0.25,0.50,0.50}{##1}}} |
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| 149 | \expandafter\def\csname PY@tok@kc\endcsname{\let\PY@bf=\textbf\def\PY@tc##1{\textcolor[rgb]{0.00,0.50,0.00}{##1}}} |
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| 150 | \expandafter\def\csname PY@tok@c\endcsname{\let\PY@it=\textit\def\PY@tc##1{\textcolor[rgb]{0.25,0.50,0.50}{##1}}} |
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| 151 | \expandafter\def\csname PY@tok@mf\endcsname{\def\PY@tc##1{\textcolor[rgb]{0.40,0.40,0.40}{##1}}} |
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| 152 | \expandafter\def\csname PY@tok@err\endcsname{\def\PY@bc##1{\setlength{\fboxsep}{0pt}\fcolorbox[rgb]{1.00,0.00,0.00}{1,1,1}{\strut ##1}}} |
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| 153 | \expandafter\def\csname PY@tok@kd\endcsname{\let\PY@bf=\textbf\def\PY@tc##1{\textcolor[rgb]{0.00,0.50,0.00}{##1}}} |
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| 154 | \expandafter\def\csname PY@tok@ss\endcsname{\def\PY@tc##1{\textcolor[rgb]{0.10,0.09,0.49}{##1}}} |
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| 155 | \expandafter\def\csname PY@tok@sr\endcsname{\def\PY@tc##1{\textcolor[rgb]{0.73,0.40,0.53}{##1}}} |
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| 156 | \expandafter\def\csname PY@tok@mo\endcsname{\def\PY@tc##1{\textcolor[rgb]{0.40,0.40,0.40}{##1}}} |
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| 157 | \expandafter\def\csname PY@tok@kn\endcsname{\let\PY@bf=\textbf\def\PY@tc##1{\textcolor[rgb]{0.00,0.50,0.00}{##1}}} |
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| 158 | \expandafter\def\csname PY@tok@mi\endcsname{\def\PY@tc##1{\textcolor[rgb]{0.40,0.40,0.40}{##1}}} |
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| 159 | \expandafter\def\csname PY@tok@gp\endcsname{\let\PY@bf=\textbf\def\PY@tc##1{\textcolor[rgb]{0.00,0.00,0.50}{##1}}} |
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| 160 | \expandafter\def\csname PY@tok@o\endcsname{\def\PY@tc##1{\textcolor[rgb]{0.40,0.40,0.40}{##1}}} |
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| 161 | \expandafter\def\csname PY@tok@kr\endcsname{\let\PY@bf=\textbf\def\PY@tc##1{\textcolor[rgb]{0.00,0.50,0.00}{##1}}} |
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| 162 | \expandafter\def\csname PY@tok@s\endcsname{\def\PY@tc##1{\textcolor[rgb]{0.73,0.13,0.13}{##1}}} |
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| 163 | \expandafter\def\csname PY@tok@kp\endcsname{\def\PY@tc##1{\textcolor[rgb]{0.00,0.50,0.00}{##1}}} |
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| 164 | \expandafter\def\csname PY@tok@w\endcsname{\def\PY@tc##1{\textcolor[rgb]{0.73,0.73,0.73}{##1}}} |
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| 165 | \expandafter\def\csname PY@tok@kt\endcsname{\def\PY@tc##1{\textcolor[rgb]{0.69,0.00,0.25}{##1}}} |
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| 166 | \expandafter\def\csname PY@tok@ow\endcsname{\let\PY@bf=\textbf\def\PY@tc##1{\textcolor[rgb]{0.67,0.13,1.00}{##1}}} |
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| 167 | \expandafter\def\csname PY@tok@sb\endcsname{\def\PY@tc##1{\textcolor[rgb]{0.73,0.13,0.13}{##1}}} |
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| 168 | \expandafter\def\csname PY@tok@k\endcsname{\let\PY@bf=\textbf\def\PY@tc##1{\textcolor[rgb]{0.00,0.50,0.00}{##1}}} |
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| 169 | \expandafter\def\csname PY@tok@se\endcsname{\let\PY@bf=\textbf\def\PY@tc##1{\textcolor[rgb]{0.73,0.40,0.13}{##1}}} |
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| 170 | \expandafter\def\csname PY@tok@sd\endcsname{\let\PY@it=\textit\def\PY@tc##1{\textcolor[rgb]{0.73,0.13,0.13}{##1}}} |
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| 171 | |||
| 172 | \def\PYZbs{\char`\\} |
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| 173 | \def\PYZus{\char`\_} |
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| 174 | \def\PYZob{\char`\{} |
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| 175 | \def\PYZcb{\char`\}} |
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| 176 | \def\PYZca{\char`\^} |
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| 177 | \def\PYZam{\char`\&} |
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| 178 | \def\PYZlt{\char`\<} |
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| 179 | \def\PYZgt{\char`\>} |
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| 180 | \def\PYZsh{\char`\#} |
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| 181 | \def\PYZpc{\char`\%} |
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| 182 | \def\PYZdl{\char`\$} |
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| 183 | \def\PYZhy{\char`\-} |
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| 184 | \def\PYZsq{\char`\'} |
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| 185 | \def\PYZdq{\char`\"} |
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| 186 | \def\PYZti{\char`\~} |
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| 187 | % for compatibility with earlier versions |
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| 188 | \def\PYZat{@} |
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| 189 | \def\PYZlb{[} |
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| 190 | \def\PYZrb{]} |
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| 191 | \makeatother |
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| 192 | |||
| 193 | |||
| 194 | % Exact colors from NB |
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| 195 | \definecolor{incolor}{rgb}{0.0, 0.0, 0.5} |
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| 196 | \definecolor{outcolor}{rgb}{0.545, 0.0, 0.0} |
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| 197 | |||
| 198 | |||
| 199 | |||
| 200 | |||
| 201 | % Prevent overflowing lines due to hard-to-break entities |
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| 202 | \sloppy |
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| 203 | % Setup hyperref package |
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| 204 | \hypersetup{ |
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| 205 | breaklinks=true, % so long urls are correctly broken across lines |
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| 206 | colorlinks=true, |
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| 207 | urlcolor=blue, |
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| 208 | linkcolor=darkorange, |
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| 209 | citecolor=darkgreen, |
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| 210 | } |
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| 211 | % Slightly bigger margins than the latex defaults |
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| 212 | |||
| 213 | \geometry{verbose,tmargin=1in,bmargin=1in,lmargin=1in,rmargin=1in} |
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| 214 | |||
| 215 | |||
| 216 | |||
| 217 | \begin{document} |
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| 218 | |||
| 219 | |||
| 220 | \maketitle |
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| 221 | |||
| 222 | |||
| 223 | |||
| 224 | |||
| 225 | |||
| 226 | \section{Robust Extraction of Quantitative Information from Histology Images} |
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| 227 | |||
| 228 | |||
| 229 | |||
| 230 | \paragraph{Quentin Caudron Romain Garnier \emph{with Bryan Grenfell and Andrea |
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| 231 | Graham}} |
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| 232 | |||
| 233 | |||
| 234 | |||
| 235 | \subsubsection{Outline} |
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| 236 | |||
| 237 | |||
| 238 | \begin{itemize} |
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| 239 | \itemsep1pt\parskip0pt\parsep0pt |
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| 240 | \item |
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| 241 | Image processing |
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| 242 | \item |
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| 243 | Extracted measures |
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| 244 | \item |
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| 245 | Preliminary analysis |
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| 246 | \item |
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| 247 | Future directions |
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| 248 | \end{itemize} |
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| 249 | |||
| 250 | \begin{enumerate} |
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| 251 | \def\labelenumi{\arabic{enumi}.} |
