Margin system collapse in utilities @ top work sheet

58807dda-3b8e-4c9d-bfd7-e80fde192678 93 4 5 decimal

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

============ Unary ▼ radius /radials ===============

set 'N' radials

size radials s 1.25 :

r 1 : N 360 : 12 mat step 011 N / range : r θ f r i θ * exp * : 31 sys

step real r 2 π * step * f Re : step imag 12 π * step * f Im : X step real vectorize eval s * : Y step imag vectorize eval s * : 12 mat 31 sys

From here . . .

1. Set N radials

2. Size s radials

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circle X Y augment :

circle

sweep angle ° j 360 :

i 1 j range vx i 2 * el X i el : for

i 1 j range vy i 2 * el Y i el : for

sweep vx vy augment :

pie p1 sweep 1120 range 12 range el : p2 sweep 121180 range 12 range el : p3 sweep 181270 range 12 range el : p4 sweep 271540 range 12 range el : p5 sweep 541720 range 12 range el : 51 sys :

x y axes x y / - :

pie axes 2 1 sys

Adjustable aperture . . . project

for Ω=1 aperture disappears . . . experiment

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clear  previous 'i' range i Clear 1

Solve/plot for a given aperture

svg 0.625 :

imaginary unit

'n' population
'w' aperture  
radius OD svg n 2000 : w 1.56019262501239 : OD 2.5 : 31 sys *

rad svg OD w i π * w /^eval * Re * : 0.976562503

x circle rad 2^x 2^- sqrt ± :

Disk j 1 n range F j el OD w i 2 * π * j w / *^eval * : for F Re F Im augment 21 line :

solve aperture

rad 0 + 200 blue 1 5 mat x circle svg Disk * 4 1 sys

Ω 1.25 : OD 2 : 21 sys

solve aperture here ... bracket wisely.

sol OD w i π * w /^eval * Re Ω - 0 ≡ w 12 solve :

plug in 'w'

sol 1.56019262501239

aperture otherwise

svg 0.75 :

'n' population
'w' aperture  
radius OD n 2000 : w 0.25 : OD 2 : 31 sys

a svg OD w i π * w /^eval * Re * :

x circle a 2^x 2^- sqrt ± :

ring svg OD * a - : 1.2878

Disk j 1 n range F j el OD w i 2 * π * j w / *^eval * : for F Re F Im augment 21 line :

plot 00 + 100 blue 15 mat x circle svg Disk * 41 sys :

plot

a 0.212179660341954

thin ring
circle only
peep hole w 1.125 ≡ w 1 ≡ w 0.25 ≡ 31 sys

adjustable nuclear quadrants + svg

svg 0.625 :

x ∠

∠

∠ rot ∠ cos ∠ sin - ∠ sin ∠ cos 22 mat :

∠1 π - 2 / 22.5 ° * + : ° 67.5 -

∠2 22.5 ° * :

'n' population
'w' aperture  
radius OD n 2000 : w 0.70349 : OD 2 : 31 sys

'w' sytem companion 0.703467417226959 0.70348 0.70349 0.7035 0.703513 0.703536 61 sys

0.70349 45° ≡ 0.703513 90° ≡ 21 mat

peep hole
circle only
thin ring w 0.25 ≡ w 1 ≡ w 1.25 ≡ 31 sys

square 2 svg * 1 - 1 - 1 - 11111 - 1 - 1 - 52 mat * :

Quad_1 svg Nuc * ∠1 rot * : Quad_2 svg Nuc * ∠2 rot * : 21 sys

similar MCD global

Nuc j 1 n range F j el OD w i 2 * π * j w / *^eval * : for F Re F Im augment 21 line :

plot Quad_2 Quad_1 x 31 sys :

The Templar cross ...

plot

Unicolor/colors at will ... all sorts of creations

1.5 11 - 3.3 - 22 mat

svg 1 : Xshift 0.125 : Yshift 0 : 12 mat shift Xshift Yshift Xshift Yshift 22 mat : L 1 el 1.5 2.5 1.5 3.3 - 22 mat : j 211 range L j el svg L j 1 - el 1 shift * + (* : for 51 line

Experiment 1 ± little

backward incline
rescale X_Y 1.5 2.5 1.5 - 3.3 22 mat

1.5 11 - 3.3 - 22 mat

vertical plot 1.5 2.5 1.5 3.3 - 22 mat

L 1.5 2.5 1.5 3.3 - 22 mat 1.625 2.5 1.625 3.3 - 22 mat 1.75 2.5 1.75 3.3 - 22 mat 1.875 2.5 1.875 3.3 - 22 mat 2 2.5 2 3.3 - 22 mat 2.125 2.5 2.125 3.3 - 22 mat 2.25 2.5 2.25 3.3 - 22 mat 2.375 2.5 2.375 3.3 - 22 mat 2.5 2.5 2.5 3.3 - 22 mat 2.625 2.5 2.625 3.3 - 22 mat 2.75 2.5 2.75 3.3 - 22 mat 111 mat

right inclined
rescale plot 1.5 2.5 2.5 3.3 22 mat

L Margin system collapse in utilities @ top work sheet

λ η m M 0 : i 1 λ range j 1 η range M i j el 255 : for for M 31 line :

collapse @ top of work sheet. creates matrix η pixels thick of 'λ' length 'η' pixels thick adjusted in-situ

▼ in-situ length/thickness ▼ .. hide/collapse after use ..

In-Situ user MarginLine ... collapse after use

'λ' length, 'η' thickness
margin(λ,η)... slide  ◄ ►  ... ▲ ▼
color scheme λ 256 : η 2 : 12 mat ω λ η m : L 0 ω * 0 ω * 1 ω * 13 mat : 31 sys

Dead memo ID a Peter ≡ b Joseph ≡ c Art ≡ d Maya ≡ e Unknown ≡ 51 line

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purely decorative user. Of much different system Smath has rainbow λ 256 thickness at will. Fixed thickness demo.

NEXT ... 1. Insert image from memnu 2. on that immense rectangle ► define argument L [type L] 3. Click on that big rectangle ► reset to original size ► switch border OFF ................... Every new 'λ' and/or augment(,,,) ► reset to original size

valued + description ...
can front end program a 1.23456789 : (Peter ≡ b 2 ln : (Joseph ≡ c 2 sqrt : (Art ≡ d 9.87654321 : (Maya ≡ e ∞ : (Unknown ≡ 51 line

web colors
as well. ω ω ω 13 mat white ≡ 1 ω * 0 ω * 0 ω * 13 mat Red ≡ 0 ω * ω 0 ω * 13 mat Green ≡ 0 ω * 0 ω * ω 13 mat Blue ≡ ω ω 0 ω * 13 mat Yellow ≡ 0 ω * ω ω 13 mat Cyan ≡ ω 0 ω * ω 13 mat Magenta ≡ 0 ω * 0 ω * 0 ω * 13 mat black ≡ 81 sys

λ η m M 0 : i 1 λ range j 1 η range M i j el 255 : for for M 31 line :

'λ' length, 'η' thickness
margin(λ,η)... slide  ◄ ►  ... ▲ ▼
color scheme ω 0 : λ 32 : η 64 : 12 mat ω λ η m : SQ 0 ω * 0 ω * 0 ω * 13 mat : 41 sys

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calipers ...

