MILWAUKEE – Nov. 9, 2004 – TEKLYNX® International, the world’s arch developer of software articles for the AIDC marketplace, today appear LABEL MATRIX® 7.02, the aboriginal characterization architecture software to be certified by the Uniform Cipher Council’s Band-aid Software Program. New LABEL MATRIX version also adds bar code symbologies/printer drivers. MILWAUKEE - Nov. 9, 2004 - TEKLYNX® International, the world's leading developer of software products for the AIDC marketplace, today announced LABEL MATRIX® 7.02, the first label design software to be certified by the Uniform Code Council's Solution Software Program.
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| *! version 7.02 24nov2013 Michael Stepner, stepner@mit.edu |
| /* CC0 license information: |
| To the extent possible under law, the author has dedicated all copyright and related and neighboring rights |
| to this software to the public domain worldwide. This software is distributed without any warranty. |
| This code is licensed under the CC0 1.0 Universal license. The full legal text as well as a |
| human-readable summary can be accessed at http://creativecommons.org/publicdomain/zero/1.0/ |
| */ |
| * Why did I include a formal license? Jeff Atwood gives good reasons: http://www.codinghorror.com/blog/2007/04/pick-a-license-any-license.html |
| program define binscatter, eclass sortpreserve |
| version 12.1 |
| syntax varlist(min=2 numeric) [if] [in] [aweight fweight], [by(varname) /// |
| Nquantiles(integer 20) GENxq(name) discrete xq(varname numeric) MEDians /// |
| CONTROLs(varlist numeric ts fv) absorb(varname) noAddmean /// |
| LINEtype(string) rd(numlist ascending) reportreg /// |
| COLors(string) MColors(string) LColors(string) Msymbols(string) /// |
| savegraph(string) savedata(string) replace /// |
| nofastxtile randvar(varname numeric) randcut(real 1) randn(integer -1) /// |
| /* LEGACY OPTIONS */ nbins(integer 20) create_xq x_q(varname numeric) symbols(string) method(string) unique(string) /// |
| *] |
| set more off |
| * Create convenient weight local |
| if ('`weight''!='') local wt [`weight'`exp'] |
| ***** Begin legacy option compatibility code |
| if (`nbins'!=20) { |
| if (`nquantiles'!=20) { |
| di as error 'Cannot specify both nquantiles() and nbins(): both are the same option, nbins is supported only for backward compatibility.' |
| exit |
| } |
| di as text 'NOTE: legacy option nbins() has been renamed nquantiles(), and is supported only for backward compatibility.' |
| local nquantiles=`nbins' |
| } |
| if ('`create_xq''!='') { |
| if ('`genxq''!='') { |
| di as error 'Cannot specify both genxq() and create_xq: both are the same option, create_xq is supported only for backward compatibility.' |
| exit |
| } |
| di as text 'NOTE: legacy option create_xq has been renamed genxq(), and is supported only for backward compatibility.' |
| local genxq='q_'+word('`varlist'',-1) |
| } |
| if ('`x_q''!='') { |
| if ('`xq''!='') { |
| di as error 'Cannot specify both xq() and x_q(): both are the same option, x_q() is supported only for backward compatibility.' |
| exit |
| } |
| di as text 'NOTE: legacy option x_q() has been renamed xq(), and is supported only for backward compatibility.' |
| local xq `x_q' |
| } |
| if ('`symbols''!='') { |
| if ('`msymbols''!='') { |
| di as error 'Cannot specify both msymbols() and symbols(): both are the same option, symbols() is supported only for backward compatibility.' |
| exit |
| } |
| di as text 'NOTE: legacy option symbols() has been renamed msymbols(), and is supported only for backward compatibility.' |
| local msymbols `symbols' |
| } |
| if ('`linetype'''noline') { |
| di as text 'NOTE: legacy line type 'noline' has been renamed 'none', and is supported only for backward compatibility.' |
| local linetype none |
| } |
| if ('`method''!='') { |
| di as text 'NOTE: method() is no longer a recognized option, and will be ignored. binscatter now always uses the fastest method without a need for two instances' |
| } |
| if ('`unique''!='') { |
