#NEXUS
[written Mon Apr 12 14:39:13 PDT 2004 by Mesquite  version 1.01+ (build e95)]

BEGIN TAXA;
	TITLE flies;
	DIMENSIONS NTAX=48;
	TAXLABELS
		nig1 nig2 nig3 nig4 nig5 nig6 nig7 nig8 nig9 nig10 nig11 nig12 met1 met2 met3 met4 met5 met6 met7 met8 met9 met10 met11 met12 moj1 moj2 moj3 moj4 moj5 moj6 moj7 moj8 moj9 moj10 moj11 moj12 pac1 pac2 pac3 pac4 pac5 pac6 pac7 pac8 pac9 pac10 pac11 pac12 
	;

END;


BEGIN CHARACTERS;
	TITLE  wings;
	DIMENSIONS NCHAR=4;
	FORMAT DATATYPE = CONTINUOUS;
CHARSTATELABELS 
		1 V1,
		2 V2,
		3 ACV,
		4 PCV ; 
	MATRIX
	nig1    1.784 1.994 0.1007 0.2488
	nig2    1.662 1.946 0.0882 0.2503
	nig3    1.92 2.244 0.0678 0.2707
	nig4    1.838 2.107 0.0678 0.2653
	nig5    1.843 2.111 0.0784 0.2791
	nig6    1.953 2.194 0.0671 0.2696
	nig7    1.782 2.03 0.0795 0.2678
	nig8    1.792 2.137 0.0852 0.2694
	nig9    1.889 2.203 0.0746 0.2575
	nig10   1.836 2.092 0.0925 0.2592
	nig11   1.877 2.13 0.0941 0.2696
	nig12   1.826 2.133 0.0741 0.2751
	met1    1.451 1.659 0.0805 0.2425
	met2    1.672 1.949 0.0754 0.2687
	met3    1.67 1.943 0.0745 0.2862
	met4    1.783 2.037 0.1074 0.2612
	met5    1.734 2.048 0.0814 0.2503
	met6    1.624 1.858 0.0736 0.2555
	met7    1.697 1.939 0.0871 0.2728
	met8    1.695 1.979 0.0923 0.2748
	met9    1.552 1.835 0.0674 0.2417
	met10   1.7 1.994 0.0875 0.2781
	met11   1.723 1.945 0.0808 0.2705
	met12   1.688 1.987 0.0875 0.2847
	moj1    1.19 1.298 0.0667 0.1871
	moj2    1.209 1.336 0.06 0.1962
	moj3    1.255 1.387 0.0806 0.2011
	moj4    1.224 1.351 0.0666 0.1847
	moj5    1.196 1.318 0.0596 0.176
	moj6    1.188 1.345 0.074 0.1991
	moj7    1.187 1.314 0.0696 0.1745
	moj8    1.235 1.371 0.06 0.1877
	moj9    1.153 1.29 0.0471 0.1688
	moj10   1.208 1.352 0.0731 0.1818
	moj11   1.177 1.29 0.0679 0.1777
	moj12   1.226 1.363 0.06 0.1909
	pac1    1.343 1.479 0.0821 0.1719
	pac2    1.429 1.56 0.0731 0.2052
	pac3    1.391 1.537 0.0731 0.2192
	pac4    1.496 1.673 0.093 0.2283
	pac5    1.347 1.514 0.0795 0.1978
	pac6    1.311 1.449 0.062 0.1795
	pac7    1.424 1.62 0.0682 0.21
	pac8    1.411 1.596 0.0787 0.2128
	pac9    1.338 1.502 0.0653 0.2077
	pac10   1.449 1.618 0.0745 0.231
	pac11   1.447 1.603 0.0787 0.2346
	pac12   1.465 1.621 0.0765 0.214

;

END;

BEGIN LABELS;
TAXAGROUPLABEL nig COLOR = (RGB 1.0 0.031372553 0.258823551) ;
TAXAGROUPLABEL met COLOR = (RGB 0.258823551 1.0 0.086274549) ;
TAXAGROUPLABEL moj COLOR = (RGB 1.0 0.62745098 0.058823551) ;
TAXAGROUPLABEL pac COLOR = (RGB 0.02745098 0.584313751 1.0) ;


END;

BEGIN SETS;
TAXPARTITION * UNTITLED  =  nig :  1 -  12, met :  13 -  24, moj :  25 -  36, pac :  37 -  48;
TAXPARTITION species  =  nig :  1 -  12, met :  13 -  24, moj :  25 -  36, pac :  37 -  48;

END;

BEGIN ASSUMPTIONS;
	TYPESET * UNTITLED   =  Squared:  1 -  4;

END;

