<p> data, want </p>

653426d7-c716-428d-8be8-7fce5bb2c356 46 9 12 decimal

&[DATE] &[TIME] - &[FILENAME]

want 0.4679 0.4542 0.4645 0.4520 0.4654 0.4524 0.4618 0.4503 0.4921 0.4799 0.4744 0.4622 0.4918 0.4799 0.4749 0.4626 0.4381 0.4251 0.4514 0.4400 0.4374 0.4258 0.4515 0.4416 0.4215 0.4121 0.4009 0.3925 0.4136 0.4048 0.3934 0.3861 0.4571 0.4443 0.4552 0.4419 0.4600 0.4483 0.4577 0.4457 0.4008 0.3903 0.3857 0.3753 0.4023 0.3903 0.3856 0.3739 0.4231 0.4093 0.4253 0.4132 0.4213 0.4077 0.4222 0.4103 78 mat :

data 0.4195 0.4099 0.4078 0.4001 0.4247 0.4163 0.4134 0.4074 0.5001 0.4884 0.4893 0.4777 0.5008 0.4910 0.4910 0.4818 0.4945 0.4802 0.4789 0.4659 0.4862 0.4723 0.4719 0.4585 0.4837 0.4692 0.4756 0.4615 0.4862 0.4729 0.4786 0.4662 0.4874 0.4786 0.4788 0.4699 0.4853 0.4765 0.4770 0.4682 0.4543 0.4443 0.4393 0.4309 0.4573 0.4486 0.4420 0.4357 0.4918 0.4798 0.4884 0.4769 0.4915 0.4800 0.4878 0.4768 0.4724 0.4167 0.4160 0.4050 0.4269 0.4171 0.4143 0.4047 0.4302 0.4125 0.4167 0.4000 0.4319 0.4132 0.4190 0.4015 0.4975 0.4861 0.5002 0.4875 0.4952 0.4851 0.4974 0.4864 0.4668 0.4525 0.4430 0.4299 0.4630 0.4495 0.4387 0.4264 0.4713 0.4563 0.4606 0.4462 0.4620 0.4464 0.4542 0.4381 0.4545 0.4433 0.4437 0.4332 0.4565 0.4467 0.4482 0.4392 0.5027 0.4848 0.5039 0.4855 0.5014 0.4839 0.5014 0.4834 0.5015 0.4863 0.4870 0.4728 0.4996 0.4834 0.4859 0.4719 0.4660 0.4569 0.4330 0.4246 0.4548 0.4464 0.4222 0.4126 0.4719 0.4592 0.4700 0.4598 0.4710 0.4588 0.4679 0.4584 0.4056 0.3927 0.3919 0.3833 0.4063 0.3914 0.3922 0.3820 0.4710 0.4584 0.4472 0.4361 0.4731 0.4611 0.4505 0.4406 0.5280 0.5138 0.5137 0.5008 0.5261 0.5121 0.5108 0.4983 0.5040 0.4946 0.5162 0.5072 0.5008 0.4929 0.5127 0.5056 0.3934 0.3872 0.3707 0.3654 0.3910 0.3817 0.3695 0.3611 0.4209 0.4076 0.4062 0.3945 0.4226 0.4104 0.4069 0.3965 0.4824 0.4718 0.4783 0.4683 0.4794 0.4681 0.4757 0.4663 0.4970 0.4869 0.4954 0.4855 0.5015 0.4905 0.5004 0.4901 258 mat :

Array1 Array2 Locate Unwrap an array in vector V Array2 1 col : i 2 Array2 cols range V V Array2 i col stack : for V 31 line locate matching occurences i 1 : match 0 : k 1 V rows range row 1 Array1 rows range col 1 Array1 cols range Array1 row col el V k el ≡ (1 ≡ match i 1 el row col 21 mat : i i 1 + : 21 line NO math occurences if for for for match 71 line :

Index data want Locate :

Index 17721 mat 12821 mat 12721 mat 6221 mat 9621 mat 7121 mat 22121 mat 16721 mat 81 mat

This document . . .

0. Source Mathcad 11, project done for Art.

1. want is complete

2. data is reduced in length.

Offered in Smath as a utilities tool .

Collab Art was involved in Medical Lab.