λ η m M 0 : i 1 λ range j 1 η range M i j el 255 : for for M 31 line :

'λ' length, 'η' thickness
margin(λ,η)... slide  ◄ ►  ... ▲ ▼
color scheme ω 0 : λ 100 : η 16 : 12 mat ω λ η m : bar 1 ω * 0.5 ω * 0 ω * 13 mat : 41 sys

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You need that one for scaling grayscale image M lo hi Scale hi lo - (M M Min - M Max M Min - / (* lo + :

clear 'M' from previous M 0 :

Mesh U, V  within the bounds L, H L H N xd U 0 : dx H L - N / : i 1 N 1 + (range U i el L dx i * dx - (+ : for U 41 line :

Generate the symmetric square matrix x y f U V Sym r 1 : i 1 U rows range c 1 : j 1 V rows range M r c el U i el V j el f eval : c c 1 + : 21 line for r r 1 + : 31 line for M 31 line :

t0 1 time :

Discrete compactor L 1 - : H 1 : N 24 : 13 mat U L H N xd : V U : 31 sys

x y f 255 x 2^y 2^+ (- 0.875 / exp * : M x y f U V Sym : 21 sys

R 1 M * 0 M * 0 M * 31 mat transpose :

G 0 M * 1 M * 0 M * 31 mat transpose :

B 0 M * 0 M * 1 M * 31 mat transpose :

Yw 1 M * 1 M * 0 M * 31 mat transpose :

Cy 0 M * 1 M * 1 M * 31 mat transpose :

Ma 1 M * 0 M * 1 M * 31 mat transpose :

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 Cy 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 Ma

1 time t0 - 4 s *

n 48 :

square white matrix

Create white 'M' i 1 n range j 1 n range M i j el 255 : for for

fg 0 : r 16 : cx 24 : cy 24 : 14 mat

ε 0.625 : (ε=1 circle ≡

M M :

centered spot
black ... white cx 0.5 n * ≡ cy 0.5 n * ≡ fg 0 ≡ fg 255 ≡ 22 mat

W i 1 M rows range j 1 M cols range m i j el fg i cx - (2^ε j cy - (2^(* + r 2^≥ M i j el cases : for for m 21 line eval :

reseved for medallion an image matrix

iVBORw0KGgoAAAANSUhEUgAAADAAAAAwCAIAAADYYG7QAAAAAXNSR0IArs4c6QAAAARnQU1BAACxjwv8YQUAAAAJcEhZcwAADsMAAA7DAcdvqGQAAAC2SURBVFhH7c5BDsMwCATA/P/T7WVObmLZscGqxFyBXa5SSvk3nxlugiiZ534jwWtkLRK2j9x3ZOwmfZbrGDrGuYukaYSLePr67GbR2mExi9YntnLpvmUll+5bVnLp/mV+gg8ahif4oGF4gg8ahif4oGF4gg9+mefSfctKLt23rOTS/cRWFq0dFrNo7bMbT98IF5E0jXMXQ8cs17tJf0fGPnIXCVsjayPB89wHUTLGTSmllNeu6wvMr83NtZ4WEwAAAABJRU5ErkJggg== W

stuff orange

R 1 W * 0 W * 0 W * 31 mat transpose :

G 0 W * 1 W * 0 W * 31 mat transpose :

B 0 W * 0 W * 1 W * 31 mat transpose :

Yw 1 W * 1 W * 0 W * 31 mat transpose :

Ma 1 W * 0 W * 1 W * 31 mat transpose :

Cy 0 W * 1 W * 1 W * 31 mat transpose :

Or 1 W * 0.5 W * 0 W * 31 mat transpose :