| di as text 'NOTE: unique() is no longer a recognized option, and will be ignored. binscatter now considers the x-variable discrete if it has fewer unique values than nquantiles()' |
| } |
| ***** End legacy option capatibility code |
| *** Perform checks |
| * Set default linetype and check valid |
| if ('`linetype'''') local linetype lfit |
| else if!inlist('`linetype'','connect','lfit','qfit','none') { |
| di as error 'linetype() must either be connect, lfit, qfit, or none' |
| exit |
| } |
| * Check that nofastxtile isn't combined with fastxtile-only options |
| if'`fastxtile'''nofastxtile'& ('`randvar''!=''| `randcut'!=1 | `randn'!=-1) { |
| di as error 'Cannot combine randvar, randcut or randn with nofastxtile' |
| exit |
| } |
| * Misc checks |
| if ('`genxq''!=''& ('`xq''!=''|'`discrete''!='')) | ('`xq''!=''&'`discrete''!='') { |
| di as error 'Cannot specify more than one of genxq(), xq(), and discrete simultaneously.' |
| exit |
| } |
| if ('`genxq''!='') confirm new variable `genxq' |
| if ('`xq''!='') { |
| capture assert `xq'int(`xq') & `xq'>0 |
| if _rc!=0 { |
| di as error 'xq() must contain only positive integers.' |
| exit |
| } |
| if ('`controls'`absorb''!='') di as text 'warning: xq() is specified in combination with controls() or absorb(). note that binning takes places after residualization, so the xq variable should contain bins of the residuals.' |
| } |
| if `nquantiles'!=20 & ('`xq''!=''|'`discrete''!='') { |
| di as error 'Cannot specify nquantiles in combination with discrete or an xq variable.' |
| exit |
| } |
| if'`reportreg''!=''&!inlist('`linetype'','lfit','qfit') { |
| di as error 'Cannot specify 'reportreg' when no fit line is being created.' |
| exit |
| } |
| if'`replace'''' { |
| if`'`savegraph''!='' { |
| if regexm(`'`savegraph'','.[a-zA-Z0-9]+$') confirm new file `'`savegraph'' |
| else confirm new file `'`savegraph'.gph' |
| } |
| if`'`savedata''!='' { |
| confirm new file `'`savedata'.csv' |
| confirm new file `'`savedata'.do' |
| } |
| } |
| * Mark sample (reflects the if/in conditions, and includes only nonmissing observations) |
| marksample touse |
| markout `touse' `by' `xq' `controls' `absorb', strok |
| qui count if `touse' |
| local samplesize=r(N) |
| local touse_first=_N-`samplesize'+1 |
| local touse_last=_N |
| * Parse varlist into y-vars and x-var |
| local x_var=word('`varlist'',-1) |
| local y_vars=regexr('`varlist'',' `x_var'$','') |
| local ynum=wordcount('`y_vars'') |
| * Check number of unique byvals & create local storing byvals |
| if'`by''!='' { |
| local byvarname `by' |
| capture confirm numeric variable `by' |
| if _rc { |
| * by-variable is string => generate a numeric version |
| tempvar by |
| tempname bylabel |
| egen `by'=group(`byvarname'), lname(`bylabel') |
| } |
| local bylabel `:value label `by' /*catch value labels for numeric by-vars too*/ |
| tempname byvalmatrix |
| qui tab `by' if `touse', nofreq matrow(`byvalmatrix') |
| local bynum=r(r) |
| forvalues i=1/`bynum' { |
| local byvals `byvals' `=`byvalmatrix'[`i',1]' |
| } |
| } |
| else local bynum=1 |
| ****** Create residuals ****** |
| if (`'`controls'`absorb''!='') quietly { |
| * Parse absorb to define the type of regression to be used |
| if`'`absorb''!='' { |
| local regtype 'areg' |
| local absorb 'absorb(`absorb')' |
| } |
| else { |
| local regtype 'reg' |
| } |
| * Generate residuals |
| local firstloop=1 |
| foreach var of varlist `x_var' `y_vars' { |
| tempvar residvar |
| `regtype' `var' `controls' `wt' if `touse', `absorb' |
| predict `residvar' if e(sample), residuals |
| if ('`addmean''!='noaddmean') { |
| summarize `var' `wt' if `touse', meanonly |
| replace `residvar'=`residvar'+r(mean) |
| } |
| label variable `residvar' '`var'' |
| if `firstloop'1 { |
| local x_r `residvar' |
| local firstloop=0 |
| } |
| else local y_vars_r `y_vars_r' `residvar' |
| } |
| } |
| else { /*absorb and controls both empty, no need for regression*/ |
| local x_r `x_var' |
| local y_vars_r `y_vars' |
| } |
| ****** Regressions for fit lines ****** |
| if ('`reportreg'''') local reg_verbosity 'quietly' |