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| 252 | \setcounter{enumi}{3} |
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| 253 | \itemsep1pt\parskip0pt\parsep0pt |
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| 254 | \item |
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| 255 | Age as random effect \textless{}--- |
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| 256 | \end{enumerate} |
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| 257 | |||
| 258 | {[}``interface\_hepatitis'', ``confluent\_necrosis'', |
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| 259 | ``portal\_inflammation'', ``ln\_ap\_ri''{]} |
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| 260 | |||
| 261 | \begin{Verbatim}[commandchars=\\\{\}] |
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| 262 | {\color{incolor}In [{\color{incolor}3}]:} \PY{k}{def} \PY{n+nf}{normalise}\PY{p}{(}\PY{n}{df}\PY{p}{,} \PY{n}{skip} \PY{o}{=} \PY{p}{[}\PY{p}{]}\PY{p}{)} \PY{p}{:} |
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| 263 | \PY{k}{for} \PY{n}{i} \PY{o+ow}{in} \PY{n}{df}\PY{o}{.}\PY{n}{columns} \PY{p}{:} |
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| 264 | \PY{k}{if} \PY{n}{i} \PY{o+ow}{not} \PY{o+ow}{in} \PY{n}{skip} \PY{p}{:} |
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| 265 | \PY{n}{df}\PY{p}{[}\PY{n}{i}\PY{p}{]} \PY{o}{\PYZhy{}}\PY{o}{=} \PY{n}{df}\PY{p}{[}\PY{n}{i}\PY{p}{]}\PY{o}{.}\PY{n}{mean}\PY{p}{(}\PY{p}{)} |
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| 266 | \PY{n}{df}\PY{p}{[}\PY{n}{i}\PY{p}{]} \PY{o}{/}\PY{o}{=} \PY{n}{df}\PY{p}{[}\PY{n}{i}\PY{p}{]}\PY{o}{.}\PY{n}{std}\PY{p}{(}\PY{p}{)} |
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| 267 | \PY{k}{return} \PY{n}{df} |
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| 268 | |||
| 269 | |||
| 270 | |||
| 271 | |||
| 272 | |||
| 273 | |||
| 274 | \PY{k}{def} \PY{n+nf}{rescale}\PY{p}{(}\PY{n}{df}\PY{p}{,} \PY{n}{skip} \PY{o}{=} \PY{p}{[}\PY{p}{]}\PY{p}{)} \PY{p}{:} |
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| 275 | \PY{k}{for} \PY{n}{i} \PY{o+ow}{in} \PY{n}{df}\PY{o}{.}\PY{n}{columns} \PY{p}{:} |
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| 276 | \PY{k}{if} \PY{n}{i} \PY{o+ow}{not} \PY{o+ow}{in} \PY{n}{skip} \PY{p}{:} |
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| 277 | \PY{n}{df}\PY{p}{[}\PY{n}{i}\PY{p}{]} \PY{o}{\PYZhy{}}\PY{o}{=} \PY{n}{df}\PY{p}{[}\PY{n}{i}\PY{p}{]}\PY{o}{.}\PY{n}{min}\PY{p}{(}\PY{p}{)} |
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| 278 | \PY{n}{df}\PY{p}{[}\PY{n}{i}\PY{p}{]} \PY{o}{/}\PY{o}{=} \PY{n}{df}\PY{p}{[}\PY{n}{i}\PY{p}{]}\PY{o}{.}\PY{n}{max}\PY{p}{(}\PY{p}{)} |
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| 279 | \PY{k}{return} \PY{n}{df} |
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| 280 | |||
| 281 | |||
| 282 | |||
| 283 | \PY{c}{\PYZsh{} Remove a layer from a list} |
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| 284 | \PY{k}{def} \PY{n+nf}{delayer}\PY{p}{(}\PY{n}{m}\PY{p}{)} \PY{p}{:} |
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| 285 | \PY{n}{out} \PY{o}{=} \PY{p}{[}\PY{p}{]} |
||
| 286 | \PY{k}{for} \PY{n}{i} \PY{o+ow}{in} \PY{n}{m} \PY{p}{:} |
||
| 287 | \PY{k}{if} \PY{n+nb}{isinstance}\PY{p}{(}\PY{n}{i}\PY{p}{,} \PY{n+nb}{list}\PY{p}{)} \PY{p}{:} |
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| 288 | \PY{k}{for} \PY{n}{j} \PY{o+ow}{in} \PY{n}{i} \PY{p}{:} |
||
| 289 | \PY{n}{out}\PY{o}{.}\PY{n}{append}\PY{p}{(}\PY{n}{j}\PY{p}{)} |
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| 290 | \PY{k}{else} \PY{p}{:} |
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| 291 | \PY{n}{out}\PY{o}{.}\PY{n}{append}\PY{p}{(}\PY{n}{i}\PY{p}{)} |
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| 292 | \PY{k}{return} \PY{n}{out} |
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| 293 | |||
| 294 | |||
| 295 | |||
| 296 | |||
| 297 | |||
| 298 | |||
| 299 | |||
| 300 | \PY{c}{\PYZsh{} Remove all layers from a list} |
||
| 301 | \PY{k}{def} \PY{n+nf}{flatten}\PY{p}{(}\PY{n}{m}\PY{p}{)} \PY{p}{:} |
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| 302 | \PY{n}{out} \PY{o}{=} \PY{n}{m}\PY{p}{[}\PY{p}{:}\PY{p}{]} |
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| 303 | |||
| 304 | \PY{k}{while} \PY{n}{out} \PY{o}{!=} \PY{n}{delayer}\PY{p}{(}\PY{n}{out}\PY{p}{)} \PY{p}{:} |
||
| 305 | \PY{n}{out} \PY{o}{=} \PY{n}{delayer}\PY{p}{(}\PY{n}{out}\PY{p}{)} |
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| 306 | |||
| 307 | \PY{k}{return} \PY{n}{out} |
||
| 308 | |||
| 309 | |||
| 310 | |||
| 311 | |||
| 312 | |||
| 313 | |||
| 314 | |||
| 315 | |||
| 316 | \PY{c}{\PYZsh{} Generate all combinations of objects in a list} |
||
| 317 | \PY{k}{def} \PY{n+nf}{combinatorial}\PY{p}{(}\PY{n}{l}\PY{p}{)} \PY{p}{:} |
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| 318 | \PY{n}{out} \PY{o}{=} \PY{p}{[}\PY{p}{]} |
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| 319 | |||
| 320 | \PY{k}{for} \PY{n}{numel} \PY{o+ow}{in} \PY{n+nb}{range}\PY{p}{(}\PY{n+nb}{len}\PY{p}{(}\PY{n}{l}\PY{p}{)}\PY{p}{)} \PY{p}{:} |
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| 321 | \PY{k}{for} \PY{n}{i} \PY{o+ow}{in} \PY{n}{itertools}\PY{o}{.}\PY{n}{combinations}\PY{p}{(}\PY{n}{l}\PY{p}{,} \PY{n}{numel}\PY{o}{+}\PY{l+m+mi}{1}\PY{p}{)} \PY{p}{:} |
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| 322 | \PY{n}{out}\PY{o}{.}\PY{n}{append}\PY{p}{(}\PY{n+nb}{list}\PY{p}{(}\PY{n}{i}\PY{p}{)}\PY{p}{)} |
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| 323 | |||
| 324 | \PY{k}{return} \PY{n}{out} |
||
| 325 | |||
| 326 | |||
| 327 | |||
| 328 | |||
| 329 | |||
| 330 | |||
| 331 | |||
| 332 | |||
| 333 | |||
| 334 | |||
| 335 | \PY{k}{def} \PY{n+nf}{pcaplot}\PY{p}{(}\PY{n}{df}\PY{p}{)} \PY{p}{:} |
||
| 336 | |||
| 337 | \PY{c}{\PYZsh{} PCA} |
||
| 338 | \PY{n}{pca} \PY{o}{=} \PY{n}{decomposition}\PY{o}{.}\PY{n}{PCA}\PY{p}{(}\PY{n}{whiten} \PY{o}{=} \PY{n+nb+bp}{True}\PY{p}{)} |
||
| 339 | \PY{n}{pca}\PY{o}{.}\PY{n}{fit}\PY{p}{(}\PY{n}{df}\PY{p}{)} |
||
| 340 | \PY{n}{p1} \PY{o}{=} \PY{n}{pca}\PY{o}{.}\PY{n}{components\PYZus{}}\PY{p}{[}\PY{l+m+mi}{0}\PY{p}{]} \PY{o}{/} \PY{n}{np}\PY{o}{.}\PY{n}{abs}\PY{p}{(}\PY{n}{pca}\PY{o}{.}\PY{n}{components\PYZus{}}\PY{p}{[}\PY{l+m+mi}{0}\PY{p}{]}\PY{p}{)}\PY{o}{.}\PY{n}{max}\PY{p}{(}\PY{p}{)} \PY{o}{*} \PY{n}{np}\PY{o}{.}\PY{n}{sqrt}\PY{p}{(}\PY{l+m+mi}{2}\PY{p}{)}\PY{o}{/}\PY{l+m+mi}{2} |
||
| 341 | \PY{n}{p2} \PY{o}{=} \PY{n}{pca}\PY{o}{.}\PY{n}{components\PYZus{}}\PY{p}{[}\PY{l+m+mi}{1}\PY{p}{]} \PY{o}{/} \PY{n}{np}\PY{o}{.}\PY{n}{abs}\PY{p}{(}\PY{n}{pca}\PY{o}{.}\PY{n}{components\PYZus{}}\PY{p}{[}\PY{l+m+mi}{1}\PY{p}{]}\PY{p}{)}\PY{o}{.}\PY{n}{max}\PY{p}{(}\PY{p}{)} \PY{o}{*} \PY{n}{np}\PY{o}{.}\PY{n}{sqrt}\PY{p}{(}\PY{l+m+mi}{2}\PY{p}{)}\PY{o}{/}\PY{l+m+mi}{2} |
||
| 342 | |||
| 343 | \PY{c}{\PYZsh{} Normalise} |
||
| 344 | \PY{n}{norms} \PY{o}{=} \PY{n}{np}\PY{o}{.}\PY{n}{max}\PY{p}{(}\PY{p}{[}\PY{n}{np}\PY{o}{.}\PY{n}{sqrt}\PY{p}{(}\PY{p}{(}\PY{n}{np}\PY{o}{.}\PY{n}{array}\PY{p}{(}\PY{n+nb}{zip}\PY{p}{(}\PY{n}{p1}\PY{p}{,} \PY{n}{p2}\PY{p}{)}\PY{p}{[}\PY{n}{i}\PY{p}{]}\PY{p}{)}\PY{o}{*}\PY{o}{*}\PY{l+m+mi}{2}\PY{p}{)}\PY{o}{.}\PY{n}{sum}\PY{p}{(}\PY{p}{)}\PY{p}{)} \PY{k}{for} \PY{n}{i} \PY{o+ow}{in} \PY{n+nb}{range}\PY{p}{(}\PY{n+nb}{len}\PY{p}{(}\PY{n}{p1}\PY{p}{)}\PY{p}{)}\PY{p}{]}\PY{p}{)} |
||
| 345 | \PY{n}{c} \PY{o}{=} \PY{n}{plt}\PY{o}{.}\PY{n}{Circle}\PY{p}{(} \PY{p}{(}\PY{l+m+mi}{0}\PY{p}{,} \PY{l+m+mi}{0}\PY{p}{)}\PY{p}{,} \PY{n}{radius} \PY{o}{=} \PY{l+m+mi}{1}\PY{p}{,} \PY{n}{alpha} \PY{o}{=} \PY{l+m+mf}{0.2}\PY{p}{)} |
||
| 346 | \PY{n}{plt}\PY{o}{.}\PY{n}{axes}\PY{p}{(}\PY{n}{aspect} \PY{o}{=} \PY{l+m+mi}{1}\PY{p}{)} |
||
| 347 | \PY{n}{plt}\PY{o}{.}\PY{n}{gca}\PY{p}{(}\PY{p}{)}\PY{o}{.}\PY{n}{add\PYZus{}artist}\PY{p}{(}\PY{n}{c}\PY{p}{)} |
||
| 348 | |||
| 349 | \PY{n}{plt}\PY{o}{.}\PY{n}{scatter}\PY{p}{(}\PY{n}{p1} \PY{o}{/} \PY{n}{norms}\PY{p}{,} \PY{n}{p2} \PY{o}{/} \PY{n}{norms}\PY{p}{)} |
||
| 350 | \PY{n}{plt}\PY{o}{.}\PY{n}{xlim}\PY{p}{(}\PY{p}{[}\PY{o}{\PYZhy{}}\PY{l+m+mi}{1}\PY{p}{,} \PY{l+m+mi}{1}\PY{p}{]}\PY{p}{)} |
||
| 351 | \PY{n}{plt}\PY{o}{.}\PY{n}{ylim}\PY{p}{(}\PY{p}{[}\PY{o}{\PYZhy{}}\PY{l+m+mi}{1}\PY{p}{,} \PY{l+m+mi}{1}\PY{p}{]}\PY{p}{)} |
||
| 352 | |||
| 353 | \PY{k}{for} \PY{n}{i}\PY{p}{,} \PY{n}{text} \PY{o+ow}{in} \PY{n+nb}{enumerate}\PY{p}{(}\PY{n}{df}\PY{o}{.}\PY{n}{columns}\PY{p}{)} \PY{p}{:} |
||
| 354 | \PY{n}{plt}\PY{o}{.}\PY{n}{annotate}\PY{p}{(}\PY{n}{text}\PY{p}{,} \PY{n}{xy} \PY{o}{=} \PY{p}{[}\PY{n}{p1}\PY{p}{[}\PY{n}{i}\PY{p}{]}\PY{p}{,} \PY{n}{p2}\PY{p}{[}\PY{n}{i}\PY{p}{]}\PY{p}{]}\PY{p}{)} |
||
| 355 | |||
| 356 | \PY{n}{plt}\PY{o}{.}\PY{n}{tight\PYZus{}layout}\PY{p}{(}\PY{p}{)} |
||
| 357 | |||
| 358 | |||
| 359 | |||
| 360 | |||
| 361 | |||
| 362 | |||
| 363 | |||