iVBORw0KGgoAAAANSUhEUgAAADAAAAAwCAYAAABXAvmHAAAAAXNSR0IArs4c6QAAAARnQU1BAACxjwv8YQUAAAAJcEhZcwAADsMAAA7DAcdvqGQAAADrSURBVGhD7ZhBDsMwCASd/v/PTS0FKYdIMexi7MJIVU9ZPN5wydFa+/5+2/K5/rdlewGXV+gpsA/ygCagCWHKwALIwwwRaAfQ6hjVmwUYwztojkmAdXgByVMLsA8vWHNVAl6HFyz50BKvwLCA9+0L2jk5Gph1+4Jm3v83MPv2hdG5OXZgZUogmhKIpgSiKYFoSiCaEojmVcDrm+Ybo3NzvEKzW9DMy7PEs1rQzsnTQMe7BUu+ugEvCWuu6RViSyB55h1gSaA50BKjwxmX0DMoH980Iaz2OjSBO0+BzEPfcRGYCbQDK1ACsbR2Apl/HFPmXd+HAAAAAElFTkSuQmCCKDmvGwAXAzhlC9JzugFwUYD2LSDmi29AKwI1F/IIakMg58HeAS0I9BzoS5j+8Q2XAAXYUYfQsoE4wC59GC2Hv9uzVH09eOUwTQc/1QFMnxyq8eCnWoDX3hmw+dBfOwLgm6t4Cf/nBIATAE4AOAHgBIATAE4AOAHgBIATAE4AOAHgBIATAE4AOAHgBIATAE4AOAHgBIATAE4AtLV+AZmmJK9dLETmAAAAAElFTkSuQmCCwwTevXIgQtQdMrB+1X4G638MDGdgOAPDGRjOwHAGhjMwnIHhDAxnYDgDwxkYzsBwBoYzMJyB4QwMZ2A4A8MZGM7AcAaGMzCcgeEMDGdgOAPDGRhtrW+HGCzbkytf+wAAAABJRU5ErkJggl+hB9kUOPAICrcYC+4573uE9Vgnuq/3xIM73mSmQhZHf4rk7puuZR3wkeb8A1440QVWTGKOxiem+uaVbncMC4/ihAWQT2MTz9SdWJpIm8aDD3yUd3w2b9Km8ZB9Y8skjbzHPH6UH82lOU/zOM15t6WJvGGjkfeYx4/yo7k052kepznvduWAJm0aD3k3+mze8dm8SZvGw9JEF5/iRN5mdz6NTTxTd+KViSw8IgKeIc8K/2Z8YqpvrPtmwhNeyGFdgKcyw8ON+1Mkd990LeuA1nz1oDfBVKixUJOnLkfjfY+wHutE980Eg87ZBBzYYvyY2P0V0z4ziQ8rrTcTDAAHWDjRWEjwMzDPwY49Z/ps1w3WBWi/m5iMcFBDYYtpkYGH+37Ih+mcqZ6NgHVfPRFW4ikCFE6MyP+Kz/H5oTVMZsLdBAsw4DxwcIrBJAp+XcQVPrdNTLrC3YRfRl7AAYFDwQVbTMRa+NT3+uDzupZ1WB+ao/8cnwCe4rPYU3wqforvJ07xTdEpvrM7xbenp/ge+xS/KDjFbztO8Sub///vnS6XD43GjoI+Ww8FAAAAAElFTkSuQmCCycTeadjEs1Bzjv+yWfnM/9/pcvkfzH+Gd4tqA30AAAAASUVORK5CYII= R iVBORw0KGgoAAAANSUhEUgAAADAAAAAwCAYAAABXAvmHAAAAAXNSR0IArs4c6QAAAARnQU1BAACxjwv8YQUAAAAJcEhZcwAADsMAAA7DAcdvqGQAAADrSURBVGhD7ZhBDsMwCASd/P/PbVwVKYdIMexibMFIVU9ZPN5wydFa+1y/bTn//9uyvYDPK/SU2Cc5wBPQpBBlcAHkaYIItgNod4Tu7QKE4T/AHJsA6/ACkKcXYB9eMObqBLwOLxjysSVegHEB79sXlHOSNDDr9gXFvAQNzL59YXBukh1YmBKIpgSiKYFoSiCaEoimBKJ5F3D6pvnK4Nwkr9DsFhTzEi3xrBaUcxI10PFuwZCvb8BLwphre4XYEkCefQdYEmAOtsSoBOESegTn25smhdXeBU/gzlMi8dB3fAQmgu3AApRALK19AYR/HFP29LgAAAAAAElFTkSuQmCCQ8F53QC4HMApWxCe0w2AywK0bwEwX34DWhGguZhXUBsCOA93B7QgwHOwlzCNUPAQsAA76hBKNpAH2KUPo+Twd3uUro8Hr5ym6OCnPoDpk1MVHvzUC/DaOxMWH/prZwB8cR2X8D9OADgB4ASAEwBOADgB4ASAEwBOADgB4ASAEwBOADgB4ASAEwBOADgB4ASAEwBOADgB4ARAW+sXfqYkrwXG03gAAAAASUVORK5CYIIojbrjBN69ciJA1B0zsH71fgbrXwwMZ2A4A8MZGM7AcAaGMzCcgeEMDGdgOAPDGRjOwHAGhjMwnIHhDAxnYDgDwxkYzsBwBoYzMJyB4QwMZ2A4A8MZGG2tb2YYLNvQHHfPAAAAAElFTkSuQmCCIZyPqO4jFE4GWs8m9K+QG3yTcMEt3DjFUHBe4323oB7q7LrniwEsXuBNpGpEcZ5X0TnnJHtRhwnNZxOGGyuywYhKzNZ6RdWfQPfaBPHGrVhBAc6rtYo9fQvGJjSqdcGCt/KMe/NEo1pf0G310AYP57nG9a1865oGcw2uezCPMTahN2weznON61v51jUN5hpc92AeY74USDSqdaF3o3vzjHvzRKNaXxibyOZVrNDb7MyrtYo9fQvWJrRxCwnYg54V/ma9oupPoPtsghe40cWygZ/KiB9uOK+ic85J9qIOE5rn1SJvMlWjhEKJnrwYCe+7BfVQZ9d9NuFF5r7JuGCKwWPiH/MR1X2kEi8GWs8mvGBcgMIdCYUIPgP7OZgxr5Gszb6CukzXfjVRGXGhxI0pJkUKP9znQ76p6lT9aMRA97y6IEbi3cS4saJE/iusw/oiNVRmFq4mvMEGmAsXVjNTiTJfBnEE66aJSpe4mODLiBtcQLioYcMUI7EUXs25X7Be9qIO6rPmRf9BPgE8xGexh/hU/BDfTxzim6JDfGd3iG9PD/E99iF+UXCI33Yc4lc2//3vnVq7Bxh1joLg0P91AAAAAElFTkSuQmCCttoYMS6wEp0GqHUDihppQkPC8zTSDCJ9XuXEQ2v/AGE1hndJg5a4AAAAAElFTkSuQmCC G 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 B iVBORw0KGgoAAAANSUhEUgAAADAAAAAwCAYAAABXAvmHAAAAAXNSR0IArs4c6QAAAARnQU1BAACxjwv8YQUAAAAJcEhZcwAADsMAAA7DAcdvqGQAAADySURBVGhD7ZjRDsMgCEXt/v+fu5HUpFlcKtyL6OQky5564Yi8eJRSzs9vWV7X/7IsL+Byhc5G4iGVHKAJtJr+BVMGFtA0/g1DBNoBpHkB/V4wCzCKC2iOSYDVfAXJUwuwm69Yc1UCXs1XLPnQEs9At4D36Ve0dfaYwKjTr2jq/f8ERp9+pbfuHjswMykQTQpEkwLRpEA0KRBNCkTzKOD1pvlEb909rtDoKWjq7bPEo6agrbPPBATvKVjy1RPwkrDmmq4QWwLJM+8ASwLNgZYYLc44BImgvL1pXvBY0xNoAndaMsym77gIjATagRlIgVhKeQNCoDFT8pT/oQAAAABJRU5ErkJggkOd83oCYG0BVjkF3XN6AmCtAdJPATFf+wlIjUDNhdyC0iKQ82DPgJQI9BzoQ5j+8wkXARpgopaQcgLxAFP3MlKWP81Rol4evPKVwKTFl7gA5cwQiYsvsQHeHYmRvPR3SwT4ZREP4X9mAJgBYAaAGQBmAJgBYAaAGQBmAJgBYAaAGQBmAJgBYAaAGQBmAJgBYAaAGQBmAJgBYAZAjfEAlak/r6JKsfYAAAAASUVORK5CYIJGXWECr67EJkRdIQPrW+0zWL9jYDgDwxkYzsBwBoYzMJyB4QwMZ2A4A8MZGM7AcAaGMzCcgeEMDGdgOAPDGRjOwHAGhjMwnIHhDAxnYDgDwxkYzsBoY3wCZUpN20ZcXUUAAAAASUVORK5CYIJsaAydSOf6zNSz3TdYF6xMeILaiwOH1WZViMcjun3Gws1I672JfGN5kk2BA7egcRVjwfWZ953DeqwT3btj4ck/eJPpGlkc4y5Te2xqL+uAvzTnH/DCjtpgRCdma76j629Wuj0wLNzKHRZA3c11XNK3Y2gi0c0HH3iurvnSurKp5/D478hDgrrOeX6r3npW64TnCdc1hibytk5Q1znPb9Vbz2qd8DzhusaOAyqJbj7U/79s1TVfWle29AxN1OZd7sintVp3cx2X9O1YmcjCLSLgEvjoeel8R9ffWPe9CT/wQg6rDSKmwuddj7tM7bGpvawDquadJ70JukYVCzXdh3rwvnNYj3Wi+94Ek67ZBBxYxfATCAs+R7fPdOLDSOu9CSaAAyycbCwk5EcrhrnRM1PPdt9gXYD2o4nOCAdVaGwxVWT4/HmdK905XT8bAeu+/2lH3u4reYesY5Mg52vT32zBDesLgmBTTXkM7OUcWF68OJiIIAuudTKiCcR3JnjlbIBcxSHY4m3CexDu844mzok3jmqiuwFADLli4a4B8cHnLre30x3i/lU8BmzCTdy8CoNzBoINuF6ePTuYGAkPCXIVbwOYyMFkN0VIFRciHDzv9akhZ8Jyc3O6CQt23YXFp45oTGzdRLCoTniH93Mm5y9Pn55MJJyrgYglG8Qnc/DoJhBkgR11PfhMuI7fFF3F7+yu4renV/F77Kv4i4Kr+NuOq/grm///752m6Rc0cNGvNLILQwAAAABJRU5ErkJggrF0GjaxFdbcxn/ZpH42RowFdqKrAdbaQGJaNZEW4fU0qhnEOe/GwsPDMPwFsb6epOxg5EoAAAAASUVORK5CYII= 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Ma iVBORw0KGgoAAAANSUhEUgAAADAAAAAwCAYAAABXAvmHAAAAAXNSR0IArs4c6QAAAARnQU1BAACxjwv8YQUAAAAJcEhZcwAADsMAAA7DAcdvqGQAAADtSURBVGhD7ZndCsMwCEbTvfjYk3cLRCgjo9HPn2TxQGlvqh6NN+1RSjk/17I82n1ZlhcwOULnsz1cOF7tQRk1gV7Rv9CUgQU4hX+jIQLtAFJ8BX2/IhbQSF5B44gEtIonkHhsAe3iCWlcloBV8YQkPrTEMzAsYN19gptnjwl4dZ/g5Pv/CXh3nxjNu8cOzEwKRJMC0aRANCkQTQpEkwLR3ApYfdO8YzTvHkfIewqcfPsssdcUuHn2mUDFegqS+OwJWElI44qOkLYEEk+8A1oSaBxoidHkGk3Iv5Q9ejKaRV8xEfAE2oEZSIFYSnkDB0AxU4jI0DYAAAAASUVORK5CYII= Or

