From c87c0a95649ed795ae15f343b5a7ce98645e4dc5 Mon Sep 17 00:00:00 2001
From: Blaise Thompson <blaise@untzag.com>
Date: Thu, 22 Mar 2018 22:11:26 -0500
Subject: 2018-03-22 22:11

---
 dissertation.cls       |   4 +++-
 dissertation.pdf       | Bin 1252765 -> 1255941 bytes
 processing/chapter.tex |  45 +++++++++++++++++++++++++++++++++++++++++++++
 3 files changed, 48 insertions(+), 1 deletion(-)

diff --git a/dissertation.cls b/dissertation.cls
index 4e8adc8..3769526 100644
--- a/dissertation.cls
+++ b/dissertation.cls
@@ -86,7 +86,7 @@
 \usemintedstyle{colorfuli}
 \setminted[python]{linenos=false, frame=none}
 
-\definecolor{bg}{rgb}{0.95,0.95,0.95}
+\definecolor{bg}{rgb}{0.95, 0.95, 0.95}
 
 \setmintedinline[python]{bgcolor=bg}
 
@@ -100,6 +100,8 @@
   arc=0,
   shadow=false,
   boxsep=1ex, top=0pt, left=0pt, right=0pt, bottom=0pt,
+  title={\hfill(\arabic{chapter}.\arabic{equation})},
+  list entry={\hfill(\arabic{chapter}.\arabic{equation})},
   comment={\hfill(\arabic{chapter}.\arabic{equation})},
   listing outside comment,
   righthand width=2.5em,
diff --git a/dissertation.pdf b/dissertation.pdf
index 2371c9c..6db6bd2 100644
Binary files a/dissertation.pdf and b/dissertation.pdf differ
diff --git a/processing/chapter.tex b/processing/chapter.tex
index 3225624..72d1d27 100644
--- a/processing/chapter.tex
+++ b/processing/chapter.tex
@@ -281,6 +281,51 @@ Also consider using the fit sub-package.  % TODO: more info, link to section
 
 Chop is one of the most important methods of data, although it is typically not called directly by
 users of WrightTools.  %
+Chop takes n-dimensional data and ``chops'' it into all of it's lower dimensional components.  %
+Consider a 3D dataset in \python{('wm', 'w2', 'w1')}.  %
+This dataset can be chopped to it's component 2D \python{('wm', 'w1')} spectra.  %
+\begin{codefragment}{python, label=test_label}
+>>> import WrightTools as wt; from WrightTools import datasets
+>>> data = wt.data.from_PyCMDS(datasets.PyCMDS.wm_w2_w1_000)
+data created at /tmp/lzyjg4au.wt5::/
+  axes ('wm', 'w2', 'w1')
+  shape (35, 11, 11)
+>>> chopped = data.chop('wm', 'w1')  
+chopped data into 11 piece(s) in ('wm', 'w1')
+>>> chopped.chop000
+<WrightTools.Data 'chop000' ('wm', 'w1') at /tmp/935c2v5a.wt5::/chop000>
+\end{codefragment}
+\python{chopped} is a collection containing 11 data objects: \python{chop000, chop001 ...
+  chop010}.  %
+Note that, by default, the collection is made at the root level of a new tempfile.  %
+An optional keyword argument \python{parent} allows users to specify the destination for this new
+collection.   %
+These lower dimensional data objects can then be used in plotting routines, fitting routines etc.  %
+
+By default, chop returns \emph{all} of the lower dimensional slices.  %
+Considering the same data object from \autoref{test_label}, we can choose to get all 1D wm
+slices.  %
+\begin{codefragment}{python}
+>>> chopped = data.chop('wm')
+chopped data into 121 piece(s) in ('wm',)
+>>> chopped.chop000
+<WrightTools.Data 'chop000' ('wm',) at /tmp/pqkbc0qr.wt5::/chop000>
+\end{codefragment}
+
+If desired, users may use the \python{at} keyword argument to specify a particular coordinate in
+the un-retained dimensions.  %
+For example, suppose that you want to plot the data from \ref{test_label} as an wm, w1 plot at
+w2 = 1580 wn.  %
+\begin{codefragment}{python}
+>>> chopped = data.chop('wm', 'w1', at={'w2': [1580, 'wn']})[0]
+chopped data into 1 piece(s) in ('wm', 'w1')
+>>> chopped
+<WrightTools.Data 'chop000' ('wm', 'w1') at /tmp/_yhrdprp.wt5::/chop000>
+>>> chopped.w2.points
+array([1580.0])
+\end{codefragment}
+Note the [0]...  % TODO
+This same syntax used in artists...  % TODO
 
 \subsubsection{Collapse}
 
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