| 364 | |||
| 365 | |||
| 366 | |||
| 367 | |||
| 368 | \PY{k}{def} \PY{n+nf}{test\PYZus{}all\PYZus{}linear}\PY{p}{(}\PY{n}{df}\PY{p}{,} \PY{n}{y}\PY{p}{,} \PY{n}{x}\PY{p}{,} \PY{n}{return\PYZus{}significant} \PY{o}{=} \PY{n+nb+bp}{False}\PY{p}{,} \PY{n}{group} \PY{o}{=} \PY{n+nb+bp}{None}\PY{p}{)} \PY{p}{:} |
||
| 369 | |||
| 370 | \PY{c}{\PYZsh{} All possible combinations of independent variables} |
||
| 371 | \PY{n}{independent} \PY{o}{=} \PY{n}{combinatorial}\PY{p}{(}\PY{n}{x}\PY{p}{)} |
||
| 372 | |||
| 373 | \PY{n}{fits} \PY{o}{=} \PY{p}{\PYZob{}}\PY{p}{\PYZcb{}} |
||
| 374 | \PY{n}{pval} \PY{o}{=} \PY{p}{\PYZob{}}\PY{p}{\PYZcb{}} |
||
| 375 | \PY{n}{linmodels} \PY{o}{=} \PY{p}{\PYZob{}}\PY{p}{\PYZcb{}} |
||
| 376 | \PY{n}{qsum} \PY{o}{=} \PY{p}{\PYZob{}}\PY{p}{\PYZcb{}} |
||
| 377 | \PY{n}{aic} \PY{o}{=} \PY{p}{\PYZob{}}\PY{p}{\PYZcb{}} |
||
| 378 | |||
| 379 | \PY{c}{\PYZsh{} For all dependent variables, one at a time} |
||
| 380 | \PY{k}{for} \PY{n}{dependent} \PY{o+ow}{in} \PY{n}{y} \PY{p}{:} |
||
| 381 | |||
| 382 | \PY{k}{print} \PY{l+s}{\PYZdq{}}\PY{l+s}{Fitting for }\PY{l+s+si}{\PYZpc{}s}\PY{l+s}{.}\PY{l+s}{\PYZdq{}} \PY{o}{\PYZpc{}} \PY{n}{dependent} |
||
| 383 | |||
| 384 | \PY{c}{\PYZsh{} For all combinations of independent variables} |
||
| 385 | \PY{k}{for} \PY{n}{covariate} \PY{o+ow}{in} \PY{n}{independent} \PY{p}{:} |
||
| 386 | |||
| 387 | \PY{c}{\PYZsh{} Standard mixed model} |
||
| 388 | \PY{k}{if} \PY{n}{group} \PY{o+ow}{is} \PY{n+nb+bp}{None} \PY{p}{:} |
||
| 389 | |||
| 390 | \PY{c}{\PYZsh{} Fit a linear model} |
||
| 391 | \PY{n}{subset} \PY{o}{=} \PY{n}{delayer}\PY{p}{(}\PY{p}{[}\PY{n}{covariate}\PY{p}{,} \PY{n}{dependent}\PY{p}{]}\PY{p}{)} |
||
| 392 | \PY{n}{df2} \PY{o}{=} \PY{n}{df}\PY{p}{[}\PY{n}{delayer}\PY{p}{(}\PY{n}{subset}\PY{p}{)}\PY{p}{]}\PY{o}{.}\PY{n}{dropna}\PY{p}{(}\PY{p}{)} |
||
| 393 | \PY{n}{df2}\PY{p}{[}\PY{l+s}{\PYZdq{}}\PY{l+s}{Intercept}\PY{l+s}{\PYZdq{}}\PY{p}{]} \PY{o}{=} \PY{n}{np}\PY{o}{.}\PY{n}{ones}\PY{p}{(}\PY{n+nb}{len}\PY{p}{(}\PY{n}{df2}\PY{p}{)}\PY{p}{)} |
||
| 394 | |||
| 395 | \PY{n}{ols} \PY{o}{=} \PY{n}{sm}\PY{o}{.}\PY{n}{GLS}\PY{p}{(}\PY{n}{endog} \PY{o}{=} \PY{n}{df2}\PY{p}{[}\PY{n}{dependent}\PY{p}{]}\PY{p}{,} \PY{n}{exog} \PY{o}{=} \PY{n}{df2}\PY{p}{[}\PY{n}{delayer}\PY{p}{(}\PY{p}{[}\PY{n}{covariate}\PY{p}{,} \PY{l+s}{\PYZdq{}}\PY{l+s}{Intercept}\PY{l+s}{\PYZdq{}}\PY{p}{]}\PY{p}{)}\PY{p}{]}\PY{p}{)}\PY{o}{.}\PY{n}{fit}\PY{p}{(}\PY{p}{)} |
||
| 396 | |||
| 397 | \PY{c}{\PYZsh{} Save the results} |
||
| 398 | \PY{k}{if} \PY{p}{(}\PY{n}{return\PYZus{}significant} \PY{o+ow}{and} \PY{n}{ols}\PY{o}{.}\PY{n}{f\PYZus{}pvalue} \PY{o}{\PYZlt{}} \PY{l+m+mf}{0.05}\PY{p}{)} \PY{o+ow}{or} \PY{p}{(}\PY{o+ow}{not} \PY{n}{return\PYZus{}significant}\PY{p}{)} \PY{p}{:} |
||
| 399 | \PY{n}{linmodels}\PY{o}{.}\PY{n}{setdefault}\PY{p}{(}\PY{n}{dependent}\PY{p}{,} \PY{p}{[}\PY{p}{]}\PY{p}{)}\PY{o}{.}\PY{n}{append}\PY{p}{(}\PY{n}{ols}\PY{p}{)} |
||
| 400 | \PY{n}{fits}\PY{o}{.}\PY{n}{setdefault}\PY{p}{(}\PY{n}{dependent}\PY{p}{,} \PY{p}{[}\PY{p}{]}\PY{p}{)}\PY{o}{.}\PY{n}{append}\PY{p}{(}\PY{n}{ols}\PY{o}{.}\PY{n}{rsquared}\PY{p}{)} |
||
| 401 | \PY{n}{pval}\PY{o}{.}\PY{n}{setdefault}\PY{p}{(}\PY{n}{dependent}\PY{p}{,} \PY{p}{[}\PY{p}{]}\PY{p}{)}\PY{o}{.}\PY{n}{append}\PY{p}{(}\PY{n}{ols}\PY{o}{.}\PY{n}{f\PYZus{}pvalue}\PY{p}{)} |
||
| 402 | \PY{n}{aic}\PY{o}{.}\PY{n}{setdefault}\PY{p}{(}\PY{n}{dependent}\PY{p}{,} \PY{p}{[}\PY{p}{]}\PY{p}{)}\PY{o}{.}\PY{n}{append}\PY{p}{(}\PY{n}{ols}\PY{o}{.}\PY{n}{aic}\PY{p}{)} |
||
| 403 | |||
| 404 | |||
| 405 | \PY{c}{\PYZsh{} Mixed effects model} |
||
| 406 | \PY{k}{else} \PY{p}{:} |
||
| 407 | \PY{n}{subset} \PY{o}{=} \PY{n}{delayer}\PY{p}{(}\PY{p}{[}\PY{n}{covariate}\PY{p}{,} \PY{n}{dependent}\PY{p}{,} \PY{n}{group}\PY{p}{]}\PY{p}{)} |
||
| 408 | \PY{n}{df2} \PY{o}{=} \PY{n}{df}\PY{p}{[}\PY{n}{delayer}\PY{p}{(}\PY{n}{subset}\PY{p}{)}\PY{p}{]}\PY{o}{.}\PY{n}{dropna}\PY{p}{(}\PY{p}{)} |
||
| 409 | |||
| 410 | \PY{c}{\PYZsh{} Fit a mixed effects model} |
||
| 411 | \PY{n}{ols} \PY{o}{=} \PY{n}{MixedLM}\PY{p}{(}\PY{n}{endog} \PY{o}{=} \PY{n}{df2}\PY{p}{[}\PY{n}{dependent}\PY{p}{]}\PY{p}{,} \PY{n}{exog} \PY{o}{=} \PY{n}{df2}\PY{p}{[}\PY{n}{covariate}\PY{p}{]}\PY{p}{,} \PY{n}{groups} \PY{o}{=} \PY{n}{df2}\PY{p}{[}\PY{n}{group}\PY{p}{]}\PY{p}{)}\PY{o}{.}\PY{n}{fit}\PY{p}{(}\PY{p}{)} |
||
| 412 | |||
| 413 | \PY{c}{\PYZsh{} Calculate AIC} |
||
| 414 | \PY{n}{linmodels}\PY{o}{.}\PY{n}{setdefault}\PY{p}{(}\PY{n}{dependent}\PY{p}{,} \PY{p}{[}\PY{p}{]}\PY{p}{)}\PY{o}{.}\PY{n}{append}\PY{p}{(}\PY{n}{ols}\PY{p}{)} |
||
| 415 | \PY{n}{fits}\PY{o}{.}\PY{n}{setdefault}\PY{p}{(}\PY{n}{dependent}\PY{p}{,} \PY{p}{[}\PY{p}{]}\PY{p}{)}\PY{o}{.}\PY{n}{append}\PY{p}{(}\PY{l+m+mi}{2} \PY{o}{*} \PY{p}{(}\PY{n}{ols}\PY{o}{.}\PY{n}{k\PYZus{}fe} \PY{o}{+} \PY{l+m+mi}{1}\PY{p}{)} \PY{o}{\PYZhy{}} \PY{l+m+mi}{2} \PY{o}{*} \PY{n}{ols}\PY{o}{.}\PY{n}{llf}\PY{p}{)} |
||
| 416 | \PY{n}{pval}\PY{o}{.}\PY{n}{setdefault}\PY{p}{(}\PY{n}{dependent}\PY{p}{,} \PY{p}{[}\PY{p}{]}\PY{p}{)}\PY{o}{.}\PY{n}{append}\PY{p}{(}\PY{n}{ols}\PY{o}{.}\PY{n}{pvalues}\PY{p}{)} |
||
| 417 | |||
| 418 | \PY{k}{if} \PY{n}{group} \PY{o+ow}{is} \PY{o+ow}{not} \PY{n+nb+bp}{None} \PY{p}{:} |
||
| 419 | \PY{k}{for} \PY{n}{i} \PY{o+ow}{in} \PY{n}{y} \PY{p}{:} |
||
| 420 | \PY{n}{f} \PY{o}{=} \PY{n}{np}\PY{o}{.}\PY{n}{array}\PY{p}{(}\PY{n}{fits}\PY{p}{[}\PY{n}{i}\PY{p}{]}\PY{p}{)} |
||
| 421 | \PY{n}{models} \PY{o}{=} \PY{n}{np}\PY{o}{.}\PY{n}{array}\PY{p}{(}\PY{n}{linmodels}\PY{p}{[}\PY{n}{i}\PY{p}{]}\PY{p}{)} |
||
| 422 | \PY{n}{idx} \PY{o}{=} \PY{n}{np}\PY{o}{.}\PY{n}{where}\PY{p}{(}\PY{n}{f} \PY{o}{\PYZhy{}} \PY{n}{f}\PY{o}{.}\PY{n}{min}\PY{p}{(}\PY{p}{)} \PY{o}{\PYZlt{}}\PY{o}{=} \PY{l+m+mi}{2}\PY{p}{)}\PY{p}{[}\PY{l+m+mi}{0}\PY{p}{]} |
||
| 423 | \PY{n}{bestmodelDoF} \PY{o}{=} \PY{p}{[}\PY{n}{j}\PY{o}{.}\PY{n}{k\PYZus{}fe} \PY{k}{for} \PY{n}{j} \PY{o+ow}{in} \PY{n}{np}\PY{o}{.}\PY{n}{array}\PY{p}{(}\PY{n}{linmodels}\PY{p}{[}\PY{n}{i}\PY{p}{]}\PY{p}{)}\PY{p}{[}\PY{n}{idx}\PY{p}{]}\PY{p}{]} |
||
| 424 | \PY{n}{bestmodels} \PY{o}{=} \PY{p}{[}\PY{n}{idx}\PY{p}{[}\PY{n}{j}\PY{p}{]} \PY{k}{for} \PY{n}{j} \PY{o+ow}{in} \PY{n}{np}\PY{o}{.}\PY{n}{where}\PY{p}{(}\PY{n}{bestmodelDoF} \PY{o}{==} \PY{n}{np}\PY{o}{.}\PY{n}{min}\PY{p}{(}\PY{n}{bestmodelDoF}\PY{p}{)}\PY{p}{)}\PY{p}{[}\PY{l+m+mi}{0}\PY{p}{]}\PY{p}{]} |
||
| 425 | \PY{n}{qsum}\PY{p}{[}\PY{n}{i}\PY{p}{]} \PY{o}{=} \PY{n}{models}\PY{p}{[}\PY{n}{idx}\PY{p}{[}\PY{n}{np}\PY{o}{.}\PY{n}{where}\PY{p}{(}\PY{n}{f}\PY{p}{[}\PY{n}{bestmodels}\PY{p}{]} \PY{o}{==} \PY{n}{np}\PY{o}{.}\PY{n}{min}\PY{p}{(}\PY{n}{f}\PY{p}{[}\PY{n}{bestmodels}\PY{p}{]}\PY{p}{)}\PY{p}{)}\PY{p}{]}\PY{p}{]} |
||
| 426 | |||
| 427 | |||
| 428 | \PY{k}{return} \PY{n}{linmodels}\PY{p}{,} \PY{n}{fits}\PY{p}{,} \PY{n}{pval}\PY{p}{,} \PY{n}{qsum} |
||
| 429 | |||
| 430 | \PY{k}{return} \PY{n}{linmodels}\PY{p}{,} \PY{n}{fits}\PY{p}{,} \PY{n}{pval}\PY{p}{,} \PY{n}{aic} |
||
| 431 | |||
| 432 | |||
| 433 | |||
| 434 | |||
| 435 | |||
| 436 | |||
| 437 | |||
| 438 | |||
| 439 | |||
| 440 | |||
| 441 | |||
| 442 | |||
| 443 | |||
| 444 | |||
| 445 | |||
| 446 | |||
| 447 | |||
| 448 | |||
| 449 | \PY{k}{def} \PY{n+nf}{summary}\PY{p}{(}\PY{n}{models}\PY{p}{)} \PY{p}{:} |
||
| 450 | |||
| 451 | \PY{c}{\PYZsh{} Generate list of everything} |
||
| 452 | \PY{n}{r2} \PY{o}{=} \PY{n}{np}\PY{o}{.}\PY{n}{array}\PY{p}{(}\PY{p}{[}\PY{n}{m}\PY{o}{.}\PY{n}{r2} \PY{k}{for} \PY{n}{dependent} \PY{o+ow}{in} \PY{n}{models}\PY{o}{.}\PY{n}{keys}\PY{p}{(}\PY{p}{)} \PY{k}{for} \PY{n}{m} \PY{o+ow}{in} \PY{n}{models}\PY{p}{[}\PY{n}{dependent}\PY{p}{]}\PY{p}{]}\PY{p}{)} |
||
| 453 | \PY{n}{p} \PY{o}{=} \PY{n}{np}\PY{o}{.}\PY{n}{array}\PY{p}{(}\PY{p}{[}\PY{n}{m}\PY{o}{.}\PY{n}{f\PYZus{}stat}\PY{p}{[}\PY{l+s}{\PYZdq{}}\PY{l+s}{p\PYZhy{}value}\PY{l+s}{\PYZdq{}}\PY{p}{]} \PY{k}{for} \PY{n}{dependent} \PY{o+ow}{in} \PY{n}{models}\PY{o}{.}\PY{n}{keys}\PY{p}{(}\PY{p}{)} \PY{k}{for} \PY{n}{m} \PY{o+ow}{in} \PY{n}{models}\PY{p}{[}\PY{n}{dependent}\PY{p}{]}\PY{p}{]}\PY{p}{)} |
||
| 454 | \PY{n}{mod} \PY{o}{=} \PY{n}{np}\PY{o}{.}\PY{n}{array}\PY{p}{(}\PY{p}{[}\PY{n}{m} \PY{k}{for} \PY{n}{dependent} \PY{o+ow}{in} \PY{n}{models}\PY{o}{.}\PY{n}{keys}\PY{p}{(}\PY{p}{)} \PY{k}{for} \PY{n}{m} \PY{o+ow}{in} \PY{n}{models}\PY{p}{[}\PY{n}{dependent}\PY{p}{]}\PY{p}{]}\PY{p}{)} |
||
| 455 | \PY{n}{dependent} \PY{o}{=} \PY{n}{np}\PY{o}{.}\PY{n}{array}\PY{p}{(}\PY{p}{[}\PY{n}{dependent} \PY{k}{for} \PY{n}{dependent} \PY{o+ow}{in} \PY{n}{models}\PY{o}{.}\PY{n}{keys}\PY{p}{(}\PY{p}{)} \PY{k}{for} \PY{n}{m} \PY{o+ow}{in} \PY{n}{models}\PY{p}{[}\PY{n}{dependent}\PY{p}{]}\PY{p}{]}\PY{p}{)} |
||
| 456 | |||
| 457 | \PY{c}{\PYZsh{} Sort by R2} |
||
| 458 | \PY{n}{idx} \PY{o}{=} \PY{n}{np}\PY{o}{.}\PY{n}{argsort}\PY{p}{(}\PY{n}{r2}\PY{p}{)}\PY{p}{[}\PY{p}{:}\PY{p}{:}\PY{o}{\PYZhy{}}\PY{l+m+mi}{1}\PY{p}{]} |