| if inlist('`linetype'','lfit','qfit') `reg_verbosity' { |
| * If doing a quadratic fit, generate a quadratic term in x |
| if'`linetype'''qfit' { |
| tempvar x_r2 |
| gen `x_r2'=`x_r'^2 |
| } |
| * Create matrices to hold regression results |
| tempname e_b_temp |
| forvalues i=1/`ynum' { |
| tempname y`i'_coefs |
| } |
| * LOOP over by-vars |
| local counter_by=1 |
| if ('`by'''') local noby='noby' |
| foreach byval in `byvals' `noby' { |
| * LOOP over rd intervals |
| tokenize '`rd'' |
| local counter_rd=1 |
| while ('`1''!=''| `counter_rd'1) { |
| * display text headers |
| if'`reportreg''!='' { |
| di '{txt}{hline}' |
| if ('`by''!='') { |
| if ('`bylabel'''') di '-> `byvarname' = `byval'' |
| else { |
| di '-> `byvarname' = `: label `bylabel' `byval'' |
| } |
| } |
| if ('`rd''!='') { |
| if (`counter_rd'1) di 'RD: `x_var'<=`1'' |
| else if ('`2''!='') di 'RD: `x_var'>`1' & `x_var'<=`2'' |
| else di 'RD: `x_var'>`1'' |
| } |
| } |
| * set conditions on reg |
| local conds `touse' |
| if ('`by''!='' ) local conds `conds' & `by'`byval' |
| if ('`rd''!='') { |
| if (`counter_rd'1) local conds `conds' & `x_r'<=`1' |
| else if ('`2''!='') local conds `conds' & `x_r'>`1' & `x_r'<=`2' |
| else local conds `conds' & `x_r'>`1' |
| } |
| * LOOP over y-vars |
| local counter_depvar=1 |
| foreach depvar of varlist `y_vars_r' { |
| * display text headers |
| if (`ynum'>1) { |
| if ('`controls'`absorb''!='') local depvar_name : var label `depvar' |
| else local depvar_name `depvar' |
| di as text '{bf:y_var = `depvar_name'}' |
| } |
| * perform regression |
| if ('`reg_verbosity'''quietly') capture reg `depvar' `x_r2' `x_r' `wt' if `conds' |
| else capture noisily reg `depvar' `x_r2' `x_r' `wt' if `conds' |
| * store results |
| if (_rc0) matrix e_b_temp=e(b) |
| else if (_rc2000) { |
| if ('`reg_verbosity'''quietly') di as error 'no observations for one of the fit lines. add 'reportreg' for more info.' |
| if ('`linetype'''lfit') matrix e_b_temp=.,. |
| else/*('`linetype''qfit')*/ matrix e_b_temp=.,.,. |
| } |
| else { |
| error _rc |
| exit _rc |
| } |
| * relabel matrix row |
| if ('`by''!='') matrix roweq e_b_temp ='by`counter_by'' |
| if ('`rd''!='') matrix rownames e_b_temp ='rd`counter_rd'' |
| else matrix rownames e_b_temp ='=' |
| * save to y_var matrix |
| if (`counter_by'1 & `counter_rd'1) matrix `y`counter_depvar'_coefs'=e_b_temp |
| else matrix `y`counter_depvar'_coefs'=`y`counter_depvar'_coefs' e_b_temp |
| * increment depvar counter |
| local++counter_depvar |
| } |
| * increment rd counter |
| if (`counter_rd'!=1) mac shift |
| local++counter_rd |
| } |
| * increment by counter |
| local++counter_by |
| } |
| * relabel matrix column names |
| forvalues i=1/`ynum' { |
| if ('`linetype'''lfit') matrix colnames `y`i'_coefs' ='`x_var'''_cons' |
| else if ('`linetype'''qfit') matrix colnames `y`i'_coefs' ='`x_var'^2''`x_var'''_cons' |
| } |
| } |
| ******* Define the bins ******* |
| * Specify and/or create the xq var, as necessary |
| if'`xq'''' { |
| if!(`touse_first'1 & word('`:sortedby'',1)'`x_r'') sort `touse' `x_r' |
| if'`discrete'''' { /* xq() and discrete are not specified */ |
| * Check whether the number of unique values > nquantiles, or <= nquantiles |
| capture mata: characterize_unique_vals_sorted('`x_r'',`touse_first',`touse_last',`nquantiles') |
| if (_rc0) { /* number of unique values <= nquantiles, set to discrete */ |
| local discrete discrete |
| if ('`genxq''!='') di as text `'note: the x-variable has fewer unique values than the number of bins specified (`nquantiles'). It will therefore be treated as discrete, and genxq() will be ignored' |
| local xq `x_r' |
| local nquantiles=r(r) |
| if ('`by'''') { |
| tempname xq_boundaries xq_values |
| matrix `xq_boundaries'=r(boundaries) |
| matrix `xq_values'=r(values) |
| } |
| } |
| else if (_rc134) { /* number of unique values > nquantiles, perform binning */ |
| if ('`genxq''!='') local xq `genxq' |
| else tempvar xq |
| if ('`fastxtile''!='nofastxtile') fastxtile `xq' = `x_r' `wt' in `touse_first'/`touse_last', nq(`nquantiles') randvar(`randvar') randcut(`randcut') randn(`randn') |
