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1.78578578578579 0.052103415611651 - 1.78778778778779 0.048848714158603 - 1.78978978978979 0.045599324952682 - 1.79179179179179 0.042355245286611 - 1.79379379379379 0.039116472453114 - 1.7957957957958 0.035883003744916 - 1.7977977977978 0.032654836454741 - 1.7997997997998 0.029431967875312 - 1.8018018018018 0.026214394666868 - 1.8038038038038 0.023002110068674 - 1.80580580580581 0.019795106168678 - 1.80780780780781 0.016593375053962 - 1.80980980980981 0.013396908811608 - 1.81181181181181 0.010205699528699 - 1.81381381381381 0.007019739292316 - 1.81581581581582 0.003839020189541 - 1.81781781781782 0.000663534307455 - 1.81981981981982 0.00250672626686 1.82182182182182 0.00567176944632 1.82382382382382 0.008831603143846 1.82582582582583 0.011986235272354 1.82782782782783 0.015135673744764 1.82982982982983 0.018279926473993 1.83183183183183 0.021419001372959 1.83383383383383 0.024552906354581 1.83583583583584 0.027681649331776 1.83783783783784 0.030805238217464 1.83983983983984 0.033923680924561 1.84184184184184 0.037036985365986 1.84384384384384 0.040145159454658 1.84584584584585 0.043248211103493 1.84784784784785 0.046346148225412 1.84984984984985 0.049438978733332 1.85185185185185 0.05252671054017 1.85385385385385 0.055609351558845 1.85585585585586 0.058686909702275 1.85785785785786 0.061759392883379 1.85985985985986 0.064826809015074 1.86186186186186 0.067889166010279 1.86386386386386 0.070946471781911 1.86586586586587 0.07399873424289 1.86786786786787 0.077045961306132 1.86986986986987 0.080088160884557 1.87187187187187 0.083125340891082 1.87387387387387 0.086157509238626 1.87587587587588 0.089184673840106 1.87787787787788 0.092206842608442 1.87987987987988 0.09522402345655 1.88188188188188 0.098236224297349 1.88388388388388 0.101243453043757 1.88588588588589 0.104245717608693 1.88788788788789 0.107243025905075 1.88988988988989 0.11023538584582 1.89189189189189 0.113222805343847 1.89389389389389 0.116205292312074 1.8958958958959 0.11918285466342 1.8978978978979 0.122155500310801 1.8998998998999 0.125123237167138 1.9019019019019 0.128086073145346 1.9039039039039 0.131044016158346 1.90590590590591 0.133997074119054 1.90790790790791 0.13694525494039 1.90990990990991 0.13988856653527 1.91191191191191 0.142827016816614 1.91391391391391 0.14576061369734 1.91591591591592 0.148689365090365 1.91791791791792 0.151613278908609 1.91991991991992 0.154532363064988 1.92192192192192 0.157446625472421 1.92392392392392 0.160356074043826 1.92592592592593 0.163260716692122 1.92792792792793 0.166160561330227 1.92992992992993 0.169055615871058 1.93193193193193 0.171945888227534 1.93393393393393 0.174831386312573 1.93593593593594 0.177712118039093 1.93793793793794 0.180588091320013 1.93993993993994 0.18345931406825 1.94194194194194 0.186325794196723 1.94394394394394 0.189187539618349 1.94594594594595 0.192044558246048 1.94794794794795 0.194896857992736 1.94994994994995 0.197744446771333 1.95195195195195 0.200587332494756 1.95395395395395 0.203425523075924 1.95595595595596 0.206259026427754 1.95795795795796 0.209087850463165 1.95995995995996 0.211912003095075 1.96196196196196 0.214731492236402 1.96396396396396 0.217546325800065 1.96596596596597 0.220356511698981 1.96796796796797 0.223162057846069 1.96996996996997 0.225962972154246 1.97197197197197 0.228759262536431 1.97397397397397 0.231550936905542 1.97597597597598 0.234338003174497 1.97797797797798 0.237120469256215 1.97997997997998 0.239898343063613 1.98198198198198 0.24267163250961 1.98398398398398 0.245440345507123 1.98598598598599 0.248204489969072 1.98798798798799 0.250964073808373 1.98998998998999 0.253719104937946 1.99199199199199 0.256469591270708 1.99399399399399 0.259215540719577 1.995995995996 0.261956961197473 1.997997997998 0.264693860617312 2 0.267426246892013 10002 mat :

value table col lookup k 1 : j k table rows range table j col el value ≡ index k el j : k k 1 + : 21 line continue if for k 1 ≡ index NO match : index if 31 line :

t0 1 time :