||
| 459 | |||
| 460 | \PY{c}{\PYZsh{} Output string} |
||
| 461 | \PY{n}{s} \PY{o}{=} \PY{l+s}{\PYZdq{}}\PY{l+s+si}{\PYZpc{}d}\PY{l+s}{ significant regressions.}\PY{l+s+se}{\PYZbs{}n}\PY{l+s+se}{\PYZbs{}n}\PY{l+s}{\PYZdq{}} \PY{o}{\PYZpc{}} \PY{n+nb}{len}\PY{p}{(}\PY{n}{r2}\PY{p}{)} |
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| 462 | \PY{n}{s} \PY{o}{+}\PY{o}{=} \PY{l+s}{\PYZdq{}}\PY{l+s}{Ten most correlated :}\PY{l+s+se}{\PYZbs{}n}\PY{l+s+se}{\PYZbs{}n}\PY{l+s}{\PYZdq{}} |
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| 463 | |||
| 464 | \PY{c}{\PYZsh{} Print a summary of the top ten correlations} |
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| 465 | \PY{k}{for} \PY{n}{i} \PY{o+ow}{in} \PY{n}{idx}\PY{p}{[}\PY{p}{:}\PY{l+m+mi}{10}\PY{p}{]} \PY{p}{:} |
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| 466 | \PY{n}{s} \PY{o}{+}\PY{o}{=} \PY{p}{(}\PY{l+s}{\PYZdq{}}\PY{l+s+si}{\PYZpc{}s}\PY{l+s}{ \PYZti{} }\PY{l+s+si}{\PYZpc{}s}\PY{l+s+se}{\PYZbs{}n}\PY{l+s}{\PYZdq{}} \PY{o}{\PYZpc{}} \PY{p}{(}\PY{n}{dependent}\PY{p}{[}\PY{n}{i}\PY{p}{]}\PY{p}{,} \PY{l+s}{\PYZdq{}}\PY{l+s}{ + }\PY{l+s}{\PYZdq{}}\PY{o}{.}\PY{n}{join}\PY{p}{(}\PY{n}{mod}\PY{p}{[}\PY{n}{i}\PY{p}{]}\PY{o}{.}\PY{n}{x}\PY{o}{.}\PY{n}{columns}\PY{p}{[}\PY{p}{:}\PY{o}{\PYZhy{}}\PY{l+m+mi}{1}\PY{p}{]}\PY{p}{)}\PY{p}{)}\PY{p}{)} |
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| 467 | \PY{n}{s} \PY{o}{+}\PY{o}{=} \PY{p}{(}\PY{l+s}{\PYZdq{}}\PY{l+s}{R\PYZca{}2 = }\PY{l+s+si}{\PYZpc{}f}\PY{l+s+se}{\PYZbs{}t}\PY{l+s}{p = }\PY{l+s+si}{\PYZpc{}f}\PY{l+s+se}{\PYZbs{}n}\PY{l+s+se}{\PYZbs{}n}\PY{l+s}{\PYZdq{}} \PY{o}{\PYZpc{}} \PY{p}{(}\PY{n}{r2}\PY{p}{[}\PY{n}{i}\PY{p}{]}\PY{p}{,} \PY{n}{p}\PY{p}{[}\PY{n}{i}\PY{p}{]}\PY{p}{)}\PY{p}{)} |
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| 468 | |||
| 469 | \PY{k}{print} \PY{n}{s} |
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| 470 | |||
| 471 | |||
| 472 | |||
| 473 | |||
| 474 | |||
| 475 | |||
| 476 | |||
| 477 | \PY{k}{def} \PY{n+nf}{rstr}\PY{p}{(}\PY{n}{y}\PY{p}{,} \PY{n}{x}\PY{p}{)} \PY{p}{:} |
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| 478 | \PY{n}{formatstr} \PY{o}{=} \PY{l+s}{\PYZdq{}}\PY{l+s+si}{\PYZpc{}s}\PY{l+s}{ \PYZti{} }\PY{l+s}{\PYZdq{}} \PY{o}{\PYZpc{}} \PY{n}{y} |
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| 479 | \PY{k}{for} \PY{n}{i} \PY{o+ow}{in} \PY{n}{x}\PY{p}{[}\PY{p}{:}\PY{o}{\PYZhy{}}\PY{l+m+mi}{1}\PY{p}{]} \PY{p}{:} |
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| 480 | \PY{n}{formatstr} \PY{o}{+}\PY{o}{=} \PY{n+nb}{str}\PY{p}{(}\PY{n}{i}\PY{p}{)} |
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| 481 | \PY{n}{formatstr} \PY{o}{+}\PY{o}{=} \PY{l+s}{\PYZdq{}}\PY{l+s}{ + }\PY{l+s}{\PYZdq{}} |
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| 482 | \PY{n}{formatstr} \PY{o}{+}\PY{o}{=} \PY{n+nb}{str}\PY{p}{(}\PY{n}{x}\PY{p}{[}\PY{o}{\PYZhy{}}\PY{l+m+mi}{1}\PY{p}{]}\PY{p}{)} |
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| 483 | \PY{k}{return} \PY{n}{formatstr} |
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| 484 | \end{Verbatim} |
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| 485 | |||
| 486 | \begin{Verbatim}[commandchars=\\\{\}] |
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| 487 | {\color{incolor}In [{\color{incolor}14}]:} \PY{k+kn}{import} \PY{n+nn}{numpy} \PY{k+kn}{as} \PY{n+nn}{np} |
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| 488 | \PY{k+kn}{from} \PY{n+nn}{sklearn.neighbors} \PY{k+kn}{import} \PY{n}{KernelDensity} |
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| 489 | \PY{k+kn}{from} \PY{n+nn}{matplotlib} \PY{k+kn}{import} \PY{n}{rcParams} |
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| 490 | \PY{k+kn}{import} \PY{n+nn}{matplotlib.pyplot} \PY{k+kn}{as} \PY{n+nn}{plt} |
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| 491 | \PY{k+kn}{import} \PY{n+nn}{seaborn} |
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| 492 | \PY{k+kn}{import} \PY{n+nn}{pandas} \PY{k+kn}{as} \PY{n+nn}{pd} |
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| 493 | \PY{k+kn}{import} \PY{n+nn}{itertools} |
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| 494 | \PY{k+kn}{from} \PY{n+nn}{sklearn} \PY{k+kn}{import} \PY{n}{linear\PYZus{}model}\PY{p}{,} \PY{n}{ensemble}\PY{p}{,} \PY{n}{decomposition}\PY{p}{,} \PY{n}{cross\PYZus{}validation}\PY{p}{,} \PY{n}{preprocessing} |
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| 495 | \PY{k+kn}{from} \PY{n+nn}{statsmodels.regression.mixed\PYZus{}linear\PYZus{}model} \PY{k+kn}{import} \PY{n}{MixedLM} |
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| 496 | \PY{k+kn}{import} \PY{n+nn}{statsmodels.api} \PY{k+kn}{as} \PY{n+nn}{sm} |
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| 497 | \PY{k+kn}{from} \PY{n+nn}{statsmodels.regression.linear\PYZus{}model} \PY{k+kn}{import} \PY{n}{OLSResults} |
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| 498 | \PY{k+kn}{from} \PY{n+nn}{statsmodels.tools.tools} \PY{k+kn}{import} \PY{n}{add\PYZus{}constant} |
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| 499 | |||
| 500 | |||
| 501 | \PY{o}{\PYZpc{}}\PY{k}{matplotlib} \PY{n}{inline} |
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| 502 | \PY{n}{rcParams}\PY{p}{[}\PY{l+s}{\PYZdq{}}\PY{l+s}{figure.figsize}\PY{l+s}{\PYZdq{}}\PY{p}{]} \PY{o}{=} \PY{p}{(}\PY{l+m+mi}{14}\PY{p}{,} \PY{l+m+mi}{8}\PY{p}{)} |
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| 503 | |||
| 504 | |||
| 505 | \PY{c}{\PYZsh{} RAW DATA} |
||
| 506 | |||
| 507 | \PY{n}{raw\PYZus{}physical} \PY{o}{=} \PY{n}{pd}\PY{o}{.}\PY{n}{read\PYZus{}csv}\PY{p}{(}\PY{l+s}{\PYZdq{}}\PY{l+s}{../data/physical.csv}\PY{l+s}{\PYZdq{}}\PY{p}{)} |
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| 508 | \PY{n}{raw\PYZus{}histo} \PY{o}{=} \PY{n}{pd}\PY{o}{.}\PY{n}{read\PYZus{}csv}\PY{p}{(}\PY{l+s}{\PYZdq{}}\PY{l+s}{../data/tawfik.csv}\PY{l+s}{\PYZdq{}}\PY{p}{)} |
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| 509 | \PY{n}{ent} \PY{o}{=} \PY{n}{pd}\PY{o}{.}\PY{n}{read\PYZus{}csv}\PY{p}{(}\PY{l+s}{\PYZdq{}}\PY{l+s}{../4x/results/entropy.csv}\PY{l+s}{\PYZdq{}}\PY{p}{)}\PY{o}{.}\PY{n}{drop}\PY{p}{(}\PY{p}{[}\PY{l+s}{\PYZdq{}}\PY{l+s}{Unnamed: 0}\PY{l+s}{\PYZdq{}}\PY{p}{]}\PY{p}{,} \PY{l+m+mi}{1}\PY{p}{)} |
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| 510 | \PY{n}{foci} \PY{o}{=} \PY{n}{pd}\PY{o}{.}\PY{n}{read\PYZus{}csv}\PY{p}{(}\PY{l+s}{\PYZdq{}}\PY{l+s}{../4x/results/foci.csv}\PY{l+s}{\PYZdq{}}\PY{p}{)}\PY{o}{.}\PY{n}{drop}\PY{p}{(}\PY{p}{[}\PY{l+s}{\PYZdq{}}\PY{l+s}{Unnamed: 0}\PY{l+s}{\PYZdq{}}\PY{p}{]}\PY{p}{,} \PY{l+m+mi}{1}\PY{p}{)} |
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| 511 | \PY{n}{lac} \PY{o}{=} \PY{n}{pd}\PY{o}{.}\PY{n}{read\PYZus{}csv}\PY{p}{(}\PY{l+s}{\PYZdq{}}\PY{l+s}{../4x/results/normalised\PYZus{}lacunarity.csv}\PY{l+s}{\PYZdq{}}\PY{p}{)}\PY{o}{.}\PY{n}{drop}\PY{p}{(}\PY{p}{[}\PY{l+s}{\PYZdq{}}\PY{l+s}{Unnamed: 0}\PY{l+s}{\PYZdq{}}\PY{p}{]}\PY{p}{,} \PY{l+m+mi}{1}\PY{p}{)} |
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| 512 | \PY{n}{gabor} \PY{o}{=} \PY{n}{pd}\PY{o}{.}\PY{n}{read\PYZus{}csv}\PY{p}{(}\PY{l+s}{\PYZdq{}}\PY{l+s}{../4x/results/gabor\PYZus{}filters.csv}\PY{l+s}{\PYZdq{}}\PY{p}{)}\PY{o}{.}\PY{n}{drop}\PY{p}{(}\PY{p}{[}\PY{l+s}{\PYZdq{}}\PY{l+s}{Unnamed: 0}\PY{l+s}{\PYZdq{}}\PY{p}{]}\PY{p}{,} \PY{l+m+mi}{1}\PY{p}{)} |
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| 513 | \PY{n}{ts} \PY{o}{=} \PY{n}{pd}\PY{o}{.}\PY{n}{read\PYZus{}csv}\PY{p}{(}\PY{l+s}{\PYZdq{}}\PY{l+s}{../4x/results/tissue\PYZus{}sinusoid\PYZus{}ratio.csv}\PY{l+s}{\PYZdq{}}\PY{p}{)}\PY{o}{.}\PY{n}{drop}\PY{p}{(}\PY{p}{[}\PY{l+s}{\PYZdq{}}\PY{l+s}{Unnamed: 0}\PY{l+s}{\PYZdq{}}\PY{p}{]}\PY{p}{,} \PY{l+m+mi}{1}\PY{p}{)} |
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| 514 | |||
| 515 | \PY{n}{raw\PYZus{}image} \PY{o}{=} \PY{n}{pd}\PY{o}{.}\PY{n}{merge}\PY{p}{(}\PY{n}{lac}\PY{p}{,} \PY{n}{ent}\PY{p}{,} |
||
| 516 | \PY{n}{on}\PY{o}{=}\PY{p}{[}\PY{l+s}{\PYZdq{}}\PY{l+s}{Sheep}\PY{l+s}{\PYZdq{}}\PY{p}{,} \PY{l+s}{\PYZdq{}}\PY{l+s}{Image}\PY{l+s}{\PYZdq{}}\PY{p}{]}\PY{p}{)}\PY{o}{.}\PY{n}{merge}\PY{p}{(}\PY{n}{foci}\PY{p}{,} |
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| 517 | \PY{n}{on}\PY{o}{=}\PY{p}{[}\PY{l+s}{\PYZdq{}}\PY{l+s}{Sheep}\PY{l+s}{\PYZdq{}}\PY{p}{,} \PY{l+s}{\PYZdq{}}\PY{l+s}{Image}\PY{l+s}{\PYZdq{}}\PY{p}{]}\PY{p}{)}\PY{o}{.}\PY{n}{merge}\PY{p}{(}\PY{n}{gabor}\PY{p}{,} |
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| 518 | \PY{n}{on}\PY{o}{=}\PY{p}{[}\PY{l+s}{\PYZdq{}}\PY{l+s}{Sheep}\PY{l+s}{\PYZdq{}}\PY{p}{,} \PY{l+s}{\PYZdq{}}\PY{l+s}{Image}\PY{l+s}{\PYZdq{}}\PY{p}{]}\PY{p}{)}\PY{o}{.}\PY{n}{merge}\PY{p}{(}\PY{n}{ts}\PY{p}{,} |