| else xtile `xq' = `x_r' `wt' in `touse_first'/`touse_last', nq(`nquantiles') |
| if ('`by'''') { |
| mata: characterize_unique_vals_sorted('`xq'',`touse_first',`touse_last',`nquantiles') |
| if (r(r)!=`nquantiles') { |
| di as text 'warning: nquantiles(`nquantiles') was specified, but only `r(r)' were generated. see help file under nquantiles() for explanation.' |
| local nquantiles=r(r) |
| } |
| tempname xq_boundaries xq_values |
| matrix `xq_boundaries'=r(boundaries) |
| matrix `xq_values'=r(values) |
| } |
| } |
| else { |
| error _rc |
| } |
| } |
| else { /* discrete is specified, xq() & genxq() are not */ |
| if ('`controls'`absorb''!='') di as text 'warning: discrete is specified in combination with controls() or absorb(). note that binning takes places after residualization, so the residualized x-variable may contain many more unique values.' |
| capture mata: characterize_unique_vals_sorted('`x_r'',`touse_first',`touse_last',`=`samplesize'/2') |
| if (_rc0) { |
| local xq `x_r' |
| local nquantiles=r(r) |
| if ('`by'''') { |
| tempname xq_boundaries xq_values |
| matrix `xq_boundaries'=r(boundaries) |
| matrix `xq_values'=r(values) |
| } |
| } |
| else if (_rc134) { |
| di as error 'discrete specified, but number of unique values is > (sample size/2)' |
| exit 134 |
| } |
| else { |
| error _rc |
| } |
| } |
| } |
| else { |
| if!(`touse_first'1 & word('`:sortedby'',1)'`xq'') sort `touse' `xq' |
| * set nquantiles & boundaries |
| mata: characterize_unique_vals_sorted('`xq'',`touse_first',`touse_last',`=`samplesize'/2') |
| if (_rc0) { |
| local nquantiles=r(r) |
| if ('`by'''') { |
| tempname xq_boundaries xq_values |
| matrix `xq_boundaries'=r(boundaries) |
| matrix `xq_values'=r(values) |
| } |
| } |
| else if (_rc134) { |
| di as error 'discrete specified, but number of unique values is > (sample size/2)' |
| exit 134 |
| } |
| else { |
| error _rc |
| } |
| } |
| ********** Compute scatter points ********** |
| if ('`by''!='') { |
| sort `touse' `by' `xq' |
| tempname by_boundaries |
| mata: characterize_unique_vals_sorted('`by'',`touse_first',`touse_last',`bynum') |
| matrix `by_boundaries'=r(boundaries) |
| } |
| forvalues b=1/`bynum' { |
| if ('`by''!='') { |
| mata: characterize_unique_vals_sorted('`xq'',`=`by_boundaries'[`b',1]',`=`by_boundaries'[`b',2]',`nquantiles') |
| tempname xq_boundaries xq_values |
| matrix `xq_boundaries'=r(boundaries) |
| matrix `xq_values'=r(values) |
| } |
| /* otherwise xq_boundaries and xq_values are defined above in the binning code block */ |
| * Define x-means |
| tempname xbin_means |
| if ('`discrete'''discrete') { |
| matrix `xbin_means'=`xq_values' |
| } |
| else { |
| means_in_boundaries `x_r' `wt', bounds(`xq_boundaries') `medians' |
| matrix `xbin_means'=r(means) |
| } |
| * LOOP over y-vars to define y-means |
| local counter_depvar=0 |
| foreach depvar of varlist `y_vars_r' { |
| local++counter_depvar |
| means_in_boundaries `depvar' `wt', bounds(`xq_boundaries') `medians' |
| * store to matrix |
| if (`b'1) { |
| tempname y`counter_depvar'_scatterpts |
| matrix `y`counter_depvar'_scatterpts' = `xbin_means',r(means) |
| } |
| else { |
| * make matrices conformable before right appending |
| local rowdiff=rowsof(`y`counter_depvar'_scatterpts')-rowsof(`xbin_means') |
| if (`rowdiff'0) matrix `y`counter_depvar'_scatterpts' = `y`counter_depvar'_scatterpts',`xbin_means',r(means) |
| else if (`rowdiff'>0) matrix `y`counter_depvar'_scatterpts' = `y`counter_depvar'_scatterpts', ( (`xbin_means',r(means)) J(`rowdiff',2,.) ) |
| else/*(`rowdiff'<0)*/ matrix `y`counter_depvar'_scatterpts' = ( `y`counter_depvar'_scatterpts' J(-`rowdiff',colsof(`y`counter_depvar'_scatterpts'),.) ) ,`xbin_means',r(means) |
| } |
| } |
| } |
| *********** Perform Graphing *********** |
| * If rd is specified, prepare xline parameters |
| if'`rd''!='' { |
| foreach xval in'`rd'' { |
| local xlines `xlines' xline(`xval', lpattern(dash) lcolor(gs8)) |
| } |
| } |
| * Fill colors if missing |
| if`'`colors'''' local colors /// |