4 appVersion 1.0.8348.30405

ROW data 2 col Min data 2 lookup : 39811 mat

sol data ROW row (: 0.795 1.748 - 12 mat

data sol 1 el sol 2 el + 40 red 1 5 mat 2 1 sys

Engineer style lookup

data Clear 1

Altitude correction from source [1..4] data 1.2929 1.2469 1.2022 1.1588 1.1523 1.1113 1.0714 1.0327 1.0392 1.0022 0.9663 0.9314 0.9464 0.9127 0.88 0.8482 0.8688 0.8378 0.8078 0.7786 0.8029 0.7743 0.7466 0.7196 0.7464 0.7198 0.694 0.6689 0.6972 0.6724 0.6483 0.6249 0.6542 0.6309 0.6083 0.5863 0.6161 0.5942 0.5729 0.5522 0.5823 0.5615 0.5414 0.5219 0.5519 0.5323 0.5132 0.4947 0.5246 0.5059 0.4878 0.4702 0.4998 0.482 0.4648 0.448 0.4773 0.4603 0.4438 0.4278 0.4567 0.4405 0.4247 0.4094 0.4379 0.4223 0.4071 0.3924 0.4205 0.4055 0.391 0.3769 0.4044 0.39 0.376 0.3625 0.3896 0.3757 0.3622 0.3491 0.3757 0.3624 0.3494 0.3368 0.3629 0.3499 0.3374 0.3252 224 mat :

search range value"truth" condition lo 0.6309 : hi 0.8688 : 12 mat x c lo x ≤ (x hi ≤ (* : 21 sys

Nested exploder sorted row wise ... [row_col] M lo hi locate k 0 : i 1 M rows range j 1 M cols range M i j el lo ≥ (M i j el hi ≤ (* 0 ≠ u k k 1 + : el i : v k k : el j : 12 mat k k 1 + : if for for strip paired 0's k 0 : i 1 u rows range u i el v i el * 0 ≠ R k k 1 + : el u i el v i el 12 mat : 11 line NOT in search lo/hi if 11 line for R 31 line 41 line :

index data lo hi locate :

index rows 18

veritas cnt 1 : j 1 index rows range n index j el (11 el : k index j el (12 el : value cnt el data n k el : cnt cnt 1 + : 41 line for value 31 line :

data UnestV v data 1 el : j 2 data rows range v v data j el stack : for v 31 line :

index 4412 mat 5112 mat 5212 mat 5312 mat 5412 mat 6112 mat 6212 mat 6312 mat 6412 mat 7112 mat 7212 mat 7312 mat 7412 mat 8112 mat 8212 mat 8312 mat 9112 mat 9212 mat 181 mat

idx index UnestV :

header row col value 13 mat :

header idx veritas augment stack

Project header idx veritas augment stack :

index index eval :

Project row col value 44 0.8482 51 0.8688 52 0.8378 53 0.8078 54 0.7786 61 0.8029 62 0.7743 63 0.7466 64 0.7196 71 0.7464 72 0.7198 73 0.694 74 0.6689 81 0.6972 82 0.6724 83 0.6483 91 0.6542 92 0.6309 193 mat

Truth table T data c data * vectorize : 000000000000000 0.8482 0.8688 0.8378 0.8078 0.7786 0.8029 0.7743 0.7466 0.7196 0.7464 0.7198 0.694 0.6689 0.6972 0.6724 0.6483 0 0.6542 0.6309 000000000000000000000000000000000000000000000000000000224 mat

Locate exact value in vector V x FindIdx j 1 : V j el x ≠ j j 1 + : while j V j el 21 mat 31 line :

veritas 0.8482 0.8688 0.8378 0.8078 0.7786 0.8029 0.7743 0.7466 0.7196 0.7464 0.7198 0.694 0.6689 0.6972 0.6724 0.6483 0.6542 0.6309 181 mat

wanted 0.7466 :