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| 519 | \PY{n}{on}\PY{o}{=}\PY{p}{[}\PY{l+s}{\PYZdq{}}\PY{l+s}{Sheep}\PY{l+s}{\PYZdq{}}\PY{p}{,} \PY{l+s}{\PYZdq{}}\PY{l+s}{Image}\PY{l+s}{\PYZdq{}}\PY{p}{]}\PY{p}{)} |
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| 520 | \PY{n}{raw\PYZus{}image}\PY{o}{.}\PY{n}{rename}\PY{p}{(}\PY{n}{columns} \PY{o}{=} \PY{p}{\PYZob{}} \PY{l+s}{\PYZdq{}}\PY{l+s}{meanSize}\PY{l+s}{\PYZdq{}} \PY{p}{:} \PY{l+s}{\PYZdq{}}\PY{l+s}{FociSize}\PY{l+s}{\PYZdq{}}\PY{p}{,} |
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| 521 | \PY{l+s}{\PYZdq{}}\PY{l+s}{TSRatio}\PY{l+s}{\PYZdq{}} \PY{p}{:} \PY{l+s}{\PYZdq{}}\PY{l+s}{TissueToSinusoid}\PY{l+s}{\PYZdq{}}\PY{p}{,} |
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| 522 | \PY{l+s}{\PYZdq{}}\PY{l+s}{Count}\PY{l+s}{\PYZdq{}} \PY{p}{:} \PY{l+s}{\PYZdq{}}\PY{l+s}{FociCount}\PY{l+s}{\PYZdq{}} \PY{p}{\PYZcb{}}\PY{p}{,} \PY{n}{inplace}\PY{o}{=}\PY{n+nb+bp}{True}\PY{p}{)} |
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| 523 | |||
| 524 | |||
| 525 | |||
| 526 | \PY{c}{\PYZsh{} CLEAN DATA} |
||
| 527 | |||
| 528 | \PY{n}{physcols} \PY{o}{=} \PY{p}{[}\PY{l+s}{\PYZdq{}}\PY{l+s}{Weight}\PY{l+s}{\PYZdq{}}\PY{p}{,} \PY{l+s}{\PYZdq{}}\PY{l+s}{Sex}\PY{l+s}{\PYZdq{}}\PY{p}{,} \PY{l+s}{\PYZdq{}}\PY{l+s}{AgeAtDeath}\PY{l+s}{\PYZdq{}}\PY{p}{,} \PY{l+s}{\PYZdq{}}\PY{l+s}{Foreleg}\PY{l+s}{\PYZdq{}}\PY{p}{,} \PY{l+s}{\PYZdq{}}\PY{l+s}{Hindleg}\PY{l+s}{\PYZdq{}}\PY{p}{]} |
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| 529 | \PY{n}{imagecols} \PY{o}{=} \PY{p}{[}\PY{l+s}{\PYZdq{}}\PY{l+s}{Entropy}\PY{l+s}{\PYZdq{}}\PY{p}{,} \PY{l+s}{\PYZdq{}}\PY{l+s}{Lacunarity}\PY{l+s}{\PYZdq{}}\PY{p}{,} \PY{l+s}{\PYZdq{}}\PY{l+s}{Inflammation}\PY{l+s}{\PYZdq{}}\PY{p}{,} \PY{l+s}{\PYZdq{}}\PY{l+s}{Scale}\PY{l+s}{\PYZdq{}}\PY{p}{,} \PY{l+s}{\PYZdq{}}\PY{l+s}{Directionality}\PY{l+s}{\PYZdq{}}\PY{p}{,} \PY{l+s}{\PYZdq{}}\PY{l+s}{FociCount}\PY{l+s}{\PYZdq{}}\PY{p}{,} \PY{l+s}{\PYZdq{}}\PY{l+s}{FociSize}\PY{l+s}{\PYZdq{}}\PY{p}{,} \PY{l+s}{\PYZdq{}}\PY{l+s}{TissueToSinusoid}\PY{l+s}{\PYZdq{}}\PY{p}{]} |
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| 530 | \PY{n}{histcols} \PY{o}{=} \PY{p}{[}\PY{l+s}{\PYZdq{}}\PY{l+s}{Lobular\PYZus{}collapse}\PY{l+s}{\PYZdq{}}\PY{p}{,} \PY{l+s}{\PYZdq{}}\PY{l+s}{Interface\PYZus{}hepatitis}\PY{l+s}{\PYZdq{}}\PY{p}{,} \PY{l+s}{\PYZdq{}}\PY{l+s}{Confluent\PYZus{}necrosis}\PY{l+s}{\PYZdq{}}\PY{p}{,} \PY{l+s}{\PYZdq{}}\PY{l+s}{Ln\PYZus{}ap\PYZus{}ri}\PY{l+s}{\PYZdq{}}\PY{p}{,} \PY{l+s}{\PYZdq{}}\PY{l+s}{Portal\PYZus{}inflammation}\PY{l+s}{\PYZdq{}}\PY{p}{,} \PY{l+s}{\PYZdq{}}\PY{l+s}{BD\PYZus{}hyperplasia}\PY{l+s}{\PYZdq{}}\PY{p}{,} \PY{l+s}{\PYZdq{}}\PY{l+s}{Fibrosis}\PY{l+s}{\PYZdq{}}\PY{p}{,} \PY{l+s}{\PYZdq{}}\PY{l+s}{TawfikTotal}\PY{l+s}{\PYZdq{}}\PY{p}{,} \PY{l+s}{\PYZdq{}}\PY{l+s}{Mean\PYZus{}hep\PYZus{}size}\PY{l+s}{\PYZdq{}}\PY{p}{,} \PY{l+s}{\PYZdq{}}\PY{l+s}{Min\PYZus{}hep\PYZus{}size}\PY{l+s}{\PYZdq{}}\PY{p}{,} \PY{l+s}{\PYZdq{}}\PY{l+s}{Max\PYZus{}hep\PYZus{}size}\PY{l+s}{\PYZdq{}}\PY{p}{]} |
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| 531 | |||
| 532 | |||
| 533 | |||
| 534 | |||
| 535 | |||
| 536 | \PY{c}{\PYZsh{} IMAGE} |
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| 537 | |||
| 538 | \PY{c}{\PYZsh{} Set FociSize to zero if FociCount is zero} |
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| 539 | \PY{c}{\PYZsh{} Drop stdSize} |
||
| 540 | \PY{n}{image} \PY{o}{=} \PY{n}{raw\PYZus{}image} |
||
| 541 | \PY{n}{image} \PY{o}{=} \PY{n}{image}\PY{o}{.}\PY{n}{drop}\PY{p}{(}\PY{l+s}{\PYZdq{}}\PY{l+s}{stdSize}\PY{l+s}{\PYZdq{}}\PY{p}{,} \PY{l+m+mi}{1}\PY{p}{)} |
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| 542 | \PY{n}{image}\PY{o}{.}\PY{n}{FociSize}\PY{p}{[}\PY{n}{raw\PYZus{}image}\PY{o}{.}\PY{n}{FociCount} \PY{o}{==} \PY{l+m+mi}{0}\PY{p}{]} \PY{o}{=} \PY{l+m+mi}{0} |
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| 543 | |||
| 544 | |||
| 545 | |||
| 546 | \PY{c}{\PYZsh{} HISTO} |
||
| 547 | |||
| 548 | \PY{n}{histo} \PY{o}{=} \PY{n}{raw\PYZus{}histo} |
||
| 549 | \PY{n}{histo} \PY{o}{=} \PY{n}{histo}\PY{o}{.}\PY{n}{drop}\PY{p}{(}\PY{p}{[}\PY{l+s}{\PYZdq{}}\PY{l+s}{Vessels}\PY{l+s}{\PYZdq{}}\PY{p}{,} \PY{l+s}{\PYZdq{}}\PY{l+s}{Vacuol}\PY{l+s}{\PYZdq{}}\PY{p}{,} \PY{l+s}{\PYZdq{}}\PY{l+s}{Pigment}\PY{l+s}{\PYZdq{}}\PY{p}{,} \PY{l+s}{\PYZdq{}}\PY{l+s}{Std\PYZus{}hep\PYZus{}size}\PY{l+s}{\PYZdq{}}\PY{p}{]}\PY{p}{,} \PY{l+m+mi}{1}\PY{p}{)} |
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| 550 | |||
| 551 | |||
| 552 | |||
| 553 | \PY{c}{\PYZsh{} PHYSICAL} |
||
| 554 | |||
| 555 | \PY{n}{physical} \PY{o}{=} \PY{n}{raw\PYZus{}physical} |
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| 556 | \PY{n}{physical} \PY{o}{=} \PY{n}{physical}\PY{o}{.}\PY{n}{drop}\PY{p}{(}\PY{p}{[}\PY{l+s}{\PYZdq{}}\PY{l+s}{CurrTag}\PY{l+s}{\PYZdq{}}\PY{p}{,} \PY{l+s}{\PYZdq{}}\PY{l+s}{DeathDate}\PY{l+s}{\PYZdq{}}\PY{p}{,} \PY{l+s}{\PYZdq{}}\PY{l+s}{Category}\PY{l+s}{\PYZdq{}}\PY{p}{]}\PY{p}{,} \PY{l+m+mi}{1}\PY{p}{)} |
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| 557 | \PY{n}{physical} |
||
| 558 | |||
| 559 | |||
| 560 | |||
| 561 | |||
| 562 | \PY{c}{\PYZsh{} COMPLETE DATASET} |
||
| 563 | |||
| 564 | \PY{n}{raw\PYZus{}data} \PY{o}{=} \PY{n}{pd}\PY{o}{.}\PY{n}{merge}\PY{p}{(}\PY{n}{pd}\PY{o}{.}\PY{n}{merge}\PY{p}{(}\PY{n}{image}\PY{p}{,} \PY{n}{histo}\PY{p}{,} \PY{n}{on}\PY{o}{=}\PY{l+s}{\PYZdq{}}\PY{l+s}{Sheep}\PY{l+s}{\PYZdq{}}\PY{p}{,} \PY{n}{how}\PY{o}{=}\PY{l+s}{\PYZdq{}}\PY{l+s}{outer}\PY{l+s}{\PYZdq{}}\PY{p}{)}\PY{p}{,} \PY{n}{physical}\PY{p}{,} \PY{n}{on}\PY{o}{=}\PY{l+s}{\PYZdq{}}\PY{l+s}{Sheep}\PY{l+s}{\PYZdq{}}\PY{p}{,} \PY{n}{how}\PY{o}{=}\PY{l+s}{\PYZdq{}}\PY{l+s}{outer}\PY{l+s}{\PYZdq{}}\PY{p}{)} |
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| 565 | \PY{n}{raw\PYZus{}data}\PY{o}{.}\PY{n}{to\PYZus{}csv}\PY{p}{(}\PY{l+s}{\PYZdq{}}\PY{l+s}{../data/tentative\PYZus{}complete.csv}\PY{l+s}{\PYZdq{}}\PY{p}{)} |
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| 566 | |||
| 567 | |||
| 568 | |||
| 569 | |||
| 570 | \PY{c}{\PYZsh{} AVERAGED BY SHEEP} |
||
| 571 | \PY{n}{data} \PY{o}{=} \PY{n}{raw\PYZus{}data} |
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| 572 | \PY{n}{data}\PY{p}{[}\PY{l+s}{\PYZdq{}}\PY{l+s}{Inflammation}\PY{l+s}{\PYZdq{}}\PY{p}{]} \PY{o}{=} \PY{n}{data}\PY{o}{.}\PY{n}{FociCount} \PY{o}{*} \PY{n}{data}\PY{o}{.}\PY{n}{FociSize} |
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| 573 | |||
| 574 | \PY{n}{sheep} \PY{o}{=} \PY{n}{rescale}\PY{p}{(}\PY{n}{data}\PY{o}{.}\PY{n}{groupby}\PY{p}{(}\PY{l+s}{\PYZdq{}}\PY{l+s}{Sheep}\PY{l+s}{\PYZdq{}}\PY{p}{)}\PY{o}{.}\PY{n}{mean}\PY{p}{(}\PY{p}{)}\PY{p}{)} |
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| 575 | \PY{n}{age} \PY{o}{=} \PY{n}{rescale}\PY{p}{(}\PY{n}{data}\PY{o}{.}\PY{n}{groupby}\PY{p}{(}\PY{l+s}{\PYZdq{}}\PY{l+s}{AgeAtDeath}\PY{l+s}{\PYZdq{}}\PY{p}{)}\PY{o}{.}\PY{n}{mean}\PY{p}{(}\PY{p}{)}\PY{p}{)} |
||
| 576 | |||
| 577 | |||
| 578 | |||
| 579 | |||
| 580 | |||
| 581 | |||
| 582 | |||
| 583 | \PY{c}{\PYZsh{} REGRESSIONS : fixed effects, grouped by sheep} |
||
| 584 | |||
| 585 | \PY{n}{df} \PY{o}{=} \PY{n}{sheep}\PY{p}{[}\PY{p}{[}\PY{l+s}{\PYZdq{}}\PY{l+s}{Portal\PYZus{}inflammation}\PY{l+s}{\PYZdq{}}\PY{p}{,} \PY{l+s}{\PYZdq{}}\PY{l+s}{FociSize}\PY{l+s}{\PYZdq{}}\PY{p}{]}\PY{p}{]}\PY{o}{.}\PY{n}{dropna}\PY{p}{(}\PY{p}{)} |
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| 586 | \PY{n}{df}\PY{p}{[}\PY{l+s}{\PYZdq{}}\PY{l+s}{Intercept}\PY{l+s}{\PYZdq{}}\PY{p}{]} \PY{o}{=} \PY{n}{np}\PY{o}{.}\PY{n}{ones}\PY{p}{(}\PY{n+nb}{len}\PY{p}{(}\PY{n}{df}\PY{p}{)}\PY{p}{)} |
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| 587 | \PY{n}{portal\PYZus{}inflammation} \PY{o}{=} \PY{n}{sm}\PY{o}{.}\PY{n}{GLS}\PY{p}{(}\PY{n}{endog} \PY{o}{=} \PY{n}{df}\PY{o}{.}\PY{n}{Portal\PYZus{}inflammation}\PY{p}{,} \PY{n}{exog} \PY{o}{=} \PY{n}{df}\PY{p}{[}\PY{p}{[}\PY{l+s}{\PYZdq{}}\PY{l+s}{FociSize}\PY{l+s}{\PYZdq{}}\PY{p}{,} \PY{l+s}{\PYZdq{}}\PY{l+s}{Intercept}\PY{l+s}{\PYZdq{}}\PY{p}{]}\PY{p}{]}\PY{p}{)}\PY{o}{.}\PY{n}{fit}\PY{p}{(}\PY{p}{)}\PY{o}{.}\PY{n}{summary}\PY{p}{(}\PY{p}{)} |
||
| 588 | \PY{c}{\PYZsh{}portal\PYZus{}inflammation = portal\PYZus{}inflammation.summary()} |
||
| 589 | \PY{k}{del} \PY{n}{portal\PYZus{}inflammation}\PY{o}{.}\PY{n}{tables}\PY{p}{[}\PY{l+m+mi}{2}\PY{p}{]} |
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| 590 | |||
| 591 | |||
| 592 | |||
| 593 | \PY{n}{df} \PY{o}{=} \PY{n}{sheep}\PY{p}{[}\PY{p}{[}\PY{l+s}{\PYZdq{}}\PY{l+s}{BD\PYZus{}hyperplasia}\PY{l+s}{\PYZdq{}}\PY{p}{,} \PY{l+s}{\PYZdq{}}\PY{l+s}{Scale}\PY{l+s}{\PYZdq{}}\PY{p}{,} \PY{l+s}{\PYZdq{}}\PY{l+s}{Directionality}\PY{l+s}{\PYZdq{}}\PY{p}{,} \PY{l+s}{\PYZdq{}}\PY{l+s}{FociSize}\PY{l+s}{\PYZdq{}}\PY{p}{]}\PY{p}{]}\PY{o}{.}\PY{n}{dropna}\PY{p}{(}\PY{p}{)} |
||