M Low High Scale High Low - (M M Min - M Max M Min - 106 -^+ / (* Low + :

n s Δ i 1 n range j 1 n range Δ i j el i j + s 1 + ≤ : for for Δ 21 line :

Q1 2232 Δ 0255 Scale : Q2 Q1 1 Q1 rows range Q1 cols 1 range el : Q3 Q1 Q1 rows 1 range Q1 cols 1 range el : Q4 Q1 Q1 rows 1 range 1 Q1 cols range el : Δ Q1 Q2 + Q3 + Q4 + (0255 Scale : 51 sys

iVBORw0KGgoAAAANSUhEUgAAABYAAAAWCAIAAABL1vtsAAAAAXNSR0IArs4c6QAAAARnQU1BAACxjwv8YQUAAAAJcEhZcwAADsMAAA7DAcdvqGQAAABSSURBVDhP7cxBDgAQDETR3v/QgvhBUIqdeKumnam4a/9F8V8Ub7yQgPFI7N+8oB+w2EQ5YbeDZsbajFqNiw2dBkcDCj3uK6SHiEwR1ZDSkdOIeNnj3HFbCNQQAAAAAElFTkSuQmCC Q1 iVBORw0KGgoAAAANSUhEUgAAABYAAAAWCAIAAABL1vtsAAAAAXNSR0IArs4c6QAAAARnQU1BAACxjwv8YQUAAAAJcEhZcwAADsMAAA7DAcdvqGQAAABWSURBVDhP7cxBDoAgEANA//9oIsaJGBVc5OKBORG27ZKGzYliThQ/mcg8v9omBldMZD766e/8dVI++O6heeYSpnbhGKNz5x6g8EjkjXSNVJNog2BNSivYeNxxfHmPOAAAAABJRU5ErkJggg== Q2 iVBORw0KGgoAAAANSUhEUgAAABYAAAAWCAIAAABL1vtsAAAAAXNSR0IArs4c6QAAAARnQU1BAACxjwv8YQUAAAAJcEhZcwAADsMAAA7DAcdvqGQAAABTSURBVDhP7cxJDgAhCETRvv+hSZP4o8YJCBsXvmVRxWcSC70dWkdUl6hYaM+4OzAYcPRh0+PixqwijmBZkAUxVgRx2b3K7lV2r96L5r1obngh8gO4zdxxdNtY3wAAAABJRU5ErkJggg== Q3 iVBORw0KGgoAAAANSUhEUgAAABYAAAAWCAIAAABL1vtsAAAAAXNSR0IArs4c6QAAAARnQU1BAACxjwv8YQUAAAAJcEhZcwAADsMAAA7DAcdvqGQAAABUSURBVDhP7cxJDgAhCERR739oIok/ahwaMC564VtCVSWxJBPBT0R3SFlILxFxoDDj70NnwNONWo9PBM2KcxDlglscfcXhyIUJdWFCvYnmTTR/mBDJujjcccmSHRkAAAAASUVORK5CYII= Q4 iVBORw0KGgoAAAANSUhEUgAAABYAAAAWCAIAAABL1vtsAAAAAXNSR0IArs4c6QAAAARnQU1BAACxjwv8YQUAAAAJcEhZcwAADsMAAA7DAcdvqGQAAABtSURBVDhPtcxBDoAgEANA/v9oI8EJMaC4oM6NbUv63VZ4LDj2B6cppieCIKOO+JH6DaUBxSHVSyoBBg1hmFnlPMk4c1jy3ReZwyTjyjnMrCEMMLikMqQ6oHhD6ZF6RxxkdCKYYlo4LXi7D0lpB7ANjvcXeEE7AAAAAElFTkSuQmCC Δ

M Low High Scale High Low - (M M Min - M Max M Min - 0 + / (* Low + :

... suite

In some instances bias small value

n s Δ i 1 n range j 1 n range Δ i j el i j + s 1 + ≤ : for for Δ 21 line :

M mirror M 1 M rows range M cols 1 range el :

M 2354848 Δ (* :

M tr 5640

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gray 2001632 Δ (* : white 2551632 Δ (* : 21 mat

D M M mirror augment :

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Mesh U, V  within the bounds L, H L H N xd N intervals U 0 : dx H L - N / : i 1 N 1 + (range U i el L dx i * dx - (+ : for U 51 line :

L 1 - :

H 1 :

½ size 'M' N 24 :

U L H N xd :

V U :

x y f 255 x 2^y 2^+ (- 0.25 / exp * :

Insert Gaussian spot in 'M Δelta matrix'
... in the module, 'M' is resident to that effect. x y f U V Sym r 1 : i 1 U rows range c 1 : j 1 V rows range M r c el U i el V j el f eval : c c 1 + : 21 line for r r 1 + : 31 line for M 31 line :

from 'M' ▼ resident in Sym(f(x,y),U,V)

N x y f U V Sym :

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up/dn ... open/close Formated Label x pluto x 0 ≡ ▲ white green 13 mat x 1 ≡ ▼ white red 13 mat x 2 ≡ ◄ ► black yellow 13 mat ► ◄ black magenta 13 mat if if if :

X 012 0.5 14 mat transpose :

X 1 el pluto

down

X 2 el pluto

open

X 3 el pluto

X 4 el pluto hatch, scale

You need that one for scaling grayscale image M lo hi Scale hi lo - (M M Min - M Max M Min - / (* lo + :

Erzeugt eine Matrix für die Darstellung vertikaler Linien zwischen den Funktionen f(x) und 
g(x) im Bereich von x1 bis x2 mit 2*n Linien. Generates a matrix for 2*N vertical lines (hatching) 
between functions f(x) and g(x) in x-range from x1 to x2 f g x.1 x.2 N hatch dx x.2 x.1 - N / (: h x.1 x.1 f x.1 x.1 g 22 mat : x x.1 x.2 dx - x.1 dx + range h h x dx 2 / + x dx 2 / + g x dx 2 / + x dx 2 / + f x dx + x dx + f x dx + x dx + g 42 mat stack : for h 41 line :

extrema
condition
amplitude α 1 : β 0 : m 1.25 : 31 sys

Bar plot simple ...

x Ψ m x α - ≥ (x β - ≤ (* x β ≥ (x α ≤ (* + 0 cases :

x f x Ψ abs (2^:

x g 0 :

p f g α - α 20 hatch :

max p 12 el : 1.5625

p 0 5 0 0 2 2 mat 2 1 sys

max 1.5625

calipers an image ... explore below

λ η m M 0 : i 1 λ range j 1 η range M i j el 255 : for for M 31 line :

'λ' length, 'η' thickness
margin(λ,η)... slide  ◄ ►  ... ▲ ▼
color scheme ω 0 : λ 100 : η 16 : 12 mat ω λ η m : cl 1 ω * 0.5 ω * 0 ω * 13 mat : 41 sys

Horizontal tank . . . process control symbol

]]> B-Companion adapted/compacted from Davide original

ndp p SVG t-> interpolation points [0,1] ... p-> control points t p DeCasteljau M 1 t - (p 1 row * t p 2 row * + : p rows 2 > i 2 p rows 1 - range M M 1 t - (p i row * t p i 1 + row * + stack : for t M DeCasteljau 21 line M if 21 line : t-> range of interpolation points [0,1] ... p-> control points t p DeCasteljauRange M t 1 el p DeCasteljau : i 2 t length range M M t i el p DeCasteljau stack : for M 31 line : ndp-> number of discretised points [>1] ... p-> control points t 011 ndp 1 - / range : M t 1 el p DeCasteljau : i 2 t length range M M t i el p DeCasteljau stack : for M 91 line :

pilot the thank svg 1 :