E veritas wanted FindIdx : 8 0.7466 21 mat

Locate exact value in table M key FindIndex r M rows : c M cols : 12 mat i 1 : j 1 : 12 mat j c ≤ (M i j el key ≠ (* i r < i i 1 + : i 1 : j j 1 + : 21 line if while j c ≤ i j 21 mat end of search if 41 line :

rowcol idx T wanted FindIndex (: 6321 mat

sanity check T idx 1 el idx 2 el el 0.7466

search index j 5 : jx index j el : 21 sys

data jx 1 el jx 2 el el 0.7786

search range index j 1518 range : jrx index j el : 21 sys

new data jrx 1 el vectorize jrx 2 el vectorize el : 0.6724 0.6483 0.6972 0.6724 0.6724 0.6483 0.6972 0.6724 0.6309 0.6083 0.6542 0.6309 0.6309 0.6083 0.6542 0.6309 44 mat

new Diag 0.6724 0000 0.6483 0000 0.6542 0000 0.6309 44 mat

veritas 1318 range 1 el 0.6689 0.6972 0.6724 0.6483 0.6542 0.6309 61 mat

◄ here is veritas Grand Companion
. . . range collection

"linterp" has a quadratic interpolation resulting property M x y Spline2D A M 112 M cols submatrix : B M 2 M rows 11 submatrix : C M 2 M rows 2 M cols submatrix : j 1 A length 2 range s j el B C 1 C rows j j submatrix y linterp : for A transpose s x linterp 51 line :

Construction from below Steam T/P 1 1.1 1.2 1.3 950 5.754 5.232 4.797 4.427 960 5.801 5.275 4.836 4.463 970 5.848 5.318 4.875 4.499 980 5.895 5.360 4.914 4.535 990 5.942 5.402 4.953 4.571 1000 5.989 5.444 4.992 4.607 75 mat :

Optimiz Numeric Steam 1970 Spline2D Steam 1.15 975 Spline2D 21 mat 5.848 5.117 21 mat

Spline-mesh [vx, vy] an Engineering table . . . Export . . .

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Table i 1 vx rows range j 1 vy rows range New i j el Steam vx i el vy j el Spline2D eval : for for x/y vy stack vx transpose New transpose stack augment 21 line :

populate the colspopulate the rows vx 1 1.3 1.025 range : vy 9501000955 range : 21 sys

.. set 3 decimals
copy/paste/export

Table x/y 1 1.025 1.05 1.075 1.1 1.125 1.15 1.175 1.2 1.225 1.25 1.275 1.3 950 5.754 5.624 5.493 5.362 5.232 5.123 5.014 4.906 4.797 4.704 4.612 4.52 4.427 955 5.778 5.646 5.516 5.384 5.254 5.144 5.035 4.926 4.816 4.724 4.631 4.538 4.445 960 5.801 5.67 5.538 5.406 5.275 5.165 5.056 4.946 4.836 4.743 4.65 4.556 4.463 965 5.824 5.692 5.56 5.428 5.296 5.186 5.076 4.966 4.856 4.762 4.668 4.575 4.481 970 5.848 5.716 5.583 5.45 5.318 5.207 5.096 4.986 4.875 4.781 4.687 4.593 4.499 975 5.872 5.738 5.605 5.472 5.339 5.228 5.117 5.006 4.894 4.8 4.706 4.611 4.517 980 5.895 5.761 5.628 5.494 5.36 5.248 5.137 5.026 4.914 4.819 4.724 4.63 4.535 985 5.918 5.784 5.65 5.515 5.381 5.269 5.157 5.045 4.934 4.838 4.743 4.648 4.553 990 5.942 5.807 5.672 5.537 5.402 5.29 5.178 5.065 4.953 4.858 4.762 4.666 4.571 995 5.966 5.83 5.694 5.559 5.423 5.31 5.198 5.085 4.972 4.877 4.781 4.685 4.589 1000 5.989 5.853 5.716 5.58 5.444 5.331 5.218 5.105 4.992 4.896 4.8 4.703 4.607 1214 mat

sanityuser ...user ... Table 1.125 1000 Spline2D Table 1.1825 977.5 Spline2D Table 1.0625 967.5 Spline2D 31 mat 5.331 4.9822 5.5056 31 mat

Advanced lookup ... mutual arrays

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 :

truth table rectagular Array1 on descending deployed Array2matched occurences collected wrt their [row/col] in Array1. 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 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 mutual match if for for for match 91 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 . . . from medical source

0. Source Mathcad 11.

1. want is complete.

2. data is reduced in length.