| 594 | \PY{n}{df}\PY{p}{[}\PY{l+s}{\PYZdq{}}\PY{l+s}{Intercept}\PY{l+s}{\PYZdq{}}\PY{p}{]} \PY{o}{=} \PY{n}{np}\PY{o}{.}\PY{n}{ones}\PY{p}{(}\PY{n+nb}{len}\PY{p}{(}\PY{n}{df}\PY{p}{)}\PY{p}{)} |
||
| 595 | \PY{n}{hyperplasia} \PY{o}{=} \PY{n}{sm}\PY{o}{.}\PY{n}{GLS}\PY{p}{(}\PY{n}{endog} \PY{o}{=} \PY{n}{df}\PY{o}{.}\PY{n}{BD\PYZus{}hyperplasia}\PY{p}{,} \PY{n}{exog} \PY{o}{=} \PY{n}{df}\PY{p}{[}\PY{p}{[}\PY{l+s}{\PYZdq{}}\PY{l+s}{FociSize}\PY{l+s}{\PYZdq{}}\PY{p}{,} \PY{l+s}{\PYZdq{}}\PY{l+s}{Scale}\PY{l+s}{\PYZdq{}}\PY{p}{,} \PY{l+s}{\PYZdq{}}\PY{l+s}{Directionality}\PY{l+s}{\PYZdq{}}\PY{p}{,} \PY{l+s}{\PYZdq{}}\PY{l+s}{Intercept}\PY{l+s}{\PYZdq{}}\PY{p}{]}\PY{p}{]}\PY{p}{)}\PY{o}{.}\PY{n}{fit}\PY{p}{(}\PY{p}{)}\PY{o}{.}\PY{n}{summary}\PY{p}{(}\PY{p}{)} |
||
| 596 | \PY{c}{\PYZsh{}hyperplasia.summary()} |
||
| 597 | \PY{k}{del} \PY{n}{hyperplasia}\PY{o}{.}\PY{n}{tables}\PY{p}{[}\PY{l+m+mi}{2}\PY{p}{]} |
||
| 598 | |||
| 599 | |||
| 600 | |||
| 601 | |||
| 602 | |||
| 603 | |||
| 604 | \PY{c}{\PYZsh{} REGRESSIONS : fixed effects, grouped by age} |
||
| 605 | |||
| 606 | \PY{n}{df} \PY{o}{=} \PY{n}{age}\PY{p}{[}\PY{p}{[}\PY{l+s}{\PYZdq{}}\PY{l+s}{Max\PYZus{}hep\PYZus{}size}\PY{l+s}{\PYZdq{}}\PY{p}{,} \PY{l+s}{\PYZdq{}}\PY{l+s}{Entropy}\PY{l+s}{\PYZdq{}}\PY{p}{,} \PY{l+s}{\PYZdq{}}\PY{l+s}{Directionality}\PY{l+s}{\PYZdq{}}\PY{p}{]}\PY{p}{]}\PY{o}{.}\PY{n}{dropna}\PY{p}{(}\PY{p}{)} |
||
| 607 | \PY{n}{df}\PY{p}{[}\PY{l+s}{\PYZdq{}}\PY{l+s}{Intercept}\PY{l+s}{\PYZdq{}}\PY{p}{]} \PY{o}{=} \PY{n}{np}\PY{o}{.}\PY{n}{ones}\PY{p}{(}\PY{n+nb}{len}\PY{p}{(}\PY{n}{df}\PY{p}{)}\PY{p}{)} |
||
| 608 | \PY{n}{maxhepsize} \PY{o}{=} \PY{n}{sm}\PY{o}{.}\PY{n}{GLS}\PY{p}{(}\PY{n}{endog} \PY{o}{=} \PY{n}{df}\PY{o}{.}\PY{n}{Max\PYZus{}hep\PYZus{}size}\PY{p}{,} \PY{n}{exog} \PY{o}{=} \PY{n}{df}\PY{p}{[}\PY{p}{[}\PY{l+s}{\PYZdq{}}\PY{l+s}{Entropy}\PY{l+s}{\PYZdq{}}\PY{p}{,} \PY{l+s}{\PYZdq{}}\PY{l+s}{Directionality}\PY{l+s}{\PYZdq{}}\PY{p}{,} \PY{l+s}{\PYZdq{}}\PY{l+s}{Intercept}\PY{l+s}{\PYZdq{}}\PY{p}{]}\PY{p}{]}\PY{p}{)}\PY{o}{.}\PY{n}{fit}\PY{p}{(}\PY{p}{)}\PY{o}{.}\PY{n}{summary}\PY{p}{(}\PY{p}{)} |
||
| 609 | \PY{k}{del} \PY{n}{maxhepsize}\PY{o}{.}\PY{n}{tables}\PY{p}{[}\PY{l+m+mi}{2}\PY{p}{]} |
||
| 610 | |||
| 611 | |||
| 612 | |||
| 613 | |||
| 614 | \PY{n}{df} \PY{o}{=} \PY{n}{age}\PY{p}{[}\PY{p}{[}\PY{l+s}{\PYZdq{}}\PY{l+s}{Lobular\PYZus{}collapse}\PY{l+s}{\PYZdq{}}\PY{p}{,} \PY{l+s}{\PYZdq{}}\PY{l+s}{FociSize}\PY{l+s}{\PYZdq{}}\PY{p}{]}\PY{p}{]}\PY{o}{.}\PY{n}{dropna}\PY{p}{(}\PY{p}{)} |
||
| 615 | \PY{n}{df}\PY{p}{[}\PY{l+s}{\PYZdq{}}\PY{l+s}{Intercept}\PY{l+s}{\PYZdq{}}\PY{p}{]} \PY{o}{=} \PY{n}{np}\PY{o}{.}\PY{n}{ones}\PY{p}{(}\PY{n+nb}{len}\PY{p}{(}\PY{n}{df}\PY{p}{)}\PY{p}{)} |
||
| 616 | \PY{n}{lobular\PYZus{}collapse} \PY{o}{=} \PY{n}{sm}\PY{o}{.}\PY{n}{GLS}\PY{p}{(}\PY{n}{endog} \PY{o}{=} \PY{n}{df}\PY{o}{.}\PY{n}{Lobular\PYZus{}collapse}\PY{p}{,} \PY{n}{exog} \PY{o}{=} \PY{n}{df}\PY{p}{[}\PY{p}{[}\PY{l+s}{\PYZdq{}}\PY{l+s}{FociSize}\PY{l+s}{\PYZdq{}}\PY{p}{,} \PY{l+s}{\PYZdq{}}\PY{l+s}{Intercept}\PY{l+s}{\PYZdq{}}\PY{p}{]}\PY{p}{]}\PY{p}{)}\PY{o}{.}\PY{n}{fit}\PY{p}{(}\PY{p}{)}\PY{o}{.}\PY{n}{summary}\PY{p}{(}\PY{p}{)} |
||
| 617 | \PY{k}{del} \PY{n}{lobular\PYZus{}collapse}\PY{o}{.}\PY{n}{tables}\PY{p}{[}\PY{l+m+mi}{2}\PY{p}{]} |
||
| 618 | |||
| 619 | |||
| 620 | \PY{n}{df} \PY{o}{=} \PY{n}{age}\PY{p}{[}\PY{p}{[}\PY{l+s}{\PYZdq{}}\PY{l+s}{Interface\PYZus{}hepatitis}\PY{l+s}{\PYZdq{}}\PY{p}{,} \PY{l+s}{\PYZdq{}}\PY{l+s}{Lacunarity}\PY{l+s}{\PYZdq{}}\PY{p}{]}\PY{p}{]}\PY{o}{.}\PY{n}{dropna}\PY{p}{(}\PY{p}{)} |
||
| 621 | \PY{n}{df}\PY{p}{[}\PY{l+s}{\PYZdq{}}\PY{l+s}{Intercept}\PY{l+s}{\PYZdq{}}\PY{p}{]} \PY{o}{=} \PY{n}{np}\PY{o}{.}\PY{n}{ones}\PY{p}{(}\PY{n+nb}{len}\PY{p}{(}\PY{n}{df}\PY{p}{)}\PY{p}{)} |
||
| 622 | \PY{n}{interface\PYZus{}hepatitis} \PY{o}{=} \PY{n}{sm}\PY{o}{.}\PY{n}{GLS}\PY{p}{(}\PY{n}{endog} \PY{o}{=} \PY{n}{df}\PY{o}{.}\PY{n}{Interface\PYZus{}hepatitis}\PY{p}{,} \PY{n}{exog} \PY{o}{=} \PY{n}{df}\PY{p}{[}\PY{p}{[}\PY{l+s}{\PYZdq{}}\PY{l+s}{Lacunarity}\PY{l+s}{\PYZdq{}}\PY{p}{,} \PY{l+s}{\PYZdq{}}\PY{l+s}{Intercept}\PY{l+s}{\PYZdq{}}\PY{p}{]}\PY{p}{]}\PY{p}{)}\PY{o}{.}\PY{n}{fit}\PY{p}{(}\PY{p}{)}\PY{o}{.}\PY{n}{summary}\PY{p}{(}\PY{p}{)} |
||
| 623 | \PY{k}{del} \PY{n}{interface\PYZus{}hepatitis}\PY{o}{.}\PY{n}{tables}\PY{p}{[}\PY{l+m+mi}{2}\PY{p}{]} |
||
| 624 | |||
| 625 | |||
| 626 | \PY{n}{df} \PY{o}{=} \PY{n}{age}\PY{p}{[}\PY{p}{[}\PY{l+s}{\PYZdq{}}\PY{l+s}{Fibrosis}\PY{l+s}{\PYZdq{}}\PY{p}{,} \PY{l+s}{\PYZdq{}}\PY{l+s}{Inflammation}\PY{l+s}{\PYZdq{}}\PY{p}{]}\PY{p}{]}\PY{o}{.}\PY{n}{dropna}\PY{p}{(}\PY{p}{)} |
||
| 627 | \PY{n}{df}\PY{p}{[}\PY{l+s}{\PYZdq{}}\PY{l+s}{Intercept}\PY{l+s}{\PYZdq{}}\PY{p}{]} \PY{o}{=} \PY{n}{np}\PY{o}{.}\PY{n}{ones}\PY{p}{(}\PY{n+nb}{len}\PY{p}{(}\PY{n}{df}\PY{p}{)}\PY{p}{)} |
||
| 628 | \PY{n}{fibrosis} \PY{o}{=} \PY{n}{sm}\PY{o}{.}\PY{n}{GLS}\PY{p}{(}\PY{n}{endog} \PY{o}{=} \PY{n}{df}\PY{o}{.}\PY{n}{Fibrosis}\PY{p}{,} \PY{n}{exog} \PY{o}{=} \PY{n}{df}\PY{p}{[}\PY{p}{[}\PY{l+s}{\PYZdq{}}\PY{l+s}{Inflammation}\PY{l+s}{\PYZdq{}}\PY{p}{,} \PY{l+s}{\PYZdq{}}\PY{l+s}{Intercept}\PY{l+s}{\PYZdq{}}\PY{p}{]}\PY{p}{]}\PY{p}{)}\PY{o}{.}\PY{n}{fit}\PY{p}{(}\PY{p}{)}\PY{o}{.}\PY{n}{summary}\PY{p}{(}\PY{p}{)} |
||
| 629 | \PY{k}{del} \PY{n}{fibrosis}\PY{o}{.}\PY{n}{tables}\PY{p}{[}\PY{l+m+mi}{2}\PY{p}{]} |
||
| 630 | |||
| 631 | |||
| 632 | |||
| 633 | |||
| 634 | \PY{c}{\PYZsh{} PCA} |
||
| 635 | |||
| 636 | \PY{n}{s} \PY{o}{=} \PY{n}{sheep}\PY{o}{.}\PY{n}{dropna}\PY{p}{(}\PY{n}{subset}\PY{o}{=}\PY{n}{delayer}\PY{p}{(}\PY{p}{[}\PY{n}{imagecols}\PY{p}{,} \PY{n}{histcols}\PY{p}{]}\PY{p}{)}\PY{p}{)} |
||
| 637 | \PY{n}{pca} \PY{o}{=} \PY{n}{decomposition}\PY{o}{.}\PY{n}{PCA}\PY{p}{(}\PY{n}{n\PYZus{}components}\PY{o}{=}\PY{l+m+mi}{1}\PY{p}{)} |
||
| 638 | \PY{n}{pcax} \PY{o}{=} \PY{n}{pca}\PY{o}{.}\PY{n}{fit\PYZus{}transform}\PY{p}{(}\PY{n}{s}\PY{p}{[}\PY{n}{imagecols}\PY{p}{]}\PY{p}{)} |
||
| 639 | \PY{n}{pcay} \PY{o}{=} \PY{n}{pca}\PY{o}{.}\PY{n}{fit\PYZus{}transform}\PY{p}{(}\PY{n}{s}\PY{p}{[}\PY{n}{histcols}\PY{p}{]}\PY{p}{)} |
||
| 640 | \PY{n}{pca} \PY{o}{=} \PY{n}{sm}\PY{o}{.}\PY{n}{GLS}\PY{p}{(}\PY{n}{endog} \PY{o}{=} \PY{n}{pcay}\PY{p}{[}\PY{p}{:}\PY{p}{,} \PY{l+m+mi}{0}\PY{p}{]}\PY{p}{[}\PY{p}{:}\PY{p}{,} \PY{n}{np}\PY{o}{.}\PY{n}{newaxis}\PY{p}{]}\PY{p}{,} \PY{n}{exog} \PY{o}{=} \PY{n}{add\PYZus{}constant}\PY{p}{(}\PY{n}{pcax}\PY{p}{)}\PY{p}{)}\PY{o}{.}\PY{n}{fit}\PY{p}{(}\PY{p}{)}\PY{o}{.}\PY{n}{summary}\PY{p}{(}\PY{p}{)} |
||
| 641 | \PY{k}{del} \PY{n}{pca}\PY{o}{.}\PY{n}{tables}\PY{p}{[}\PY{l+m+mi}{2}\PY{p}{]} |
||
| 642 | |||
| 643 | |||
| 644 | |||
| 645 | |||
| 646 | |||
| 647 | \PY{c}{\PYZsh{} REGRESSIONS : mixed effects, intercept on age at death} |
||
| 648 | |||
| 649 | \PY{n}{df} \PY{o}{=} \PY{n}{age}\PY{p}{[}\PY{p}{[}\PY{l+s}{\PYZdq{}}\PY{l+s}{Fibrosis}\PY{l+s}{\PYZdq{}}\PY{p}{,} \PY{l+s}{\PYZdq{}}\PY{l+s}{Inflammation}\PY{l+s}{\PYZdq{}}\PY{p}{]}\PY{p}{]}\PY{o}{.}\PY{n}{dropna}\PY{p}{(}\PY{p}{)} |
||
| 650 | \PY{n}{df}\PY{p}{[}\PY{l+s}{\PYZdq{}}\PY{l+s}{Intercept}\PY{l+s}{\PYZdq{}}\PY{p}{]} \PY{o}{=} \PY{n}{np}\PY{o}{.}\PY{n}{ones}\PY{p}{(}\PY{n+nb}{len}\PY{p}{(}\PY{n}{df}\PY{p}{)}\PY{p}{)} |
||
| 651 | \PY{n}{fibrosis} \PY{o}{=} \PY{n}{sm}\PY{o}{.}\PY{n}{GLS}\PY{p}{(}\PY{n}{endog} \PY{o}{=} \PY{n}{df}\PY{o}{.}\PY{n}{Fibrosis}\PY{p}{,} \PY{n}{exog} \PY{o}{=} \PY{n}{df}\PY{p}{[}\PY{p}{[}\PY{l+s}{\PYZdq{}}\PY{l+s}{Inflammation}\PY{l+s}{\PYZdq{}}\PY{p}{,} \PY{l+s}{\PYZdq{}}\PY{l+s}{Intercept}\PY{l+s}{\PYZdq{}}\PY{p}{]}\PY{p}{]}\PY{p}{)}\PY{o}{.}\PY{n}{fit}\PY{p}{(}\PY{p}{)}\PY{o}{.}\PY{n}{summary}\PY{p}{(}\PY{p}{)} |
||
| 652 | \PY{k}{del} \PY{n}{fibrosis}\PY{o}{.}\PY{n}{tables}\PY{p}{[}\PY{l+m+mi}{2}\PY{p}{]} |
||
| 653 | \end{Verbatim} |
||
| 654 | |||
| 655 | \begin{Verbatim}[commandchars=\\\{\}] |
||
| 656 | {\color{incolor}In [{\color{incolor}19}]:} \PY{n}{a} \PY{o}{=} \PY{n}{portal\PYZus{}inflammation}\PY{o}{.}\PY{n}{summary}\PY{p}{(}\PY{p}{)} |
||
| 657 | \PY{k}{del} \PY{n}{a}\PY{o}{.}\PY{n}{tables}\PY{p}{[}\PY{l+m+mi}{2}\PY{p}{]} |
||
| 658 | \PY{n}{a} |
||
| 659 | \end{Verbatim} |
||
| 660 | |||
| 661 | \begin{Verbatim}[commandchars=\\\{\}] |
||
| 662 | {\color{outcolor}Out[{\color{outcolor}19}]:} <class 'statsmodels.iolib.summary.Summary'> |
||
| 663 | """ |
||
| 664 | GLS Regression Results |
||
| 665 | =============================================================================== |
||
| 666 | Dep. Variable: Portal\_inflammation R-squared: 0.280 |
||
| 667 | Model: GLS Adj. R-squared: 0.273 |
||
| 668 | Method: Least Squares F-statistic: 37.34 |
||
| 669 | Date: Tue, 28 Oct 2014 Prob (F-statistic): 2.12e-08 |
||
| 670 | Time: 23:35:30 Log-Likelihood: 14.996 |
||
| 671 | No. Observations: 98 AIC: -25.99 |
||
| 672 | Df Residuals: 96 BIC: -20.82 |
||
| 673 | Df Model: 1 |
||
| 674 | Covariance Type: nonrobust |
||
