<p> Locate, Strip ... zoomfract(M,a,b) </p>

115bd3a1-ef0e-48d4-a05a-8ffc70e941a6 25 4 5 decimal

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

U 59 π * 2 sqrt 2 ln 0.1 exp 1.23456789 9.87654321 61 mat :

U 2 sqrt 1 findrows 1.414 11 mat

j 1 U rows range :

N j U augment :

N 2 sqrt 2 findrows 22 sqrt 12 mat

<p> Locate, Strip ... zoomfract(M,a,b) </p>

data Strip3 nest striped in 'R' u data 1 col : v data 2 col : z data 3 col : k 0 : i 1 data rows range u i el v i el * z i el * 0 ≠ R k k 1 + : el u i el v i el z i el 13 mat : 11 line Undefined if 11 line for 21 line Un-nest R v R 1 el : j 2 R rows range v v R j el stack : for v 91 line :

M mask Locate Locate exclusive count 1 : i 1 M rows range j 1 M cols range M i j el mask i el - 0 ≡ V i 1 el i : V i 2 el j : V i 3 el M i j el : 31 line count count 1 + : if for for V 41 line :

Implicit 'zoom fractional' Up/Down M a b zoomfract a b ≡ (a b | (1 ≠ (& (implicit conditions ≡ i 1 M rows a * (range j 1 M cols b * (range N i j el M i a / Ceil j b / Ceil el : a 1 ≥ N i j el M i a / Floor j b / Floor el : cases for for N 31 line :

Locate specific values in data table

The search is exclusive of non existing values. Locate(M,mask)accounts only for the last position in 'M' found from 'mask'.

Q 1.22 7.36 7.96 7.94 1.26 2.36 4.74 3.07 5.83 4.11 3.78 8.14 3.64 9.93 8.95 9.73 5.13 3.71 5.78 3.16 54 mat :

mask v 5.13 4.74 9.93 9.73 3.16 51 mat :

JoBlo Q v Locate Strip3 :

Q v Locate 00023 4.74 00044 9.73 54 3.16 53 mat

JoBlo 23 4.74 44 9.73 54 3.16 33 mat

Mat i 110 range j 110 range Mat i j el i 1 - sin j 1 - cos + : for for Mat 21 line :

Mat Min Mat Max 21 mat 1.949 - 1.989 21 mat

n 5 :

M δ j z k 0 : k M rows < i k n + : j j : i 1 ≥ (M i j el abs (* δ ≥ i i 1 - : j j 1 + : 21 line while i 1 < k k 1 + : if i 1 ≥ break if 51 line while i j M i j el 31 mat 31 line :

Mat 14 z 45 0.512523612803745 - 31 mat

Mat 45 el 0.513 -

Mat 1 0.54 0.416 - 0.99 - 0.654 - 0.284 0.96 0.754 0.146 - 0.911 - 1.841 1.382 0.425 0.149 - 0.188 1.125 1.802 1.595 0.696 0.07 - 1.909 1.45 0.493 0.081 - 0.256 1.193 1.869 1.663 0.764 0.002 - 1.141 0.681 0.275 - 0.849 - 0.513 - 0.425 1.101 0.895 0.004 - 0.77 - 0.243 0.217 - 1.173 - 1.747 - 1.41 - 0.473 - 0.203 0.003 - 0.902 - 1.668 - 0.041 0.419 - 1.375 - 1.949 - 1.613 - 0.675 - 0.001 0.205 - 1.104 - 1.87 - 0.721 0.261 0.696 - 1.269 - 0.933 - 0.004 0.681 0.474 0.425 - 1.191 - 1.657 1.197 0.241 0.333 - 0.003 0.941 1.617 1.411 0.511 0.254 - 1.989 1.53 0.573 0.001 - 0.336 1.273 1.95 1.743 0.844 0.078 1.412 0.952 0.004 - 0.578 - 0.242 - 0.696 1.372 1.166 0.267 0.499 - 1010 mat

WL 0.85 0.74 0.74 0.75 0.73 0.72 0.72 0.72 0.73 0.72 0.71 0.69 0.7 0.71 0.72 0.7 0.7 0.7 0.67 0.71 0.7 0.7 0.68 0.68 0.69 0.69 0.69 0.67 0.67 0.67 0.68 0.7 0.68 0.67 0.68 0.67 0.67 0.67 0.66 0.68 0.68 0.67 0.67 0.66 0.65 0.86 0.9 0.9 0.89 0.93 0.9 0.9 1.11 1.13 0.89 0.9 0.95 0.98 0.9 0.9 0.87 0.87 0.89 0.64 0.63 0.63 0.65 0.64 0.63 0.62 0.63 0.62 0.85 0.92 0.9 0.9 0.91 0.91 0.9 0.93 0.94 99 mat :