]]>

1. scan => coincidences data <=> want2. zap => located in rows 'data' j 1 Index rows range scan j el data Index j el 1 el Index j el 2 el el : zap j el Index j el 1 el : 21 line for

Recover 'want' found in 'data' zap scan augment 17 0.4679 12 0.4381 12 0.4542 6 0.4443 9 0.4132 7 0.4918 22 0.3934 16 0.4222 82 mat

zap 171212697221681 mat

sanity individual matched jj 8 :

data Index jj el 1 el Index jj el 2 el el 0.4222

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

'include'  rows of data not marked '1' include s 1 data rows range : y delrow : x y in x y ≡ vectorize max : 31 sys j 1 : t s w j el t : j j 1 + : 21 line t y in 0 ≡ Exclude cases for w 41 line :

on descending 's' rows(data),logical testexcludes indices  that are common between's' and 'delrow' t y in logic test common [1/0] ≡

1. vec'r included data2. data xcluded  'want'3. length 'filtered' vr 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 0.4443 0.4393 0.4309 0.4573 0.4486 0.442 0.4357 0.4918 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 0.4132 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 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 0.487 0.4728 0.4996 0.4834 0.4859 0.4719 0.466 0.4569 0.433 0.4246 0.4548 0.4464 0.4222 0.4126 0.4719 0.4592 0.47 0.4598 0.471 0.4588 0.4679 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 0.3934 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 :

Explore graph col 3 :

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

Medicdata_1 col Medicdata 2 1 sys

'Medic', is data stripped of the
rows 'mark 1'... as determined
by Locate(Array1,Array2).

sanity individual 'mark' jj 8 :

data Index jj el 1 el Index jj el 2 el el 0.4222

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

identify/visualize/locatein data where 'want & data'do coincide  ...[kind of truth table] data Index markWant

data data Index markWant :

<content> data 'mark " ... Medic </content>

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 ▄▄ 0.4393 0.4309 0.4573 0.4486 0.442 0.4357 ▄▄ 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 ▄▄ 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 ▄▄ ▄▄ 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 ▄▄ 0.4126 0.4719 0.4592 0.47 0.4598 0.471 0.4588 ▄▄ 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 ▄▄ 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

Hermite convex wthin data set is possible ...

data 1 0.4195 2 0.5001 3 0.4945 4 0.4837 5 0.4874 6 0.4724 7 0.4975 8 0.4668 9 0.4545 10 0.5027 11 0.5015 12 0.4056 13 0.471 14 0.528 15 0.504 16 0.4209 17 0.4824 18 0.497 182 mat :

data data 2 1 sys

Bidirectional search in XY data set

User 6.5 2.5 6.5294 2.4502 6.5578 2.401 6.585 2.3522 6.6112 2.304 6.6362 2.2562 6.6602 2.209 6.683 2.1622 6.7048 2.116 6.7254 2.0702 6.745 2.025 6.7634 1.9802 6.7808 1.936 6.797 1.8922 6.8122 1.849 6.8262 1.8062 6.8392 1.764 6.851 1.7222 6.8618 1.681 6.8714 1.6402 6.88 1.6 6.8874 1.5602 6.8938 1.521 6.899 1.4822 6.9032 1.444 6.9062 1.4063 6.9082 1.369 6.909 1.3323 6.9088 1.296 6.9074 1.2603 6.905 1.225 6.9014 1.1903 6.8968 1.156 6.8911 1.1223 6.8842 1.089 6.8762 1.0563 6.8672 1.024 6.8571 0.9923 6.8458 0.961 6.8335 0.9303 6.82 0.9 6.8055 0.8703 6.7898 0.841 6.7731 0.8123 6.7552 0.784 6.7363 0.7563 6.7162 0.729 6.6951 0.7023 6.6728 0.676 6.6495 0.6503 6.625 0.625 6.5995 0.6003 6.5728 0.576 6.5451 0.5523 6.5162 0.529 6.4863 0.5063 6.4552 0.484 6.4231 0.4623 6.3898 0.441 6.3555 0.4203 6.32 0.4 6.2835 0.3803 6.2458 0.361 6.2071 0.3423 6.1672 0.324 6.1263 0.3063 6.0842 0.289 6.0411 0.2723 5.9968 0.256 5.9515 0.2403 5.905 0.225 5.8575 0.2103 5.8088 0.196 5.7591 0.1823 5.7082 0.169 5.6563 0.1563 5.6032 0.144 5.5491 0.1323 5.4938 0.121 5.4375 0.1103 5.38 0.1 5.3215 0.0903 5.2618 0.081 5.2011 0.0723 5.1392 0.064 5.0763 0.0563 5.0122 0.049 4.9471 0.0423 4.8808 0.036 4.8135 0.0303 4.745 0.025 4.6755 0.0203 4.6048 0.016 4.5331 0.0123 4.4602 0.009 4.3863 0.0063 4.3112 0.004 4.2351 0.0023 4.1578 0.001 4.0795 0.0003 411027 -^* 3.9204 0 3.8416 0 3.7636 0 3.6864 0 3.61 0 3.5344 0 3.4596 0 3.3856 0 3.3124 0 3.24 0 3.1684 0 3.0976 0 3.0276 0 2.9584 0 2.89 0 2.8224 0 2.7556 0 2.6896 0 2.6244 0 2.56 0 2.4964 0 2.4336 0 2.3716 0 2.3104 0 2.25 0 2.1904 0 2.1316 0 2.0736 0 2.0164 0 1.96 0 1.9044 0 1.8496 0 1.7956 0 1.7424 0 1.69 0 1.6384 0 1.5876 0 1.5376 0 1.4884 0 1.44 0 1.3924 0 1.3456 0 1.2996 0 1.2544 0 1.21 0 1.1664 0 1.1236 0 1.0816 0 1.0404 010 0.9604 0 0.9216 0 0.8836 0 0.8464 0 0.81 0 0.7744 0 0.7396 0 0.7056 0 0.6724 0 0.64 0 0.6084 0 0.5776 0 0.5476 0 0.5184 0 0.49 0 0.4624 0 0.4356 0 0.4096 0 0.3844 0 0.36 0 0.3364 0 0.3136 0 0.2916 0 0.2704 0 0.25 0 0.2304 0 0.2116 0 0.1936 0 0.1764 0 0.16 0 0.1444 0 0.1296 0 0.1156 0 0.1024 0 0.09 0 0.0784 0 0.0676 0 0.0576 0 0.0484 0 0.04 0 0.0324 0 0.0256 0 0.0196 0 0.0144 0 0.01 0 0.0064 0 0.0036 0 0.0016 0 0.0004 0 6.4 1027 -^* 02012 mat :