| navy maroon forest_green dkorange teal cranberry lavender /// |
| khaki sienna emidblue emerald brown erose gold bluishgray /// |
| /* lime magenta cyan pink blue */ |
| if`'`mcolors'''' { |
| if (`ynum'1 & `bynum'1 &'`linetype''!='connect') local mcolors `: word 1 of `colors' |
| else local mcolors `colors' |
| } |
| if`'`lcolors'''' { |
| if (`ynum'1 & `bynum'1 &'`linetype''!='connect') local lcolors `: word 2 of `colors' |
| else local lcolors `colors' |
| } |
| local num_mcolor=wordcount(`'`mcolors'') |
| local num_lcolor=wordcount(`'`lcolors'') |
| * Prepare connect & msymbol options |
| if ('`linetype'''connect') local connect 'c(l)' |
| if'`msymbols''!='' { |
| local symbol_prefix 'msymbol(' |
| local symbol_suffix ')' |
| } |
| *** Prepare scatters |
| * c indexes which color is to be used |
| local c=0 |
| local counter_series=0 |
| * LOOP over by-vars |
| local counter_by=0 |
| if ('`by'''') local noby='noby' |
| foreach byval in `byvals' `noby' { |
| local++counter_by |
| local xind=`counter_by'*2-1 |
| local yind=`counter_by'*2 |
| * LOOP over y-vars |
| local counter_depvar=0 |
| foreach depvar of varlist `y_vars' { |
| local++counter_depvar |
| local++c |
| * LOOP over rows (each row contains a coordinate pair) |
| local row=1 |
| local xval=`y`counter_depvar'_scatterpts'[`row',`xind'] |
| local yval=`y`counter_depvar'_scatterpts'[`row',`yind'] |
| if!missing(`xval',`yval') { |
| local++counter_series |
| local scatters `scatters' (scatteri |
| if ('`savedata''!='') { |
| if ('`by'''') local savedata_scatters `savedata_scatters' (scatter `depvar' `x_var' |
| else local savedata_scatters `savedata_scatters' (scatter `depvar'_by`counter_by' `x_var'_by`counter_by' |
| } |
| } |
| else { |
| * skip the rest of this loop iteration |
| continue |
| } |
| while (`xval'!=. & `yval'!=.) { |
| local scatters `scatters' `yval' `xval' |
| local++row |
| local xval=`y`counter_depvar'_scatterpts'[`row',`xind'] |
| local yval=`y`counter_depvar'_scatterpts'[`row',`yind'] |
| } |
| * Add options |
| local scatter_options `connect' mcolor(`: word `c' of `mcolors') lcolor(`: word `c' of `lcolors') `symbol_prefix'`: word `c' of `msymbols'`symbol_suffix' |
| local scatters `scatters', `scatter_options') |
| if ('`savedata''!='') local savedata_scatters `savedata_scatters', `scatter_options') |
| * Add legend |
| if'`by'''' { |
| if (`ynum'1) local legend_labels off |
| else local legend_labels `legend_labels' lab(`counter_series' `depvar') |
| } |
| else { |
| if ('`bylabel'''') local byvalname=`byval' |
| else { |
| local byvalname `: label `bylabel' `byval' |
| } |
| if (`ynum'1) local legend_labels `legend_labels' lab(`counter_series' `byvarname'=`byvalname') |
| else local legend_labels `legend_labels' lab(`counter_series' `depvar': `byvarname'=`byvalname') |
| } |
| if ('`by''!=''| `ynum'>1) local order `order' `counter_series' |
| } |
| } |
| *** Fit lines |
| if inlist(`'`linetype'','lfit','qfit') { |
| * c indexes which color is to be used |
| local c=0 |
| local rdnum=wordcount('`rd'')+1 |
| tempname fitline_bounds |
| if ('`rd'''') matrix `fitline_bounds'=.,. |
| else matrix `fitline_bounds'=.,`=subinstr('`rd'','',',',.)',. |
| * LOOP over by-vars |
| local counter_by=0 |
| if ('`by'''') local noby='noby' |
| foreach byval in `byvals' `noby' { |
| local++counter_by |
| ** Set the column for the x-coords in the scatterpts matrix |
| local xind=`counter_by'*2-1 |
| * Set the row to start seeking from |
| * note: each time we seek a coeff, it should be from row (rd_num)(counter_by-1)+counter_rd |
| local row0=( `rdnum' ) * (`counter_by' - 1) |
| * LOOP over y-vars |
| local counter_depvar=0 |
| foreach depvar of varlist `y_vars_r' { |
| local++counter_depvar |
| local++c |
| * Find lower and upper bounds for the fit line |
| matrix `fitline_bounds'[1,1]=`y`counter_depvar'_scatterpts'[1,`xind'] |
| local fitline_ub_rindex=`nquantiles' |
| local fitline_ub=. |
| while `fitline_ub'. { |
| local fitline_ub=`y`counter_depvar'_scatterpts'[`fitline_ub_rindex',`xind'] |
| local--fitline_ub_rindex |
| } |