BEGIN TREES;
	Title stored_trees;
	LINK Taxa = flies;
	TRANSLATE
		1 nig1,
		2 nig2,
		3 nig3,
		4 nig4,
		5 nig5,
		6 nig6,
		7 nig7,
		8 nig8,
		9 nig9,
		10 nig10,
		11 nig11,
		12 nig12,
		13 met1,
		14 met2,
		15 met3,
		16 met4,
		17 met5,
		18 met6,
		19 met7,
		20 met8,
		21 met9,
		22 met10,
		23 met11,
		24 met12,
		25 moj1,
		26 moj2,
		27 moj3,
		28 moj4,
		29 moj5,
		30 moj6,
		31 moj7,
		32 moj8,
		33 moj9,
		34 moj10,
		35 moj11,
		36 moj12,
		37 pac1,
		38 pac2,
		39 pac3,
		40 pac4,
		41 pac5,
		42 pac6,
		43 pac7,
		44 pac8,
		45 pac9,
		46 pac10,
		47 pac11,
		48 pac12;
	TREE colored = (((1[%color = 5 ],(2[%color = 5 ],(3[%color = 5 ],(4[%color = 5 ],(5[%color = 5 ],(6[%color = 5 ],(7[%color = 5 ],(8[%color = 5 ],(9[%color = 5 ],(10[%color = 5 ],(11[%color = 5 ],12[%color = 5 ])[%color = 5 ])[%color = 5 ])[%color = 5 ])[%color = 5 ])[%color = 5 ])[%color = 5 ])[%color = 5 ])[%color = 5 ])[%color = 5 ])[%color = 5 ])[%color = 5 ],(13[%color = 8 ],(14[%color = 8 ],(15[%color = 8 ],(16[%color = 8 ],(17[%color = 8 ],(18[%color = 8 ],(19[%color = 8 ],(20[%color = 8 ],(21[%color = 8 ],(22[%color = 8 ],(23[%color = 8 ],24[%color = 8 ])[%color = 8 ])[%color = 8 ])[%color = 8 ])[%color = 8 ])[%color = 8 ])[%color = 8 ])[%color = 8 ])[%color = 8 ])[%color = 8 ])[%color = 8 ])[%color = 8 ]),((25[%color = 10 ],(26[%color = 10 ],(27[%color = 10 ],(28[%color = 10 ],(29[%color = 10 ],(30[%color = 10 ],(31[%color = 10 ],(32[%color = 10 ],(33[%color = 10 ],(34[%color = 10 ],(35[%color = 10 ],36[%color = 10 ])[%color = 10 ])[%color = 10 ])[%color = 10 ])[%color = 10 ])[%color = 10 ])[%color = 10 ])[%color = 10 ])[%color = 10 ])[%color = 10 ])[%color = 10 ])[%color = 10 ],(37[%color = 11 ],(38[%color = 11 ],(39[%color = 11 ],(40[%color = 11 ],(42[%color = 11 ],(41[%color = 11 ],(43[%color = 11 ],(44[%color = 11 ],(45[%color = 11 ],(46[%color = 11 ],(47[%color = 11 ],48[%color = 11 ])[%color = 11 ])[%color = 11 ])[%color = 11 ])[%color = 11 ])[%color = 11 ])[%color = 11 ])[%color = 11 ])[%color = 11 ])[%color = 11 ])[%color = 11 ])[%color = 11 ]));

END;


BEGIN MESQUITECHARMODELS;
	ProbModelSet * UNTITLED   =  Brownian_default:  1 -  4;
END;

BEGIN NOTES;
	ANNOTATION TAXA = flies TAXON = 9  AUTHOR = _ REFERENCE = _ COMMENT = wow IMAGELOC = _ DATECREATED = 'Mon Apr 12 14:39:06 PDT 2004' DATEMOD = 'Mon Apr 12 14:39:09 PDT 2004';



END;

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		tell It;
			setTaxonSource  #mesquite.minimal.StoredTaxa.StoredTaxa;
			tell It;
				setTaxa #5510618219447170949;
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						tell It;
							setCharacterSource #mesquite.charMatrices.StoredMatrices.StoredMatrices;
							tell It;
								setDataSet #3229888185240561153;
							endTell;
						endTell;
						setOrdinator #mesquite.rhetenor.CanonicalVariates.CanonicalVariates;
						setItem 0;
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						tell It;
							getCharter #mesquite.charts.ItemValuesChart.ItemValuesChart;
							tell It;
								getWindow;
								tell It;
									setSize 383 284;
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									tell It;
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									setChartType  #mesquite.charts.Histogram.Histogram;
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			tell It;
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					setX 1;
					setY 2;
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		newAssistant  #mesquite.basic.ExamplesNavigator.ExamplesNavigator;
		tell It;
			setNextFileName '04-anoles.nex';
			setPrevFileName '02-wingsPCA.nex';
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					setSize 487 137;
					setLocation 16 560;
					setFont SanSerif;
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					offInfoBar;
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				setExplanation 'In the scatter plot at right, a Canonical Variates Analysis is shown, which uses the partition into the four species as the a priori grouping.  The plot above shows the character loadings on each of the canonical variates.  Note that character 1 loads most highly on the first variate.';
				setTitle Canonical_Variates;
				toggleFileNames off;
				setPrevButtonName Previous;
				setNextButtonName Next;
			endTell;
			showWindow;
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		endTell;
end;