NDP 10 :

cap svg 020 - 00255023 mat 1001201005025023 mat 12 mat transpose * :

cyl svg 0000505023 mat 1001001005050023 mat 10000022 mat 13 mat transpose * :

b1 NDP cap 1 el SVG : i 2 cap length range b1 b1 NDP cap i el SVG stack : for 21 line

L cyl 2 el 1 el : ID cyl 2 el 2 el : V π 4 / ID 2^* L * : 31 sys 10050 1.9635 105^* 31 sys

b2 NDP cyl 1 el SVG : i 2 cyl length range b2 b2 NDP cyl i el SVG stack : for 21 line

cyl 1 el 0005005032 mat

2 cyl length range 2321 mat

truncate left of decimal Number part Trunc part Number part / 0 round * :

V V 10 Trunc :

m³ 1 :

Volume of the caps are subject to Pressurized Vessel Standards ... Typical: TEMA [Tubular Exchanger Manufacturers Association

svg 1

b1 b2 2 1 sys

V m³ 2105^*

ID 50

L 100

Wind mill . . . project

]]> f1, f2, f3

f1 00 0.006 - 0.004 0.012 - 0.007 0.019 - 0.011 0.025 - 0.015 0.031 - 0.019 0.038 - 0.022 0.044 - 0.026 0.05 - 0.03 0.056 - 0.034 0.062 - 0.038 0.069 - 0.042 0.075 - 0.046 0.081 - 0.05 0.088 - 0.055 0.094 - 0.059 0.1 - 0.063 0.106 - 0.067 0.112 - 0.072 0.119 - 0.076 0.125 - 0.081 0.131 - 0.085 0.138 - 0.09 0.144 - 0.094 0.15 - 0.099 0.156 - 0.104 0.162 - 0.109 0.169 - 0.113 0.175 - 0.118 0.181 - 0.123 0.188 - 0.128 0.194 - 0.133 0.2 - 0.138 0.206 - 0.144 0.212 - 0.149 0.219 - 0.154 0.225 - 0.16 0.231 - 0.165 0.238 - 0.17 0.244 - 0.176 0.25 - 0.182 0.256 - 0.187 0.262 - 0.193 0.269 - 0.199 0.275 - 0.205 0.281 - 0.211 0.288 - 0.217 0.294 - 0.223 0.3 - 0.229 0.306 - 0.236 0.312 - 0.242 0.319 - 0.249 0.325 - 0.255 0.331 - 0.262 0.338 - 0.269 0.344 - 0.276 0.35 - 0.283 0.356 - 0.29 0.362 - 0.297 0.369 - 0.304 0.375 - 0.312 0.381 - 0.319 0.388 - 0.327 0.394 - 0.335 0.4 - 0.343 0.406 - 0.351 0.412 - 0.359 0.419 - 0.368 0.425 - 0.376 0.431 - 0.385 0.438 - 0.394 0.444 - 0.404 0.45 - 0.413 0.456 - 0.423 0.462 - 0.433 0.469 - 0.443 0.475 - 0.454 0.481 - 0.465 0.488 - 0.476 0.494 - 0.488 0.5 - 0.5 0.506 - 0.513 0.512 - 0.526 0.519 - 0.54 0.525 - 0.555 0.531 - 0.572 0.538 - 0.589 0.544 - 0.609 0.55 - 0.632 0.556 - 0.661 0.556 - 0.783 0.55 - 0.803 0.544 - 0.818 0.538 - 0.829 0.531 - 0.838 0.525 - 0.846 0.519 - 0.852 0.512 - 0.857 0.506 - 0.862 0.5 - 0.866 0.494 - 0.869 0.488 - 0.872 0.481 - 0.874 0.475 - 0.876 0.469 - 0.878 0.462 - 0.879 0.456 - 0.88 0.45 - 0.88 0.444 - 0.88 0.438 - 0.88 0.431 - 0.879 0.425 - 0.879 0.419 - 0.878 0.412 - 0.876 0.406 - 0.875 0.4 - 0.873 0.394 - 0.871 0.388 - 0.869 0.381 - 0.867 0.375 - 0.864 0.369 - 0.861 0.362 - 0.858 0.356 - 0.855 0.35 - 0.852 0.344 - 0.848 0.338 - 0.844 0.331 - 0.84 0.325 - 0.836 0.319 - 0.831 0.312 - 0.827 0.306 - 0.822 0.3 - 0.817 0.294 - 0.812 0.288 - 0.806 0.281 - 0.801 0.275 - 0.795 0.269 - 0.789 0.262 - 0.783 0.256 - 0.776 0.25 - 0.769 0.244 - 0.763 0.238 - 0.755 0.231 - 0.748 0.225 - 0.74 0.219 - 0.733 0.212 - 0.725 0.206 - 0.716 0.2 - 0.708 0.194 - 0.699 0.188 - 0.69 0.181 - 0.68 0.175 - 0.671 0.169 - 0.661 0.162 - 0.65 0.156 - 0.64 0.15 - 0.629 0.144 - 0.617 0.138 - 0.605 0.131 - 0.593 0.125 - 0.581 0.119 - 0.568 0.112 - 0.554 0.106 - 0.54 0.1 - 0.525 0.094 - 0.51 0.088 - 0.494 0.081 - 0.477 0.075 - 0.46 0.069 - 0.442 0.062 - 0.422 0.056 - 0.402 0.05 - 0.38 0.044 - 0.356 0.038 - 0.33 0.031 - 0.302 0.025 - 0.271 0.019 - 0.235 0.012 - 0.193 0.006 - 0.137 001802 mat :

f2 0.011 0.006 0.022 0.013 0.033 0.019 0.044 0.025 0.056 0.031 0.067 0.036 0.078 0.042 0.089 0.047 0.1 0.053 0.111 0.058 0.122 0.063 0.133 0.068 0.144 0.073 0.156 0.078 0.167 0.083 0.178 0.087 0.189 0.092 0.2 0.096 0.211 0.101 0.222 0.105 0.233 0.109 0.244 0.113 0.256 0.117 0.267 0.121 0.278 0.124 0.289 0.128 0.3 0.131 0.311 0.135 0.322 0.138 0.333 0.141 0.344 0.144 0.356 0.147 0.367 0.15 0.378 0.153 0.389 0.155 0.4 0.158 0.411 0.16 0.422 0.162 0.433 0.165 0.444 0.167 0.456 0.169 0.467 0.17 0.478 0.172 0.489 0.174 0.5 0.175 0.511 0.177 0.522 0.178 0.533 0.179 0.544 0.18 0.556 0.181 0.567 0.182 0.578 0.183 0.589 0.183 0.6 0.184 0.611 0.184 0.622 0.184 0.633 0.185 0.644 0.184 0.656 0.184 0.667 0.184 0.678 0.183 0.689 0.183 0.7 0.182 0.711 0.181 0.722 0.18 0.733 0.178 0.744 0.177 0.756 0.175 0.767 0.173 0.778 0.171 0.789 0.169 0.8 0.166 0.811 0.163 0.822 0.16 0.833 0.157 0.844 0.153 0.856 0.149 0.867 0.145 0.878 0.14 0.889 0.135 0.9 0.13 0.911 0.123 0.922 0.117 0.933 0.109 0.944 0.101 0.956 0.091 0.967 0.079 0.978 0.065 0.989 0.047 1010 0.989 0.047 - 0.978 0.065 - 0.967 0.079 - 0.956 0.091 - 0.944 0.101 - 0.933 0.109 - 0.922 0.117 - 0.911 0.123 - 0.9 0.13 - 0.889 0.135 - 0.878 0.14 - 0.867 0.145 - 0.856 0.149 - 0.844 0.153 - 0.833 0.157 - 0.822 0.16 - 0.811 0.163 - 0.8 0.166 - 0.789 0.169 - 0.778 0.171 - 0.767 0.173 - 0.756 0.175 - 0.744 0.177 - 0.733 0.178 - 0.722 0.18 - 0.711 0.181 - 0.7 0.182 - 0.689 0.183 - 0.678 0.183 - 0.667 0.184 - 0.656 0.184 - 0.644 0.184 - 0.633 0.185 - 0.622 0.184 - 0.611 0.184 - 0.6 0.184 - 0.589 0.183 - 0.578 0.183 - 0.567 0.182 - 0.556 0.181 - 0.544 0.18 - 0.533 0.179 - 0.522 0.178 - 0.511 0.177 - 0.5 0.175 - 0.489 0.174 - 0.478 0.172 - 0.467 0.17 - 0.456 0.169 - 0.444 0.167 - 0.433 0.165 - 0.422 0.162 - 0.411 0.16 - 0.4 0.158 - 0.389 0.155 - 0.378 0.153 - 0.367 0.15 - 0.356 0.147 - 0.344 0.144 - 0.333 0.141 - 0.322 0.138 - 0.311 0.135 - 0.3 0.131 - 0.289 0.128 - 0.278 0.124 - 0.267 0.121 - 0.256 0.117 - 0.244 0.113 - 0.233 0.109 - 0.222 0.105 - 0.211 0.101 - 0.2 0.096 - 0.189 0.092 - 0.178 0.087 - 0.167 0.083 - 0.156 0.078 - 0.144 0.073 - 0.133 0.068 - 0.122 0.063 - 0.111 0.058 - 0.1 0.053 - 0.089 0.047 - 0.078 0.042 - 0.067 0.036 - 0.056 0.031 - 0.044 0.025 - 0.033 0.019 - 0.022 0.013 - 0.011 0.006 - 1802 mat :