M key FindIndex r M rows : idx 1 : M idx el key ≠ idx r < idx idx 1 + : idx if while idx 41 line :

SX User 1 col : SY User 2 col : 12 mat

idx SX SX Max FindIndex : 28

SX idx row SY idx row 12 mat 6.909 11 mat 1.3323 11 mat 12 mat

User 1 28 range 1 2 range el User 29 User rows range 1 2 range el 6.91 1.332 + 40 black 1 5 mat 3 1 sys

User 128 range 12 range el User 29 User rows range 12 range el 6.91 1.332 + 40 black 15 mat 31 sys

Locate the 1rst occurence of aspecific element in matrix V x FindIdx j 1 : V j el x ≠ j j 1 + : while j V j el 12 mat 31 line :

M 123410 - 112181333 mat :

x 11 :

13 is on length 9 of M M x FindIdx 61112 mat

data 10 0.59 21 0.61 32 0.65 43 0.6 54862 0.55 7 0.3 0.6 - 8 0.4 0.62 - 9 0.4 0.6 10 0.38 6114 0.45 12 0.45 0.48 - 13 0.5 - 0.5 - 14 0.48 - 0.45 15 0.45 4166 0.38 17 0.6 0.4 18 0.62 - 0.4 19 0.6 - 0.3 20 0.55 2218422 0.6 323 0.65 224 0.61 125 0.59 0253 mat :

Locate 1rst exact value in vector V x col FindIdx j 1 : V j col el x ≠ j j 1 + : while j 0 ≡ inexistant j V j col el 12 mat if 31 line :

key 0.4 : col 2 : 12 mat

idxkey data key col FindIdx :

idxkey 8 0.4 12 mat

data idxkey 11 el row 8 0.4 0.62 - 13 mat

M index Clear 1

count/locate ... in vector

N 15214334555667138109610911151213137147151016617218121913201021122252312241125112617277282299305313329331634113513367379389397409417428431344114544611479486497501851115255313548551256165785813591660561862763664765116646796856917708711372137313741275137617747887914808811182118312841285486487188689159011911092293129413958961597139889910100141011210271036104121051510681074108111091211031111311281131311416115101161111712118101198120161215122161236124161251112614127212891290130113141327133713491351213681371113891391014017141414213143414417145121461614712148101491415031514152121532154315511156815715158111591016091618162916310164116551661716717168316911170111711017281734174121751717681771217811179101801218110182131831118491850186161872188318911190319117192121935194919511196919761983199720052002 mat :

h 611526672316357553377120 mat transpose :