]]>

1. scan => coincidences data <=> want
2. Index => located in 'data' j 1 Index rows range stamp j el Index j el : scan j el data stamp j el 1 el stamp j el 2 el el : 21 line for

data idx markWant mark 1 : i 1 idx rows range data idx i el (1 el idx i el (2 el el mark : for data 31 line :

rows to be zapped in data j 1 Index rows range zap j el Index j el 1 el : for

MARK data Index markWant :

zap scan augment 17 0.468 12 0.438 12 0.454 6 0.444 9 0.413 7 0.492 22 0.393 16 0.422 82 mat

zap 171212697221681 mat

explode to see rows 'marked 1' MARK 11 mat

======================================================================================

Strip repeated in 'zap' vector zap Strip zap zap sort : k 0 : i 1 zap rows 1 - (range zap i 1 + el zap i el - 0 ≠ R k k 1 + : el zap i el : 11 line if 11 line for R zap zap rows el stack 41 line :

Next objective is to delete rows marked '1' in data. We sort the "zap" vector, then strip from repeated rows indices.

delrow zap Strip :

indices of rows to 
be deleted in data delrow 6791216172271 mat

s 1 data rows range : x y in x y ≡ vectorize max : 21 line

INCLUDE conserves rows of data not marked '1' x y INCLUDE j 1 : t x w j el t : j j 1 + : 21 line t y in 0 ≡ Exclude cases for w 31 line :

1. vector filtered data
2. filtered data  'want'
3. length of 'filtered' vr s delrow INCLUDE : Medic data vr 18 range el : k 1 Medic rows range : 31 sys

vr 123458101113141518192021232425181 mat

data 0.4195 0.4099 0.4078 0.4001 0.4247 0.4163 0.4134 0.4074 0.5001 0.4884 0.4893 0.4777 0.5008 0.491 0.491 0.4818 0.4945 0.4802 0.4789 0.4659 0.4862 0.4723 0.4719 0.4585 0.4837 0.4692 0.4756 0.4615 0.4862 0.4729 0.4786 0.4662 0.4874 0.4786 0.4788 0.4699 0.4853 0.4765 0.477 0.4682 0.4543 1 0.4393 0.4309 0.4573 0.4486 0.442 0.4357 1 0.4798 0.4884 0.4769 0.4915 0.48 0.4878 0.4768 0.4724 0.4167 0.416 0.405 0.4269 0.4171 0.4143 0.4047 0.4302 0.4125 0.4167 0.4 0.4319 1 0.419 0.4015 0.4975 0.4861 0.5002 0.4875 0.4952 0.4851 0.4974 0.4864 0.4668 0.4525 0.443 0.4299 0.463 0.4495 0.4387 0.4264 0.4713 0.4563 0.4606 0.4462 0.462 0.4464 11 0.4545 0.4433 0.4437 0.4332 0.4565 0.4467 0.4482 0.4392 0.5027 0.4848 0.5039 0.4855 0.5014 0.4839 0.5014 0.4834 0.5015 0.4863 0.487 0.4728 0.4996 0.4834 0.4859 0.4719 0.466 0.4569 0.433 0.4246 0.4548 0.4464 1 0.4126 0.4719 0.4592 0.47 0.4598 0.471 0.4588 1 0.4584 0.4056 0.3927 0.3919 0.3833 0.4063 0.3914 0.3922 0.382 0.471 0.4584 0.4472 0.4361 0.4731 0.4611 0.4505 0.4406 0.528 0.5138 0.5137 0.5008 0.5261 0.5121 0.5108 0.4983 0.504 0.4946 0.5162 0.5072 0.5008 0.4929 0.5127 0.5056 1 0.3872 0.3707 0.3654 0.391 0.3817 0.3695 0.3611 0.4209 0.4076 0.4062 0.3945 0.4226 0.4104 0.4069 0.3965 238 mat

Medic Medic :

col 4 :

Medicdata_1 k Medic 1 col augment : col Medicdata k Medic col col augment : 21 line

Medic', is data stripped of the rows 'mark 1'... as determined by the scan Locate(Array1,Array2). In other words the sick patients in data are "killed" from patients in "want" that have same tag value. Now, you can plot 8 cols of Medicdata, each col of 18 left rows. At this point, there are many ways to compare 2 * 2 patients. You can plot all 8 cols as well and attempt a PCA [Principal Component Analysis] ... not offered.