f3 00 0.006 - 0.004 - 0.012 - 0.007 - 0.019 - 0.011 - 0.025 - 0.015 - 0.031 - 0.019 - 0.038 - 0.022 - 0.044 - 0.026 - 0.05 - 0.03 - 0.056 - 0.034 - 0.062 - 0.038 - 0.069 - 0.042 - 0.075 - 0.046 - 0.081 - 0.05 - 0.088 - 0.055 - 0.094 - 0.059 - 0.1 - 0.063 - 0.106 - 0.067 - 0.112 - 0.072 - 0.119 - 0.076 - 0.125 - 0.081 - 0.131 - 0.085 - 0.138 - 0.09 - 0.144 - 0.094 - 0.15 - 0.099 - 0.156 - 0.104 - 0.162 - 0.109 - 0.169 - 0.113 - 0.175 - 0.118 - 0.181 - 0.123 - 0.188 - 0.128 - 0.194 - 0.133 - 0.2 - 0.138 - 0.206 - 0.144 - 0.212 - 0.149 - 0.219 - 0.154 - 0.225 - 0.16 - 0.231 - 0.165 - 0.238 - 0.17 - 0.244 - 0.176 - 0.25 - 0.182 - 0.256 - 0.187 - 0.262 - 0.193 - 0.269 - 0.199 - 0.275 - 0.205 - 0.281 - 0.211 - 0.288 - 0.217 - 0.294 - 0.223 - 0.3 - 0.229 - 0.306 - 0.236 - 0.312 - 0.242 - 0.319 - 0.249 - 0.325 - 0.255 - 0.331 - 0.262 - 0.338 - 0.269 - 0.344 - 0.276 - 0.35 - 0.283 - 0.356 - 0.29 - 0.362 - 0.297 - 0.369 - 0.304 - 0.375 - 0.312 - 0.381 - 0.319 - 0.388 - 0.327 - 0.394 - 0.335 - 0.4 - 0.343 - 0.406 - 0.351 - 0.412 - 0.359 - 0.419 - 0.368 - 0.425 - 0.376 - 0.431 - 0.385 - 0.438 - 0.394 - 0.444 - 0.404 - 0.45 - 0.413 - 0.456 - 0.423 - 0.462 - 0.433 - 0.469 - 0.443 - 0.475 - 0.454 - 0.481 - 0.465 - 0.488 - 0.476 - 0.494 - 0.488 - 0.5 - 0.5 - 0.506 - 0.513 - 0.512 - 0.526 - 0.519 - 0.54 - 0.525 - 0.555 - 0.531 - 0.572 - 0.538 - 0.589 - 0.544 - 0.609 - 0.55 - 0.632 - 0.556 - 0.661 - 0.556 - 0.783 - 0.55 - 0.803 - 0.544 - 0.818 - 0.538 - 0.829 - 0.531 - 0.838 - 0.525 - 0.846 - 0.519 - 0.852 - 0.512 - 0.857 - 0.506 - 0.862 - 0.5 - 0.866 - 0.494 - 0.869 - 0.488 - 0.872 - 0.481 - 0.874 - 0.475 - 0.876 - 0.469 - 0.878 - 0.462 - 0.879 - 0.456 - 0.88 - 0.45 - 0.88 - 0.444 - 0.88 - 0.438 - 0.88 - 0.431 - 0.879 - 0.425 - 0.879 - 0.419 - 0.878 - 0.412 - 0.876 - 0.406 - 0.875 - 0.4 - 0.873 - 0.394 - 0.871 - 0.388 - 0.869 - 0.381 - 0.867 - 0.375 - 0.864 - 0.369 - 0.861 - 0.362 - 0.858 - 0.356 - 0.855 - 0.35 - 0.852 - 0.344 - 0.848 - 0.338 - 0.844 - 0.331 - 0.84 - 0.325 - 0.836 - 0.319 - 0.831 - 0.312 - 0.827 - 0.306 - 0.822 - 0.3 - 0.817 - 0.294 - 0.812 - 0.288 - 0.806 - 0.281 - 0.801 - 0.275 - 0.795 - 0.269 - 0.789 - 0.262 - 0.783 - 0.256 - 0.776 - 0.25 - 0.769 - 0.244 - 0.763 - 0.238 - 0.755 - 0.231 - 0.748 - 0.225 - 0.74 - 0.219 - 0.733 - 0.212 - 0.725 - 0.206 - 0.716 - 0.2 - 0.708 - 0.194 - 0.699 - 0.188 - 0.69 - 0.181 - 0.68 - 0.175 - 0.671 - 0.169 - 0.661 - 0.162 - 0.65 - 0.156 - 0.64 - 0.15 - 0.629 - 0.144 - 0.617 - 0.138 - 0.605 - 0.131 - 0.593 - 0.125 - 0.581 - 0.119 - 0.568 - 0.112 - 0.554 - 0.106 - 0.54 - 0.1 - 0.525 - 0.094 - 0.51 - 0.088 - 0.494 - 0.081 - 0.477 - 0.075 - 0.46 - 0.069 - 0.442 - 0.062 - 0.422 - 0.056 - 0.402 - 0.05 - 0.38 - 0.044 - 0.356 - 0.038 - 0.33 - 0.031 - 0.302 - 0.025 - 0.271 - 0.019 - 0.235 - 0.012 - 0.193 - 0.006 - 0.137 - 001802 mat :

svg 1 :

Eol system in there

x c svg 2^x 2^- sqrt ± : θ π 5 / - : 12 mat Eol f1 f2 f3 stack : θ rot θ cos θ sin - θ sin θ cos 22 mat : 31 sys

Smath 2D vector rotation system t Eol Eol θ π 30 / t * + rot * eval :