| matrix `fitline_bounds'[1,`rdnum'+1]=`fitline_ub' |
| * LOOP over rd intervals |
| forvalues counter_rd=1/`rdnum' { |
| if (`'`linetype'''lfit') { |
| local coef_quad=0 |
| local coef_lin=`y`counter_depvar'_coefs'[`row0'+`counter_rd',1] |
| local coef_cons=`y`counter_depvar'_coefs'[`row0'+`counter_rd',2] |
| } |
| else if (`'`linetype'''qfit') { |
| local coef_quad=`y`counter_depvar'_coefs'[`row0'+`counter_rd',1] |
| local coef_lin=`y`counter_depvar'_coefs'[`row0'+`counter_rd',2] |
| local coef_cons=`y`counter_depvar'_coefs'[`row0'+`counter_rd',3] |
| } |
| if!missing(`coef_quad',`coef_lin',`coef_cons') { |
| local leftbound=`fitline_bounds'[1,`counter_rd'] |
| local rightbound=`fitline_bounds'[1,`counter_rd'+1] |
| local fits `fits' (function `coef_quad'*x^2+`coef_lin'*x+`coef_cons', range(`leftbound' `rightbound') lcolor(`: word `c' of `lcolors')) |
| } |
| } |
| } |
| } |
| } |
| * Prepare y-axis title |
| if (`ynum'1) local ytitle `y_vars' |
| else if (`ynum'2) local ytitle : subinstr local y_vars ''' and ' |
| else local ytitle : subinstr local y_vars '''; ', all |
| * Display graph |
| local graphcmd twoway `scatters' `fits', graphregion(fcolor(white)) `xlines' xtitle(`x_var') ytitle(`ytitle') legend(`legend_labels' order(`order')) `options' |
| if ('`savedata''!='') local savedata_graphcmd twoway `savedata_scatters' `fits', graphregion(fcolor(white)) `xlines' xtitle(`x_var') ytitle(`ytitle') legend(`legend_labels' order(`order')) `options' |
| `graphcmd' |
| ****** Save results ****** |
| * Save graph |
| if`'`savegraph''!='' { |
| * check file extension using a regular expression |
| if regexm(`'`savegraph'','.[a-zA-Z0-9]+$') local graphextension=regexs(0) |
| if inlist(`'`graphextension'','.gph','') graph save `'`savegraph'', `replace' |
| else graph export `'`savegraph'', `replace' |
| } |
| * Save data |
| if ('`savedata''!='') { |
| *** Save a CSV containing the scatter points |
| tempname savedatafile |
| file open `savedatafile' using `'`savedata'.csv', write text `replace' |
| * LOOP over rows |
| forvalues row=0/`nquantiles' { |
| *** Put the x-variable at the left |
| * LOOP over by-vals |
| forvalues counter_by=1/`bynum' { |
| if (`row'0) { /* write variable names */ |
| if'`by''!='' local bynlabel _by`counter_by' |
| file write `savedatafile' '`x_var'`bynlabel',' |
| } |
| else { /* write data values */ |
| if (`row'<=`=rowsof(`y1_scatterpts')') file write `savedatafile' (`y1_scatterpts'[`row',`counter_by'*2-1]) ',' |
| else file write `savedatafile' '.,' |
| } |
| } |
| *** Now y-variables at the right |
| * LOOP over y-vars |
| local counter_depvar=0 |
| foreach depvar of varlist `y_vars' { |
| local++counter_depvar |
| * LOOP over by-vals |
| forvalues counter_by=1/`bynum' { |
| if (`row'0) { /* write variable names */ |
| if'`by''!='' local bynlabel _by`counter_by' |
| file write `savedatafile' '`depvar'`bynlabel'' |
| } |
| else { /* write data values */ |
| if (`row'<=`=rowsof(`y`counter_depvar'_scatterpts')') file write `savedatafile' (`y`counter_depvar'_scatterpts'[`row',`counter_by'*2]) |
| else file write `savedatafile' '.' |
| } |
| * unless this is the last variable in the dataset, add a comma |
| if!(`counter_depvar'`ynum' & `counter_by'`bynum') file write `savedatafile' ',' |
| } /* end by-val loop */ |
| } /* end y-var loop */ |
| file write `savedatafile' _n |
| } /* end row loop */ |
| file close `savedatafile' |
| di as text `'(file `savedata'.csv written containing saved data)' |
| *** Save a do-file with the commands to generate a nicely labeled dataset and re-create the binscatter graph |
| file open `savedatafile' using `'`savedata'.do', write text `replace' |
| file write `savedatafile' `'insheet using `savedata'.csv' _n _n |
| if'`by''!='' { |
| foreach var of varlist `x_var' `y_vars' { |
| local counter_by=0 |
| foreach byval in `byvals' { |
| local++counter_by |
| if ('`bylabel'''') local byvalname=`byval' |
| else { |
| local byvalname `: label `bylabel' `byval' |
| } |
| file write `savedatafile' `'label variable `var'_by`counter_by' '`var'; `byvarname'`byvalname'' _n |
