From ca2ba044b403d73d6a815c2356034ba83051fde6 Mon Sep 17 00:00:00 2001
From: "Frederik J. Simons" <fjsimons@gmail.com>
Date: Thu, 20 Aug 2020 13:26:46 -0400
Subject: [PATCH] Backus-Robin asymptotic approximation of Legendre polynomials

---
 backus.m    |  2 +-
 bindens.m   | 53 --------------------------------------------
 row2stats.m | 64 -----------------------------------------------------
 3 files changed, 1 insertion(+), 118 deletions(-)
 delete mode 100644 bindens.m
 delete mode 100644 row2stats.m

diff --git a/backus.m b/backus.m
index 1a2552d..5ff80ab 100644
--- a/backus.m
+++ b/backus.m
@@ -28,7 +28,7 @@
 %
 % See also DAHLEN, HILBXLM.
 %
-% Last modified by fjsimons-at-alum.mit.edu, 03/16/2016
+% Last modified by fjsimons-at-alum.mit.edu, 03/17/2016
 
 defval('norma','sch')
 defval('N',1000);
diff --git a/bindens.m b/bindens.m
deleted file mode 100644
index 81f18e2..0000000
--- a/bindens.m
+++ /dev/null
@@ -1,53 +0,0 @@
-function [h,c11,cmn,hh,ybine]=bindens(x,y,nxbins,nybins)
-% [h,c11,cmn,hh,ybine]=BINDENS(x,y,nxbins,nybins)
-%
-% Density plot for data in 2D histograms
-%
-% INPUT:
-%
-% x,y              The data vectors
-% nxbins, nybins   The number of bins in the x and y direction
-%
-% OUTPUT:
-%
-% h          The '2D' histogram
-% c11,cmn    The centers of the top left and bottom right of this histogram
-% hh         Globally normalized histogram
-% ybine      The y bin edges that are being used
-%
-% See also ROW2STATS, HIST2D
-%
-% Last modified by fjsimons-at-alum.mit.edu, 03/18/2013
-
-defval('nxbins',10)
-defval('nybins',10)
-defval('xbin',range(x)/nxbins);
-defval('ybin',range(y)/nybins);
-
-% Specify the y-bin edges, that's one more than there are bins
-ybine=linspace(min(y),max(y),nybins+1);
-
-% Sort the data in the first column
-[x,I]=sort(x,1);
-
-% And have the second column follow
-y=y(I);
-
-% Bin the x-data
-ix=ceil((x-min(x))/xbin);
-ix=ix+(ix==0);
-
-% Also must put in nans for the bins that didn't happen
-adix=skip(1:max(ix),unique(ix));
-ix=[ix ; adix(:)];
-y=[y ; nan(size(adix(:)))]; 
-
-% Now use ROW2STATS to get the y-histograms
-[g,s,h,hh]=row2stats(ix,y,ybine);
-
-% Do not do flipud as the histogram treats the bins as one-sided to the
-% right but rather find the pixel-centered coordinates of the histogram?
-c11(1)=min(x)+xbin/2;
-cmn(1)=max(x)-xbin/2;
-c11(2)=min(y)+ybin/2;
-cmn(2)=max(y)-ybin/2;
diff --git a/row2stats.m b/row2stats.m
deleted file mode 100644
index 8864182..0000000
--- a/row2stats.m
+++ /dev/null
@@ -1,64 +0,0 @@
-function [g,s,h,hh]=row2stats(col1,col2,ybine)
-% [g,s,h,hh]=ROW2STATS(col1,col2,ybine)
-%
-% Find statistics of data presented belonging to different groups
-%
-% INPUT:
-%
-% col1    The first column of data of which groups are made 
-% col2    The second column of data 
-% ybine   The bin edges to make histograms of the second data column
-%
-% OUTPUT:
-%
-% g       The different groups identified in the first data column
-% s       Structure array with mean, median, etc of data per group 
-% h       Matrix with histogram counts per group in the bins provided
-% hh      Matrix with histogram counts globally normalized
-% 
-% See also BINDENS 
-%
-% Last modified by fjsimons-at-alum.mit.edu, 12/21/2011
-
-defval('nybins',10)
-defval('ybin',range(col2)/nybins);
-defval('ybine',linspace(min(col2),max(col2),nybins+1));
-
-% Sort the data in the first column
-[col1,I]=sort(col1,1);
-% And have the second column follow
-col2=col2(I);
-% The beginning index of every new value in column 1
-beg=[1 find(diff([col1(1) col1(:)']))];
-% The ending index of every separate magnitude
-ent=[beg(2:end)-1 length(col1)];
-
-% Now collect statistics of the values in column 2
-for index=1:length(beg)
-  coli=beg(index):ent(index);
-  % Identify the category in the first column
-  g(index)=col1(beg(index));
-  % Identify the element of the second column
-  colrel=col2(coli);
-  % Construct the statistics of the second column
-  s.mean(index)=nanmean(colrel);
-  s.median(index)=nanmedian(colrel);
-  s.nonnans(index)=sum(~isnan(colrel));
-  s.variance(index)=nanvar(colrel);
-  s.p25(index)=prctile(colrel,25);
-  s.p75(index)=prctile(colrel,75);
-  if nargout>2
-    h(:,index)=histc(colrel,ybine);
-    hh(:,index)=h(:,index);
-    h(:,index)=h(:,index)/sum(h(:,index));
-  end
-end
-
-if nargout>2
-  % Now remember the oddity about the HISTC bins
-  h(end-1,:)=h(end-1,:)+h(end,:);
-  h=h(1:end-1,:);
-  hh(end-1,:)=hh(end-1,:)+hh(end,:);
-  hh=hh(1:end-1,:);
-end
-