Hub 00.15 red 15 mat : step1 060 range : 21 line

svg Eol * x c 2 1 sys

Eol svg t Eol * x c Hub 31 sys :

Smath "Wind Mill" project

Eol

Filtrate bin . . . process control symbol

]]> hatch

Erzeugt eine Matrix für die Darstellung vertikaler Linien zwischen den Funktionen f(x) und 
g(x) im Bereich von x1 bis x2 mit 2*n Linien. Generates a matrix for 2*n vertical lines (hatching) between functions f(x) and g(x)
in x-range from x1 to x2 f g x.1 x.2 N hatch dx x.2 x.1 - N / (: h x.1 x.1 f x.1 x.1 g 22 mat : x x.1 x.2 dx - x.1 dx + range h h x dx 2 / + x dx 2 / + g x dx 2 / + x dx 2 / + f x dx + x dx + f x dx + x dx + g 42 mat stack : for h 41 line :

DeCasteljau

Understanding SVG

Model from jmG Mathcad 8 Pro. made work in Smath by Dave Carpi

t = interpolation point in [0,1]
p = control points t p DeCasteljau De Casteljau SMath M 1 t - (p 1 row * t p 2 row * + : p rows 2 > i 2 p rows 1 - range M M 1 t - (p i row * t p i 1 + row * + stack : for t M DeCasteljau 21 line M if 31 line :

t = range of interpolation points in [0,1]
p = control points t p DeCasteljauRange M t 1 el p DeCasteljau : i 2 t length range M M t i el p DeCasteljau stack : for M 31 line :

ndp =  number of discretization points (> 1)
p = control points ndp p DeCasteljauNDP t 011 ndp 1 - / range : M t 1 el p DeCasteljau : i 2 t length range M M t i el p DeCasteljau stack : for M 41 line :

data spec pts i 1 data rows range p i el a b c spec : for v p 1 el : Unest 'p' j 2 p rows range v v p j el stack : for data v augment 51 line :

XY 100020201015 - 05050015 - 26 mat transpose :

a b c spec . 14 black 13 mat :

xy XY a b c spec pts :

data n Decimate collect every 'n' pairs range 1 data rows n range : k 1 : i range u k el data i 1 el : v k el data i 2 el : k k 1 + : 31 line for u v augment 31 line 31 line :

NDP 50 :

svg 1 :

roof

filtrate level LV 25 :

p svg 1010015 - 15 - 023 mat 000005023 mat 0102050605023 mat 202020500023 mat 201010015 - 15 - 23 mat 200000023 mat 02020 LV LV LV 23 mat 200050505023 mat 18 mat transpose * :

bin NDP p 1 el DeCasteljauNDP :

i 2 p length range bin bin NDP p i el DeCasteljauNDP stack : for

bin rows 400

ε 1 :

m³ 1 :

level bin 306326 range 12 range el :

x y axes x y / - :

x f 0 x * ε + : x g 0 x * LV ε - (+ : 12 mat Hatch x f x g 0.5 19.5 20 hatch : 21 sys

bin level Hatch 3 1 sys

volume π 4 / 202^* LV * svg * : m³ 7854

LV 25

Trunion valve . . . process control symbol

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svg 0.75 :

valve svg 1 - 0.5 1 0.5 - 1 0.5 1 - 0.5 - 1 - 0.5 000 0.5 0.5 0.5 82 mat * :

valve 0 0 . 20 red 1 5 mat 2 1 sys

Control valve . . . process control symbol

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Globe valve 15 range 12 range el : globe Globe 1 col Globe 2 col 1 - augment : 21 sys

DeCasteljau

Understanding SVG

Model from jmG Mathcad 8 Pro. made work in Smath by Dave Carpi

t = interpolation point in [0,1]
p = control points t p DeCasteljau De Casteljau SMath M 1 t - (p 1 row * t p 2 row * + : p rows 2 > i 2 p rows 1 - range M M 1 t - (p i row * t p i 1 + row * + stack : for t M DeCasteljau 21 line M if 31 line :

t = range of interpolation points in [0,1]
p = control points t p DeCasteljauRange M t 1 el p DeCasteljau : i 2 t length range M M t i el p DeCasteljau stack : for M 31 line :

ndp =  number of discretization points (> 1)
p = control points ndp p DeCasteljauNDP t 011 ndp 1 - / range : M t 1 el p DeCasteljau : i 2 t length range M M t i el p DeCasteljau stack : for M 41 line :

data spec pts i 1 data rows range p i el a b c spec : for v p 1 el : Unest 'p' j 2 p rows range v v p j el stack : for data v augment 51 line :

XY 100020201015 - 05050015 - 26 mat transpose :

a b c spec . 14 black 13 mat :

xy XY a b c spec pts :

data n Decimate collect every 'n' pairs range 1 data rows n range : k 1 : i range u k el data i 1 el : v k el data i 2 el : k k 1 + : 31 line for u v augment 31 line 31 line :

svg svg : NDP 40 : 12 mat

actuator 0001 - 22 mat svg 0 0.25 - 0.5 0.25 - 0.5 0.75 - 0 0.75 - 0 0.25 - 52 mat * 21 sys :

p svg 1 - 0100023 mat 1 - 0101023 mat 12 mat transpose * :

diaphragm NDP p 1 el DeCasteljauNDP :

i 2 p length range diaphragm diaphragm NDP p i el DeCasteljauNDP stack : for

local 1.25 :

diaphragm actuator globe 3 1 sys local diaphragm actuator globe 3 1 sys *

The red actuator is savant. It is delivereed by the valve manufacturer. In itself, it is a "servomechanism" ... It receives the 4-20 mA signal from the controller. Converts in diaphragm pneumatic 3-15 psi Via a mechanical Laplace servo, it auto-stabilizes on the input governing signal [4-20 mA]. This advanced technology dates back years 1940 and earlier.

Pump . . . process control symbol

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svg 0.75 :

Circle definition t u D u 2 el u 1 el - 21 mat :

out svg 01 1.25 1 1.25 0.51 0.861 0.51 42 mat * :

t0 0 : t1 2 π * : N 200 : 31 line

unary radius
clockwise IC 0121 mat :

Either 'rkfixed' or 'Rkadapt' s IC t0 t1 N t u D rkfixed :

base 0.861 svg * - 0.51 svg * - svg - svg - svg svg - 0.861 svg * 0.51 svg * - 42 mat :

x s 1 col : X s 2 col : Y s 3 col : 13 mat C svg X Y augment (* : 21 mat

C out base 3 1 sys

pump C out base stack :

The line can be removed ... through reverse circulation

pump C out stack base 2 1 sys

Illustrate . . . arrow

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θ rot θ cos θ sin - θ sin θ cos 22 mat :

point 6 : svg 0.75 : quadrant 4 : 31 sys

θ π - 4 / : ° 45 -

arrow svg 1 - 2 - 1 - 12 - 10 point 211112 - 1 - 2 - 82 mat * :

Rot arrow θ rot * :

plot arrow quadrant + quadrant 10 quadrant 10 - 22 mat Rot quadrant - 10 - quadrant - 10 quadrant - 22 mat 41 sys :

plot

Circle generatrix ... main circle

Y Clear 1

A 022 - 022 mat :

t Y D A Y 1 el Y 2 el 21 mat * :

A dn_LinAlgEigenvalues 44 - 21 mat

N 200 : span 1 : α 1 π * : (overlap ≡ 31 line

t Y D 2 Y 2 el * 2 Y 1 el * - 21 mat

Circle U0 00013 mat : p 1 W1 p span 21 mat : U1 W1 0 α N t Y D rkfixed : U0 U0 U1 stack : 31 line for B1 U0 3 col U0 2 col augment : B1 2 B1 rows 1 B1 cols submatrix 41 line :

r 12 sqrt / 0.25 0.5 0.75 1.5 261 mat :