| 675 | ============================================================================== |
||
| 676 | coef std err t P>|t| [95.0\% Conf. Int.] |
||
| 677 | ------------------------------------------------------------------------------ |
||
| 678 | FociSize 0.5627 0.092 6.111 0.000 0.380 0.746 |
||
| 679 | Intercept 0.3368 0.043 7.855 0.000 0.252 0.422 |
||
| 680 | ============================================================================== |
||
| 681 | |||
| 682 | Warnings: |
||
| 683 | [1] Standard Errors assume that the covariance matrix of the errors is correctly specified. |
||
| 684 | """ |
||
| 685 | \end{Verbatim} |
||
| 686 | |||
| 687 | |||
| 688 | \subsection{Image Processing} |
||
| 689 | |||
| 690 | |||
| 691 | |||
| 692 | |||
| 693 | |||
| 694 | |||
| 695 | |||
| 696 | \subsubsection{Extraction} |
||
| 697 | |||
| 698 | |||
| 699 | \begin{itemize} |
||
| 700 | \itemsep1pt\parskip0pt\parsep0pt |
||
| 701 | \item |
||
| 702 | Automagical |
||
| 703 | \item |
||
| 704 | Reasonably quick |
||
| 705 | \end{itemize} |
||
| 706 | |||
| 707 | |||
| 708 | \subsubsection{Robust} |
||
| 709 | |||
| 710 | |||
| 711 | \begin{itemize} |
||
| 712 | \itemsep1pt\parskip0pt\parsep0pt |
||
| 713 | \item |
||
| 714 | Invariant to staining, slicing, field-related variation |
||
| 715 | \item |
||
| 716 | Capture intersample variation |
||
| 717 | \end{itemize} |
||
| 718 | |||
| 719 | \begin{figure}[htbp] |
||
| 720 | \centering |
||
| 721 | \includegraphics{figures/robust3.jpg} |
||
| 722 | \caption{image} |
||
| 723 | \end{figure} |
||
| 724 | |||
| 725 | \begin{figure}[htbp] |
||
| 726 | \centering |
||
| 727 | \includegraphics{figures/robust4.jpg} |
||
| 728 | \caption{image} |
||
| 729 | \end{figure} |
||
| 730 | |||
| 731 | \begin{figure}[htbp] |
||
| 732 | \centering |
||
| 733 | \includegraphics{figures/robust1.jpg} |
||
| 734 | \caption{image} |
||
| 735 | \end{figure} |
||
| 736 | |||
| 737 | \begin{figure}[htbp] |
||
| 738 | \centering |
||
| 739 | \includegraphics{figures/robust2.jpg} |
||
| 740 | \caption{image} |
||
| 741 | \end{figure} |
||
| 742 | |||
| 743 | |||
| 744 | \subsection{Structural and Textural Measures} |
||
| 745 | |||
| 746 | |||
| 747 | \begin{itemize} |
||
| 748 | \itemsep1pt\parskip0pt\parsep0pt |
||
| 749 | \item |
||
| 750 | characteristic \textbf{scale} of sinusoid widths |
||
| 751 | \item |
||
| 752 | \textbf{directional} amplitude of preferred sinusoid alignment |
||
| 753 | \item |
||
| 754 | \textbf{tissue to sinusoid} ratio |
||
| 755 | \item |
||
| 756 | \textbf{count} of inflammatory foci per image |
||
| 757 | \item |
||
| 758 | \textbf{mean size} of inflammatory foci per image |
||
| 759 | \item |
||
| 760 | information \textbf{entropy} of sinusoid distribution |
||
| 761 | \item |
||
| 762 | \textbf{lacunarity} ( clustering ) of sinusoids |
||
| 763 | \end{itemize} |
||
| 764 | |||
| 765 | |||
| 766 | |||
| 767 | \begin{figure}[htbp] |
||
| 768 | \centering |
||
| 769 | \includegraphics{figures/intra.png} |
||
| 770 | \caption{image} |
||
| 771 | \end{figure} |
||
| 772 | |||
| 773 | \begin{figure}[htbp] |
||
| 774 | \centering |
||
| 775 | \includegraphics{figures/inter2.png} |
||
| 776 | \caption{image} |
||
| 777 | \end{figure} |
||
| 778 | |||
| 779 | |||
| 780 | \subsection{Exploratory Analysis} |
||
| 781 | |||
| 782 | |||
| 783 | |||
| 784 | \subsubsection{by individual} |
||
| 785 | |||
| 786 | |||
| 787 | \begin{Verbatim}[commandchars=\\\{\}] |
||
| 788 | {\color{incolor}In [{\color{incolor}29}]:} \PY{n}{portal\PYZus{}inflammation} |
||
| 789 | \end{Verbatim} |
||
| 790 | |||
| 791 | \begin{Verbatim}[commandchars=\\\{\}] |
||
| 792 | {\color{outcolor}Out[{\color{outcolor}29}]:} <class 'statsmodels.iolib.summary.Summary'> |
||
| 793 | """ |
||
| 794 | GLS Regression Results |
||
| 795 | =============================================================================== |
||
| 796 | Dep. Variable: Portal\_inflammation R-squared: 0.280 |
||
| 797 | Model: GLS Adj. R-squared: 0.273 |
||
| 798 | Method: Least Squares F-statistic: 37.34 |
||
| 799 | Date: Tue, 28 Oct 2014 Prob (F-statistic): 2.12e-08 |
||
| 800 | Time: 23:40:10 Log-Likelihood: 14.996 |
||
| 801 | No. Observations: 98 AIC: -25.99 |
||
| 802 | Df Residuals: 96 BIC: -20.82 |
||
| 803 | Df Model: 1 |
||
| 804 | Covariance Type: nonrobust |
||
| 805 | ============================================================================== |
||
| 806 | coef std err t P>|t| [95.0\% Conf. Int.] |
||
| 807 | ------------------------------------------------------------------------------ |
||
| 808 | FociSize 0.5627 0.092 6.111 0.000 0.380 0.746 |
||
| 809 | Intercept 0.3368 0.043 7.855 0.000 0.252 0.422 |
||
| 810 | ============================================================================== |
||
| 811 | |||
| 812 | Warnings: |
||
| 813 | [1] Standard Errors assume that the covariance matrix of the errors is correctly specified. |
||
| 814 | """ |
||
| 815 | \end{Verbatim} |
||
| 816 | |||
| 817 | \begin{figure}[htbp] |
||
| 818 | \centering |
||
| 819 | \includegraphics{figures/portal_inflammation.png} |
||
| 820 | \caption{image} |
||
| 821 | \end{figure} |
||
| 822 | |||
| 823 | \begin{Verbatim}[commandchars=\\\{\}] |
||
| 824 | {\color{incolor}In [{\color{incolor}31}]:} \PY{n}{hyperplasia} |
||
| 825 | \end{Verbatim} |
||
| 826 | |||
| 827 | \begin{Verbatim}[commandchars=\\\{\}] |
||
| 828 | {\color{outcolor}Out[{\color{outcolor}31}]:} <class 'statsmodels.iolib.summary.Summary'> |
||
| 829 | """ |
||
| 830 | GLS Regression Results |
||
| 831 | ============================================================================== |
||
| 832 | Dep. Variable: BD\_hyperplasia R-squared: 0.306 |
||
| 833 | Model: GLS Adj. R-squared: 0.284 |
||
| 834 | Method: Least Squares F-statistic: 13.83 |
||
| 835 | Date: Tue, 28 Oct 2014 Prob (F-statistic): 1.52e-07 |
||
| 836 | Time: 23:40:10 Log-Likelihood: -3.9632 |
||
| 837 | No. Observations: 98 AIC: 15.93 |
||
| 838 | Df Residuals: 94 BIC: 26.27 |
||
| 839 | Df Model: 3 |
||
| 840 | Covariance Type: nonrobust |
||
| 841 | ================================================================================== |
||
| 842 | coef std err t P>|t| [95.0\% Conf. Int.] |
||
| 843 | ---------------------------------------------------------------------------------- |
||
| 844 | FociSize 0.6698 0.113 5.902 0.000 0.444 0.895 |
||
| 845 | Scale 0.5811 0.243 2.394 0.019 0.099 1.063 |
||
| 846 | Directionality -0.4419 0.190 -2.330 0.022 -0.819 -0.065 |
||
| 847 | Intercept -0.0504 0.079 -0.642 0.523 -0.206 0.105 |
||
| 848 | ================================================================================== |
||
| 849 | |||
| 850 | Warnings: |
||
| 851 | [1] Standard Errors assume that the covariance matrix of the errors is correctly specified. |
||
| 852 | """ |
||
| 853 | \end{Verbatim} |
||
| 854 | |||
| 855 | \begin{figure}[htbp] |
||
| 856 | \centering |
||
| 857 | \includegraphics{figures/hyperplasia.png} |
||
| 858 | \caption{image} |
||
| 859 | \end{figure} |
||
| 860 | |||
| 861 | \begin{Verbatim}[commandchars=\\\{\}] |
||
| 862 | {\color{incolor}In [{\color{incolor}15}]:} \PY{n}{pca} |
||
| 863 | \end{Verbatim} |
||
| 864 | |||
| 865 | \begin{Verbatim}[commandchars=\\\{\}] |
||
| 866 | {\color{outcolor}Out[{\color{outcolor}15}]:} <class 'statsmodels.iolib.summary.Summary'> |
||
| 867 | """ |
||
| 868 | GLS Regression Results |
||
| 869 | ============================================================================== |
||
| 870 | Dep. Variable: y R-squared: 0.075 |
||
| 871 | Model: GLS Adj. R-squared: 0.065 |
||
| 872 | Method: Least Squares F-statistic: 7.723 |
||
| 873 | Date: Wed, 29 Oct 2014 Prob (F-statistic): 0.00657 |
||
| 874 | Time: 14:38:47 Log-Likelihood: -70.082 |
||
| 875 | No. Observations: 97 AIC: 144.2 |
||
| 876 | Df Residuals: 95 BIC: 149.3 |
||
| 877 | Df Model: 1 |
||
| 878 | Covariance Type: nonrobust |
||
| 879 | ============================================================================== |
||
| 880 | coef std err t P>|t| [95.0\% Conf. Int.] |
||
| 881 | ------------------------------------------------------------------------------ |
||
| 882 | const -2.949e-17 0.051 -5.77e-16 1.000 -0.102 0.102 |
||
| 883 | x1 0.3865 0.139 2.779 0.007 0.110 0.663 |
||
| 884 | ============================================================================== |
||
| 885 | |||
| 886 | Warnings: |
||
| 887 | [1] Standard Errors assume that the covariance matrix of the errors is correctly specified. |
||
| 888 | """ |
||
| 889 | \end{Verbatim} |
||
| 890 | |||
| 891 | \begin{figure}[htbp] |
||
| 892 | \centering |
||
| 893 | \includegraphics{figures/pca.png} |
||
| 894 | \caption{image} |
||
| 895 | \end{figure} |
||
| 896 | |||
| 897 | |||
| 898 | \subsection{Exploratory Analysis} |
||
| 899 | |||
| 900 | |||
| 901 | |||
| 902 | \subsubsection{by age class} |
||
| 903 | |||
| 904 | |||