WL 0.68 5 findrows 0.67 0.71 0.7 0.7 0.68 0.68 0.69 0.69 0.69 0.67 0.67 0.66 0.68 0.68 0.67 0.67 0.66 0.65 29 mat

collect row(s) that match value specified wrt col matrix value col findrows

simply indexes the row(s) containing "value in col" data value col lookup k 1 : j k data rows range data j col el value ≡ index k el j : k k 1 + : 21 line 0 if for index IsDefined index No value(s) match error if 31 line :

t0 1 time :

WL 0.68 5 lookup 3521 mat

1 time t0 - 0

idx 5681115162125263132363841444647495053545758596263261 mat :

s 065 range :

a function of two arguments equivalent to logical 'or' x y in x y ≡ vectorize max :

x y NOTcommon j 1 : t x w j el t : j j 1 + : 21 line t y in 0 ≡ NOTcommon cases for w 31 line :

IDX s idx NOTcommon :

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

map 000000 0.4679 0 0.3934 0000000 0.4231 0.4093 0.4253 0.4132 0.4213 0.4679 0.4222 0.4103 00 0.4048 00000 0.4008 0.3903 0.3857 0.3753 0.4029 0.3903 0.3856 0.4679 58 mat :

M c Locate ordered wrt 'i' rows i 1 : m 1 M rows range n 1 M cols range L 1 i el m n 21 mat : i i 1 + : 31 line M m n el c 1 ≡ absent cases for for L 41 line :

x c x 0.4679 ≡ :

map c Locate 1721 mat 3621 mat 5821 mat 13 mat

Bolean from vectorize map c vectorize 000000100000000000000100000000000000000158 mat

map c map * vectorize 000000 0.4679 00000000000000 0.4679 00000000000000000 0.4679 58 mat

W 1.22 7.36 7.96 7.94 1.26 2.36 4.74 3.07 5.83 4.11 3.78 8.14 3.64 9.93 8.95 9.73 5.13 3.71 5.78 3.16 54 mat :

The truth table

search range values
Bolean "truth" lo 2 : hi 4 : 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 :

Truth table W c W * vectorize 00000 2.36 0 3.07 00 3.78 0 3.64 0000 3.71 0 3.16 54 mat

index W lo hi locate :

index transpose 2221 mat 2421 mat 3321 mat 4121 mat 5221 mat 5421 mat 16 mat

Symmetric/asymmetric "pivot"

vy 9.206 9.3 9.278 9.175 9.275 9.289 9.287 9.261 9.303 9.276 9.273 9.288 9.256 9.252 9.298 9.267 161 mat :

pivot n m S U 0 : V 0 : 12 mat i 0 m range U i el i : for j 1 n range V j 1 + el j - : for V reverse U stack pivot + 41 line :

pivot 10 : n 5 : m 5 : 13 mat

local assign jdx pivot n m S 11 line :

vy jdx el 9.275 9.289 9.287 9.261 9.303 9.276 9.273 9.288 9.256 9.252 9.298 111 mat

jdx 56789101112131415111 mat

pivot 10 : n 5 : m 5 : c1 1 : c2 45 : 15 mat

local assign jdx pivot n m S 11 line :

Mat i 150 range j 150 range Mat i j el i 1 - sin j 1 - cos + eval : for for Mat 21 line :

stuff Mat jdx c1 c2 range el : stuff stuff 55 zoomfract : 21 sys

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

crocodile

stuff

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

M Wanted j 1 M rows range a j 1 matrix 1 + : for i 1 M cols range b M i col : ε b a ≥ (vectorize : ε sum (a sum (≡ R b : if 31 line for R 31 line :

A 3.827 - 3.827 9.239 9.239 - 9.239 9.239 - 3.827 3.827 - 2.071 2.071 12.071 12.071 34 mat :

A Wanted 9.239 3.827 12.071 31 mat

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

G 01491251023611347044 mat :

vy π 2 ln 2 sqrt π sqrt 41 mat :

replace diagonal elements in square matrix M U DiaUser I M rows identity : i 1 M rows range j 1 M cols range ijN i j el 0 I i j el 1 ≡ 1 cases : for for ijN G * vectorize U diag + 31 line :

vy diag 3.142 0000 0.693 0000 1.414 0000 1.772 44 mat

G vy DiaUser 3.142 1491 0.693 51023 1.414 11347 1.772 44 mat