C Circle_1 r 1 el Circle * : Circle_2 r 2 el Circle_1 * : Circle_3 r 3 el Circle_1 * : Circle_4 r 4 el Circle_1 * : Circle_5 r 5 el Circle_1 * : Circle_6 r 6 el Circle_1 * : 61 sys :

Radial construction of 'r=2 in A' or user

Circle 2 sqrt 2 2 sqrt 2 - 2 2 mat 2 1 sys

Radial plot is essentially built from Rkadapt suject to user parameters [radius,t0,t1,N]

--------
radius circle
-------- Y0 02031 mat :

t0 0 : t1 2 π * : N 12 : 31 line

Rkadapt Radial

Rename: Y => .. else variable name t u D u 2 el u 3 el 1 u 1 el (2^- (* u 2 el * (u 1 el - 031 mat :

Either 'rkfixed' or 'Rkadapt' s Y0 t0 t1 N t u D Rkadapt :

x s 1 col : X s 2 col : Y s 3 col : 31 line

U x X augment : V x Y augment : XY X Y augment : 31 line

data char size clr plot k 1 data rows range r3 k el char : r4 k el size : r5 k el clr : 13 mat for data r3 r4 r5 augment 21 line :

U U . 10 blue plot : V V . 10 red plot : polar XY . 10 green plot : 31 line

polar U V 2 1 sys Radial Stem

Core component of the stem style P v replicate k 1 : i 1 v length range P i el 1 ≡ continue j 1 P i el range T k j + el v i el : for k k P i el + : 21 line if for T 31 line :

Stem construction vy stem N vy length : i 1 N range q i el 3 : q N el 2 : 21 line for 11 line i 1 N range v i el i : for i 1 N range S 3 i * el vy i el : for u q v replicate : V u S augment : V V 3 V rows 12 submatrix : 71 line :

SOL X Y augment : radial SOL 1 col stem 2 col SOL 2 col stem 2 col augment : 21 sys

'n' intervals in range n range interval j 1 n 1 + (range h j el range - range j * + n / : for h 21 line :

x y axes x y / - :

a 1.5 :

ω 502 π * interval :

θ rot θ cos θ sin - θ sin θ cos 22 mat :

G vx 0 : vy 0 : 12 mat i 1 ω rows range vx i el a ω i el sin * eval : vy i el a ω i el sin * ω i el cos * eval : 21 line for vx vy augment 31 line :

θ π - 2 / :

ω ω rows row 6.2832 11 mat

C radial axes G θ rot * 4 1 sys

Illustrate . . . exclusive region image matrix

]]> Planet matrix 'M'

M 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mat :

trim 40 :

M rows M cols 12 mat 23923912 mat

sub M trim M rows trim - (range trim M cols trim - (range el :

Lune Planet sub : fg 235 : r 60 : 12 mat ε 1 : (ε=1 circle ... ε≠1 oblate/prolate ≡ cx 120 trim - : cy 120 trim - : 12 mat 41 sys

Planet rows Planet cols 12 mat 16016012 mat

lune i 1 Planet rows range j 1 Planet cols range lune i j el fg i cx - (2^ε j cy - (2^(* + r 2^≥ Planet i j el cases : for for lune 21 line eval :

4 appVersion 0.98.6179.21440 ≡ Timing 2 min 30 sec ≡ 21 mat

Cyan
Yellow 0 lune - (* lune - lune - 13 mat lune - lune - 0 lune - (* 13 mat 21 sys

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 0 lune - ( * lune - lune - 1 3 mat 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 lune 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 1 lune - ( * 1 lune - ( * 0 lune - ( * 1 3 mat 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

original Planet

λ η m M 0 : i 1 λ range j 1 η range M i j el 255 : for for M 31 line :

'λ' length, 'η' thickness
margin(λ,η)... slide  ◄ ►  ... ▲ ▼
color scheme ω 0 : λ 160 : η 3 : 12 mat ω λ η m : V 1 ω * 0 ω * 0 ω * 13 mat : 41 sys

'λ' length, 'η' thickness
margin(λ,η)... slide  ◄ ►  ... ▲ ▼
color scheme ω 0 : λ 2 : η 160 : 12 mat ω λ η m : H 1 ω * 0 ω * 0 ω * 13 mat : 41 sys

svg 1 ≡ native contrast
experiment svg := ± 1.25 svg 1 :

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 lune svg *

The best zooming utilty is WnGrab ... it zooms by pixels. IrfanView is a good utility but zooms by % ... m(λ,η)is convenient to avoid misshandling image handles. Experiment 'svg' for user in-situ contrast @ will.

m random m m bar #808080 white 13 mat

Code aapted from Martin Kraska x y n bar Martin random bar full █ : dot ░ : s : x x eval : j 1 n range x y / j n / > s s full concat (: s s dot concat (: if for s 71 line :

STEPS to full:="" ... [similar dot:=""] 1. Get the MS Charmap from task bar 2. Select 'Font' ... Arial (suggested) 3. Click/select on symbol you want 4. Copy from Charmap 5. Paste in full:="█" 6. Once pasted, type any alpha/numeric that will invoque the pasted symbol. 7. Backspace to remove the alpha/numeric 8. Brush over, click "settings" ....... demo MicrosoftSansSerif 8

@ 20 ... bin ½ full level 20 : y 40 : n 40 : 13 mat

bin level y n bar #808080 pink 13 mat level 20 ≡ level y n bar #808080 yellow 13 mat 20 level < (level 40 < (& level y n bar #808080 lime 13 mat level 40 ≡ ... ◄  bin below mid level cases :

bin

Export this section ... set AutoCal mode

Utilities ... data

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 :

data 11110001011000110101100083 mat :

You need that one for scaling grayscale image M lo hi Scale hi lo - (M M Min - M Max M Min - 1012 -^+ / (* lo + :

For convenience: Auto-Calculation

Aarm scan from data logging or on actual "Plant scan"

collapsed utilities data data 0255 Scale :

Cumulative process scan
[P,L,T] alarm operators.
[P,L,T] Pressure/Level/°C data 11110001011000110101100083 mat ≡

Ladder data j row 2020 zoomfract : alarm Ladder 0 Ladder * 0 Ladder * 13 mat : 21 sys Batch data 8 row 2020 zoomfract : Cntrl 0 Batch (* 1 Batch 255 + (* 0 Batch (* 13 mat : 21 sys 21 sys

OPERATORS Alarm Panel 1. at the start of the batch process no condition [P,L,T] are met ... all red 2. as the process goes, some conditions are under control ... less red. 3. as the time lapses "under control" all conditions are finally OK ... all green. 4. "data" from data logging time back-scan.

PanAlarm alarm 1 j ≤ (j 7 ≤ (& Cntrl j 8 ≡ scan complete cases :

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P..L..T

PanAlarm

black is simply NO alarm on that particular [P, L, T] data logging Process scan.

Rod mill ... export this section ... shadow in context

'n' population
'w' aperture  
radius OD n 2000 : w 1.125 : OD 3.5 : 31 sys

size 100 :

svg 0.625 :

Disk j 1 n range rod j el OD w i 2 * π * j w / *^eval * : for rod Re rod Im augment 21 line :

1 - 1 - . size gray 1 5 mat 1 1 - . size gray 1 5 mat 0 0 . size gray 1 5 mat svg Disk * 6 1 sys

1 - 1 - . size gray 15 mat 11 - . size gray 15 mat 00 . size gray 15 mat svg Disk * 61 sys