| 905 | \begin{Verbatim}[commandchars=\\\{\}] |
||
| 906 | {\color{incolor}In [{\color{incolor}6}]:} \PY{n}{fibrosis} |
||
| 907 | \end{Verbatim} |
||
| 908 | |||
| 909 | \begin{Verbatim}[commandchars=\\\{\}] |
||
| 910 | {\color{outcolor}Out[{\color{outcolor}6}]:} <class 'statsmodels.iolib.summary.Summary'> |
||
| 911 | """ |
||
| 912 | GLS Regression Results |
||
| 913 | ============================================================================== |
||
| 914 | Dep. Variable: Fibrosis R-squared: 0.800 |
||
| 915 | Model: GLS Adj. R-squared: 0.778 |
||
| 916 | Method: Least Squares F-statistic: 36.07 |
||
| 917 | Date: Wed, 29 Oct 2014 Prob (F-statistic): 0.000201 |
||
| 918 | Time: 11:13:48 Log-Likelihood: 7.8003 |
||
| 919 | No. Observations: 11 AIC: -11.60 |
||
| 920 | Df Residuals: 9 BIC: -10.80 |
||
| 921 | Df Model: 1 |
||
| 922 | Covariance Type: nonrobust |
||
| 923 | ================================================================================ |
||
| 924 | coef std err t P>|t| [95.0\% Conf. Int.] |
||
| 925 | -------------------------------------------------------------------------------- |
||
| 926 | Inflammation 1.0159 0.169 6.006 0.000 0.633 1.399 |
||
| 927 | Intercept -0.0105 0.083 -0.126 0.902 -0.198 0.177 |
||
| 928 | ================================================================================ |
||
| 929 | |||
| 930 | Warnings: |
||
| 931 | [1] Standard Errors assume that the covariance matrix of the errors is correctly specified. |
||
| 932 | """ |
||
| 933 | \end{Verbatim} |
||
| 934 | |||
| 935 | \begin{figure}[htbp] |
||
| 936 | \centering |
||
| 937 | \includegraphics{figures/fibrosis.png} |
||
| 938 | \caption{image} |
||
| 939 | \end{figure} |
||
| 940 | |||
| 941 | \begin{Verbatim}[commandchars=\\\{\}] |
||
| 942 | {\color{incolor}In [{\color{incolor}7}]:} \PY{n}{lobular\PYZus{}collapse} |
||
| 943 | \end{Verbatim} |
||
| 944 | |||
| 945 | \begin{Verbatim}[commandchars=\\\{\}] |
||
| 946 | {\color{outcolor}Out[{\color{outcolor}7}]:} <class 'statsmodels.iolib.summary.Summary'> |
||
| 947 | """ |
||
| 948 | GLS Regression Results |
||
| 949 | ============================================================================== |
||
| 950 | Dep. Variable: Lobular\_collapse R-squared: 0.586 |
||
| 951 | Model: GLS Adj. R-squared: 0.540 |
||
| 952 | Method: Least Squares F-statistic: 12.73 |
||
| 953 | Date: Wed, 29 Oct 2014 Prob (F-statistic): 0.00605 |
||
| 954 | Time: 11:13:48 Log-Likelihood: 2.2626 |
||
| 955 | No. Observations: 11 AIC: -0.5252 |
||
| 956 | Df Residuals: 9 BIC: 0.2706 |
||
| 957 | Df Model: 1 |
||
| 958 | Covariance Type: nonrobust |
||
| 959 | ============================================================================== |
||
| 960 | coef std err t P>|t| [95.0\% Conf. Int.] |
||
| 961 | ------------------------------------------------------------------------------ |
||
| 962 | FociSize 1.1379 0.319 3.567 0.006 0.416 1.860 |
||
| 963 | Intercept 0.0460 0.159 0.289 0.779 -0.314 0.406 |
||
| 964 | ============================================================================== |
||
| 965 | |||
| 966 | Warnings: |
||
| 967 | [1] Standard Errors assume that the covariance matrix of the errors is correctly specified. |
||
| 968 | """ |
||
| 969 | \end{Verbatim} |
||
| 970 | |||
| 971 | \begin{figure}[htbp] |
||
| 972 | \centering |
||
| 973 | \includegraphics{figures/lobular_collapse.png} |
||
| 974 | \caption{image} |
||
| 975 | \end{figure} |
||
| 976 | |||
| 977 | \begin{Verbatim}[commandchars=\\\{\}] |
||
| 978 | {\color{incolor}In [{\color{incolor}8}]:} \PY{n}{interface\PYZus{}hepatitis} |
||
| 979 | \end{Verbatim} |
||
| 980 | |||
| 981 | \begin{Verbatim}[commandchars=\\\{\}] |
||
| 982 | {\color{outcolor}Out[{\color{outcolor}8}]:} <class 'statsmodels.iolib.summary.Summary'> |
||
| 983 | """ |
||
| 984 | GLS Regression Results |
||
| 985 | =============================================================================== |
||
| 986 | Dep. Variable: Interface\_hepatitis R-squared: 0.659 |
||
| 987 | Model: GLS Adj. R-squared: 0.621 |
||
| 988 | Method: Least Squares F-statistic: 17.38 |
||
| 989 | Date: Wed, 29 Oct 2014 Prob (F-statistic): 0.00242 |
||
| 990 | Time: 11:13:48 Log-Likelihood: 2.3063 |
||
| 991 | No. Observations: 11 AIC: -0.6126 |
||
| 992 | Df Residuals: 9 BIC: 0.1832 |
||
| 993 | Df Model: 1 |
||
| 994 | Covariance Type: nonrobust |
||
| 995 | ============================================================================== |
||
| 996 | coef std err t P>|t| [95.0\% Conf. Int.] |
||
| 997 | ------------------------------------------------------------------------------ |
||
| 998 | Lacunarity -1.0224 0.245 -4.168 0.002 -1.577 -0.468 |
||
| 999 | Intercept 0.9504 0.143 6.669 0.000 0.628 1.273 |
||
| 1000 | ============================================================================== |
||
| 1001 | |||
| 1002 | Warnings: |
||
| 1003 | [1] Standard Errors assume that the covariance matrix of the errors is correctly specified. |
||
| 1004 | """ |
||
| 1005 | \end{Verbatim} |
||
| 1006 | |||
| 1007 | \begin{figure}[htbp] |
||
| 1008 | \centering |
||
| 1009 | \includegraphics{figures/interface_hepatitis.png} |
||
| 1010 | \caption{image} |
||
| 1011 | \end{figure} |
||
| 1012 | |||
| 1013 | |||
| 1014 | \subsection{Exploratory analysis} |
||
| 1015 | |||
| 1016 | |||
| 1017 | |||
| 1018 | \subsubsection{with a random effect on age at death} |
||
| 1019 | |||
| 1020 | |||
| 1021 | \begin{longtable}[c]{@{}lcl@{}} |
||
| 1022 | \toprule\addlinespace |
||
| 1023 | Dependent variable & Models AIC \textless{} 2 + AICmin & Primary |
||
| 1024 | explanatory variables ( ordered ) |
||
| 1025 | \\\addlinespace |
||
| 1026 | \midrule\endhead |
||
| 1027 | Ishak score & 7 & entropy, tissue-to-sinusoid, focus count, focus size |
||
| 1028 | \\\addlinespace |
||
| 1029 | Lobular collapse & 5 & entropy, lacunarity, tissue-to-sinusoid, focus |
||
| 1030 | count |
||
| 1031 | \\\addlinespace |
||
| 1032 | Confluent necrosis & 1 & entropy |
||
| 1033 | \\\addlinespace |
||
| 1034 | Interface hepatitis & 2 & entropy, tissue-to-sinusoid |
||
| 1035 | \\\addlinespace |
||
| 1036 | Portal inflammation & 4 & entropy, focus size, lacunarity, focus count, |
||
| 1037 | scale, directionality |
||
| 1038 | \\\addlinespace |
||
| 1039 | Fibrosis & 2 & entropy, lacunarity, tissue-to-sinusoid |
||
| 1040 | \\\addlinespace |
||
| 1041 | Biliary hyperplasia & 1 & focus size |
||
| 1042 | \\\addlinespace |
||
| 1043 | Necrosis, apoptosis, random inflammation & 2 & entropy, lacunarity |
||
| 1044 | \\\addlinespace |
||
| 1045 | \bottomrule |
||
| 1046 | \end{longtable} |
||
| 1047 | |||
| 1048 | |||
| 1049 | \paragraph{Measures we like} |
||
| 1050 | |||
| 1051 | |||
| 1052 | \begin{itemize} |
||
| 1053 | \itemsep1pt\parskip0pt\parsep0pt |
||
| 1054 | \item |
||
| 1055 | entropy consistently explains histological measures when controlled |
||
| 1056 | for age |
||
| 1057 | \item |
||
| 1058 | also important : tissue to sinusoid ratio, focus count and size, |
||
| 1059 | lacunarity |
||
| 1060 | \end{itemize} |
||
| 1061 | |||
| 1062 | |||
| 1063 | \subsection{Future directions} |
||
| 1064 | |||
| 1065 | |||
| 1066 | |||
| 1067 | \subsubsection{Further exploration of the dataset} |
||
| 1068 | |||
| 1069 | |||
| 1070 | \begin{itemize} |
||
| 1071 | \item |
||
| 1072 | 145 sheep ( 89 females ) |
||
| 1073 | \item |
||
| 1074 | 11 age classes |
||
| 1075 | \item |
||
| 1076 | \end{itemize} |
||
| 1077 | |||
| 1078 | \begin{itemize} |
||
| 1079 | \itemsep1pt\parskip0pt\parsep0pt |
||
| 1080 | \item |
||
| 1081 | 4460 entries across 27 variables |
||
| 1082 | \item |
||
| 1083 | 3330 with full image and histological information |
||
| 1084 | \item |
||
| 1085 | 1196 for which \textbf{complete} information is available |
||
| 1086 | \end{itemize} |
||
| 1087 | |||
| 1088 | |||
| 1089 | \subsubsection{Narrow-field images} |
||
| 1090 | |||
| 1091 | |||
| 1092 | \begin{itemize} |
||
| 1093 | \itemsep1pt\parskip0pt\parsep0pt |
||
| 1094 | \item |
||
| 1095 | 12536 images |
||
| 1096 | \item |
||
| 1097 | spatial distribution of nuclei |
||
| 1098 | \end{itemize} |
||
| 1099 | |||
| 1100 | \begin{figure}[htbp] |
||
| 1101 | \centering |
||
| 1102 | \includegraphics{figures/10.jpg} |
||
| 1103 | \caption{image} |
||
| 1104 | \end{figure} |
||
| 1105 | |||
| 1106 | \begin{figure}[htbp] |
||
| 1107 | \centering |
||
| 1108 | \includegraphics{figures/Processed2.jpg} |
||
| 1109 | \caption{image} |
||
| 1110 | \end{figure} |
||
| 1111 | |||
| 1112 | \begin{figure}[htbp] |
||
| 1113 | \centering |
||
| 1114 | \includegraphics{figures/Segmented.jpg} |
||
| 1115 | \caption{image} |
||
| 1116 | \end{figure} |
||
| 1117 | |||
| 1118 | |||
| 1119 | |||
| 1120 | |||
| 1121 | % Add a bibliography block to the postdoc |
||
| 1122 | |||
| 1123 | |||
| 1124 | |||
| 1125 | \end{document} |