Medicdata_1 col Medicdata 2 1 sys

rows marked "1" are zapped for the resulting Medic data 0.4195 0.4099 0.4078 0.4001 0.4247 0.4163 0.4134 0.4074 0.5001 0.4884 0.4893 0.4777 0.5008 0.491 0.491 0.4818 0.4945 0.4802 0.4789 0.4659 0.4862 0.4723 0.4719 0.4585 0.4837 0.4692 0.4756 0.4615 0.4862 0.4729 0.4786 0.4662 0.4874 0.4786 0.4788 0.4699 0.4853 0.4765 0.477 0.4682 0.4543 1 0.4393 0.4309 0.4573 0.4486 0.442 0.4357 1 0.4798 0.4884 0.4769 0.4915 0.48 0.4878 0.4768 0.4724 0.4167 0.416 0.405 0.4269 0.4171 0.4143 0.4047 0.4302 0.4125 0.4167 0.4 0.4319 1 0.419 0.4015 0.4975 0.4861 0.5002 0.4875 0.4952 0.4851 0.4974 0.4864 0.4668 0.4525 0.443 0.4299 0.463 0.4495 0.4387 0.4264 0.4713 0.4563 0.4606 0.4462 0.462 0.4464 11 0.4545 0.4433 0.4437 0.4332 0.4565 0.4467 0.4482 0.4392 0.5027 0.4848 0.5039 0.4855 0.5014 0.4839 0.5014 0.4834 0.5015 0.4863 0.487 0.4728 0.4996 0.4834 0.4859 0.4719 0.466 0.4569 0.433 0.4246 0.4548 0.4464 1 0.4126 0.4719 0.4592 0.47 0.4598 0.471 0.4588 1 0.4584 0.4056 0.3927 0.3919 0.3833 0.4063 0.3914 0.3922 0.382 0.471 0.4584 0.4472 0.4361 0.4731 0.4611 0.4505 0.4406 0.528 0.5138 0.5137 0.5008 0.5261 0.5121 0.5108 0.4983 0.504 0.4946 0.5162 0.5072 0.5008 0.4929 0.5127 0.5056 1 0.3872 0.3707 0.3654 0.391 0.3817 0.3695 0.3611 0.4209 0.4076 0.4062 0.3945 0.4226 0.4104 0.4069 0.3965 0.4824 0.4718 0.4783 0.4683 0.4794 0.4681 0.4757 0.4663 0.497 0.4869 0.4954 0.4855 0.5015 0.4905 0.5004 0.4901 258 mat

Medic 0.4195 0.4099 0.4078 0.4001 0.4247 0.4163 0.4134 0.4074 0.5001 0.4884 0.4893 0.4777 0.5008 0.491 0.491 0.4818 0.4945 0.4802 0.4789 0.4659 0.4862 0.4723 0.4719 0.4585 0.4837 0.4692 0.4756 0.4615 0.4862 0.4729 0.4786 0.4662 0.4874 0.4786 0.4788 0.4699 0.4853 0.4765 0.477 0.4682 0.4724 0.4167 0.416 0.405 0.4269 0.4171 0.4143 0.4047 0.4975 0.4861 0.5002 0.4875 0.4952 0.4851 0.4974 0.4864 0.4668 0.4525 0.443 0.4299 0.463 0.4495 0.4387 0.4264 0.4545 0.4433 0.4437 0.4332 0.4565 0.4467 0.4482 0.4392 0.5027 0.4848 0.5039 0.4855 0.5014 0.4839 0.5014 0.4834 0.5015 0.4863 0.487 0.4728 0.4996 0.4834 0.4859 0.4719 0.4056 0.3927 0.3919 0.3833 0.4063 0.3914 0.3922 0.382 0.471 0.4584 0.4472 0.4361 0.4731 0.4611 0.4505 0.4406 0.528 0.5138 0.5137 0.5008 0.5261 0.5121 0.5108 0.4983 0.504 0.4946 0.5162 0.5072 0.5008 0.4929 0.5127 0.5056 0.4209 0.4076 0.4062 0.3945 0.4226 0.4104 0.4069 0.3965 0.4824 0.4718 0.4783 0.4683 0.4794 0.4681 0.4757 0.4663 0.497 0.4869 0.4954 0.4855 0.5015 0.4905 0.5004 0.4901 188 mat