| } |
| } |
| file write `savedatafile' _n |
| } |
| file write `savedatafile' `'`savedata_graphcmd'' _n |
| file close `savedatafile' |
| di as text `'(file `savedata'.do written containing commands to process saved data)' |
| } |
| *** Return items |
| ereturn post, esample(`touse') |
| ereturn scalar N = `samplesize' |
| ereturn local graphcmd `'`graphcmd'' |
| if inlist('`linetype'','lfit','qfit') { |
| forvalues yi=`ynum'(-1)1 { |
| ereturn matrix y`yi'_coefs=`y`yi'_coefs' |
| } |
| } |
| if ('`rd''!='') { |
| tempname rdintervals |
| matrix `rdintervals' = (. `=subinstr('`rd'','','',.)' ) , ( `=subinstr('`rd'','','',.)' .) |
| forvalues i=1/`=rowsof(`rdintervals')' { |
| local rdintervals_labels `rdintervals_labels' rd`i' |
| } |
| matrix rownames `rdintervals' = `rdintervals_labels' |
| matrix colnames `rdintervals' = gt lt_eq |
| ereturn matrix rdintervals=`rdintervals' |
| } |
| if ('`by''!=''&'`by'''`byvarname'') { /* if a numeric by-variable was specified */ |
| forvalues i=1/`=rowsof(`byvalmatrix')' { |
| local byvalmatrix_labels `byvalmatrix_labels' by`i' |
| } |
| matrix rownames `byvalmatrix' = `byvalmatrix_labels' |
| matrix colnames `byvalmatrix' = `by' |
| ereturn matrix byvalues=`byvalmatrix' |
| } |
| end |
| ********************************** |
| * Helper programs |
| program define means_in_boundaries, rclass |
| version 12.1 |
| syntax varname(numeric) [aweight fweight], BOUNDsmat(name) [MEDians] |
| * Create convenient weight local |
| if ('`weight''!='') local wt [`weight'`exp'] |
| local r=rowsof(`boundsmat') |
| matrix means=J(`r',1,.) |
| if ('`medians''!='medians') { |
| forvalues i=1/`r' { |
| sum `varlist' in `=`boundsmat'[`i',1]'/`=`boundsmat'[`i',2]' `wt', meanonly |
| matrix means[`i',1]=r(mean) |
| } |
| } |
| else { |
| forvalues i=1/`r' { |
| _pctile `varlist' in `=`boundsmat'[`i',1]'/`=`boundsmat'[`i',2]' `wt', percentiles(50) |
| matrix means[`i',1]=r(r1) |
| } |
| } |
| return clear |
| return matrix means=means |
| end |
| *** copy of: version 1.21 8oct2013 Michael Stepner, stepner@mit.edu |
| program define fastxtile, rclass |
| version 11 |
| * Parse weights, if any |
| _parsewt 'aweight fweight pweight' `0' |
| local 0 '`s(newcmd)''/* command minus weight statement */ |
| local wt '`s(weight)''/* contains [weight=exp] or nothing */ |
| * Extract parameters |
| syntax newvarname=/exp [if] [in] [,Nquantiles(integer 2) Cutpoints(varname numeric) ALTdef /// |
| CUTValues(numlist ascending) randvar(varname numeric) randcut(real 1) randn(integer -1)] |
| * Mark observations which will be placed in quantiles |
| marksample touse, novarlist |
| markout `touse' `exp' |
| qui count if `touse' |
| local popsize=r(N) |
| if'`cutpoints''''&'`cutvalues'''' { /***** NQUANTILES *****/ |
| if`'`wt''!=''&'`altdef''!='' { |
| di as error 'altdef option cannot be used with weights' |
| exit 198 |
| } |
| if `randn'!=-1 { |
| if `randcut'!=1 { |
| di as error 'cannot specify both randcut() and randn()' |
| exit 198 |
| } |
| else if `randn'<1 { |
| di as error 'randn() must be a positive integer' |
| exit 198 |
| } |
| else if `randn'>`popsize' { |
| di as text 'randn() is larger than the population. using the full population.' |
| local randvar='' |
| } |
| else { |
| local randcut=`randn'/`popsize' |
| if'`randvar''!='' { |
| qui sum `randvar', meanonly |
| if r(min)<0 | r(max)>1 { |
| di as error 'with randn(), the randvar specified must be in [0,1] and ought to be uniformly distributed' |
| exit 198 |
| } |
| } |
| } |
| } |
| * Check if need to gen a temporary uniform random var |
| if'`randvar'''' { |
| if (`randcut'<1 & `randcut'>0) { |
| tempvar randvar |
| gen `randvar'=runiform() |
| } |
| * randcut sanity check |
| else if `randcut'!=1 { |
| di as error 'if randcut() is specified without randvar(), a uniform r.v. will be generated and randcut() must be in (0,1)' |
| exit 198 |
| } |
| } |
| * Mark observations used to calculate quantile boundaries |
| if ('`randvar''!='') { |
| tempvar randsample |
| mark `randsample' `wt' if `touse' & `randvar'<=`randcut' |