N rows 200

value table c locate k 1 : j k table rows range table j c el value ≡ index k el j : k k 1 + : 21 line continue if for k 1 ≡ index NO match : index if 31 line :

6 h 1 locate transpose 1561114 mat

4 N 2 locate 4566778586107131141143151173111 mat

counts specific values in a sorted vector value table count k 1 : j k table rows range table j el value ≡ jndex k el j : k k 1 + : 21 line No match if for jndex rows 31 line :

N 2 col Max 18

j 2 :

j N 2 col count 6

Times Table n T i 1 n range j 1 n range M i j el i j * : for for M 21 line :

data 16 T eval :

Search repeated values in matrix ... [col_row] M lo hi locate k 0 : i 1 M rows range j 1 M cols range M i j el lo ≥ (M i j el hi ≤ (* 0 ≠ u k k 1 + : el i : v k k : el j : 12 mat k k 1 + : if for for strip paired 0's k 0 : i 1 u rows range u i el v i el * 0 ≠ R k k 1 + : el u i el v i el 12 mat : NOT in search lo/hi if 11 line for R transpose 31 line 41 line :

key 48 :

▄▄▄

lo key : hi lo : 12 mat

idx data lo hi locate :

colrow idx 31612 mat 41212 mat 6812 mat 8612 mat 12412 mat 16312 mat 16 mat

idx idx transpose :

▄▄▄

symbol is composite of 3
cursor RHS, backspace to delete

▄

data idx mark i 1 idx rows range data idx i el (1 el idx i el (2 el el ▄▄ : for data 21 line :

data idx mark 123456789101112131415162468101214161820222426283032369121518212427303336394245 ▄▄ 48121620242832364044 ▄▄ 5256606451015202530354045505560657075806121824303642 ▄▄ 5460667278849096714212835424956637077849198105112816243240 ▄▄ 566472808896104112120128918273645546372819099108117126135144102030405060708090100110120130140150160112233445566778899110121132143154165176122436 ▄▄ 6072849610812013214415616818019213263952657891104117130143156169182195208142842567084981121261401541681821962102241530456075901051201351501651801952102252401632 ▄▄ 6480961121281441601761922082242402561616 mat

Times Table n T i 1 n range j 1 n range M i j el i j * : for for M 21 line :

data 3 T eval :

data sum 36

data u v BlocUser ct 1 : i v a 1 ct el data i col : ct ct 1 + : 21 line for V a 1 el : j 2 a cols range V V a j el augment : for ct 1 : i u b 1 ct el V i row : ct ct 1 + : 21 line for U b 1 el : j 2 b cols range U U b j el stack : for U transpose 91 line :

M 05204580125520458012518020458012518024545801251802453208012518024532040512518024532040550066 mat :

col 13513 mat :

row 43213 mat :

New M col row BlocUser :

New 45125245208018054512533 mat

M row col el 45125245208018054512533 mat

algo style utility ... data row col select data row col el :

M row col select 45125245208018054512533 mat

Locate the first element in a vector
that exceeds a certain threshold

v u 02 π * (0.01 range : i 1 u rows range vy i el u i el sin : for vy 31 line :

v tresh first j 1 : v j el abs tresh ≤ j j 1 + : while j v j el 21 mat 31 line :

v 0.5 first 54 0.5055 21 mat

v 0.875 first 108 0.8772 21 mat

v 11 row v 12 row v 13 row 31 sys 0.0998 0.1098 0.1197 31 sys

v rows 629

x Clear 1

hyper fast x vector v x el :

x vector 0 2 1 sys

x vector 021 sys

jmG: 20231015

1 time t0 - 4 s *

k u v Clear 1

Search repeated values in matrix ... [col_row] Mat lo hi match k 0 : i 1 Mat rows range j 1 Mat cols range Mat i j el lo ≥ (Mat i j el hi ≤ (* 0 ≠ u k k 1 + : el i : v k k : el j : 12 mat k k 1 + : if for for strip paired 0's k 0 : i 1 u rows range u i el v i el * 0 ≠ R k k 1 + : el u i el v i el 12 mat : NOT in search lo/hi if 11 line for R 31 line 41 line :

Matrix 12345675933 mat :

Matrix 55 match 2212 mat 3212 mat 21 mat

Matrix 56 match 2212 mat 2312 mat 3212 mat 31 mat