| } |
| else { |
| local randsample `touse' |
| } |
| * Error checks |
| qui count if `randsample' |
| local samplesize=r(N) |
| if (`nquantiles' > r(N) + 1) { |
| if ('`randvar'''') di as error 'nquantiles() must be less than or equal to the number of observations [`r(N)'] plus one' |
| else di as error 'nquantiles() must be less than or equal to the number of sampled observations [`r(N)'] plus one' |
| exit 198 |
| } |
| else if (`nquantiles' < 2) { |
| di as error 'nquantiles() must be greater than or equal to 2' |
| exit 198 |
| } |
| * Compute quantile boundaries |
| _pctile `exp' if `randsample' `wt', nq(`nquantiles') `altdef' |
| * Store quantile boundaries in list |
| forvalues i=1/`=`nquantiles'-1' { |
| local cutvallist `cutvallist' r(r`i') |
| } |
| } |
| else if'`cutpoints''!='' { /***** CUTPOINTS *****/ |
| * Parameter checks |
| if'`cutvalues''!='' { |
| di as error 'cannot specify both cutpoints() and cutvalues()' |
| exit 198 |
| } |
| if'`wt''!=''|'`randvar''!=''|'`ALTdef''!=''| `randcut'!=1 | `nquantiles'!=2 | `randn'!=-1 { |
| di as error 'cutpoints() cannot be used with nquantiles(), altdef, randvar(), randcut(), randn() or weights' |
| exit 198 |
| } |
| tempname cutvals |
| qui tab `cutpoints', matrow(`cutvals') |
| if r(r)0 { |
| di as error 'cutpoints() all missing' |
| exit 2000 |
| } |
| else { |
| local nquantiles = r(r) + 1 |
| forvalues i=1/`r(r)' { |
| local cutvallist `cutvallist' `cutvals'[`i',1] |
| } |
| } |
| } |
| else { /***** CUTVALUES *****/ |
| if'`wt''!=''|'`randvar''!=''|'`ALTdef''!=''| `randcut'!=1 | `nquantiles'!=2 | `randn'!=-1 { |
| di as error 'cutvalues() cannot be used with nquantiles(), altdef, randvar(), randcut(), randn() or weights' |
| exit 198 |
| } |
| * parse numlist |
| numlist '`cutvalues'' |
| local cutvallist `'`r(numlist)'' |
| local nquantiles=wordcount(`'`r(numlist)'')+1 |
| } |
| * Pick data type for quantile variable |
| if (`nquantiles'<=100) local qtype byte |
| else if (`nquantiles'<=32,740) local qtype int |
| else local qtype long |
| * Create quantile variable |
| local cutvalcommalist : subinstr local cutvallist ''',', all |
| qui gen `qtype' `varlist'=1+irecode(`exp',`cutvalcommalist') if `touse' |
| label var `varlist' '`nquantiles' quantiles of `exp'' |
| * Return values |
| if ('`samplesize''!='') return scalar n = `samplesize' |
| else return scalar n = . |
| return scalar N = `popsize' |
| tokenize `'`cutvallist'' |
| forvalues i=`=`nquantiles'-1'(-1)1 { |
| return scalar r`i' = ``i' |
| } |
| end |
| version 12.1 |
| set matastrict on |
| mata: |
| void characterize_unique_vals_sorted(stringscalar var,realscalar first,realscalar last,realscalar maxuq) { |
| // Inputs: a numeric variable, a starting & ending obs #, and a maximum number of unique values |
| // Requires: the data to be sorted on the specified variable within the observation boundaries given |
| // (no check is made that this requirement is satisfied) |
| // Returns: the number of unique values found |
| // the unique values found |
| // the observation boundaries of each unique value in the dataset |
| // initialize returned results |
| realscalar Nunique |
| Nunique=0 |
| realmatrix values |
| values=J(maxuq,1,.) |
| realmatrix boundaries |
| boundaries=J(maxuq,2,.) |
| // initialize computations |
| realscalar var_index |
| var_index=st_varindex(var) |
| realscalar curvalue |
| realscalar prevvalue |
| // perform computations |
| realscalar obs |
| for (obs=first; obs<=last; obs++) { |
| curvalue=_st_data(obs,var_index) |
| if (curvalue!=prevvalue) { |
| Nunique++ |
| if (Nunique<=maxuq) { |
| prevvalue=curvalue |
| values[Nunique,1]=curvalue |
| boundaries[Nunique,1]=obs |
| if (Nunique>1) boundaries[Nunique-1,2]=obs-1 |
| } |
| else { |
| exit(error(134)) |
| } |
| } |
| } |
| boundaries[Nunique,2]=last |
| // return results |
| stata('return clear') |
| st_numscalar('r(r)',Nunique) |
| st_matrix('r(values)',values[1..Nunique,.]) |
| st_matrix('r(boundaries)',boundaries[1..Nunique,.]) |
| } |
| end |
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