8a7ed8a0-fd03-4528-9bcc-e324a0dd1689 25 4 5 decimal

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

vx vy char size clr plotG n vx length : plot vx 1 el vy 1 el char size clr augment : i 2 n range plot plot vx i el vy i el char size clr augment stack : for plot 41 line :

Error stem plot for QuickPlot unicolor data Error stemX 1 data rows range : i 1 stemX rows range stem i el data i 1 el data i 2 el data i 1 el 022 mat : for i 1 stem rows 1 - range stem i el stem i el stem i 1 + (1 el 1 el 012 mat stack : for V stem 1 el : j 2 stem rows 1 - range V V stem j el stack : for V V data data rows row stack : 71 line :

Applicable parts are: Optimiz "numeric" XY f φ β Minimize X XY 1 col : Y XY 2 col : n XY rows : k x β φ length 1 - : vx-> raw initial vector fit i 1 X length range vx i el X i el β f eval : for M-> Cholesky GradientMatrix j 1 k range i 1 n range M i j el X i el β φ j 1 + el eval : for for CholeskySolver LeastSquares Φ M transpose M * : d M transpose Y vx - (* : Δβ Φ 1 -^eval d * : b β Δβ + : 131 line :

L H N xd U 0 : dx H L - N / : i 1 N 1 + range U i el L dx - (dx i * + : for U 41 line :

Module xd(L,H,N) is a discretiser for use in-situ [user spec's]: range [L,H], density [N].

Vector gradient ... Optimiz Symbolic x β f n φ ct 1 : i 1 n range PD ct el x β f (β ct el diff : stack f(x,β) & PD V 1 el x β f : V i 1 + el PD i el : 21 line ct ct 1 + : 41 line for V 31 line :

Bar plot unicolor style, bar width user. data dt BarSize v data 2 col : t v bar t dt - 0 t dt - v t dt + v t dt + 042 mat : j 1 data rows range j 1 ≡ B data j 1 el data j 2 el bar : B B data j 1 el data j 2 el bar stack : if 11 line for B 41 line :

data 00 8.53 14.15 12.79 26.94 16.28 40.18 19.38 53.42 23.64 66.67 31.01 79.91 40.7 89.04 50 93.61 62.02 95.89 72.87 96.8 79.07 97.26 92.64 97.72 132 mat :

XY select 247101215 mat : ct 1 : i select a ct el data i 1 el : b ct el data i 2 el : ct ct 1 + : 31 line for a b augment 41 line :

X XY 1 col : Y XY 2 col : 21 line

x β f β 1 el 1 x β 4 el - β 2 el / (β 3 el^- exp - (* :

Model function

in φ(x,β,f,n) -> set 'n' to last index β # el ≡

x β φ x β f 4 φ :

<= ConjugateGradient Vector Fnct

β 9721 1.5 041 mat :

re-inject to iterate manually

Genfit coeff's of fit β XY f φ β Minimize :

β 96.5995 23.3563 1.8248 0.2939 - 41 mat

FIT range, populate U 0100 0.05 range : i 1 U rows range FIT i el U i el β f eval : for U FIT augment 41 line :

X data 1 col : Y data 2 col : Data X Y . 10 black plotG : 31 line

Relative residuals Residuals i 1 data rows range Δ i el Y i el X i el β f - eval : for X Δ augment 21 line :

Data FIT 2 1 sys Residuals 1 BarSize 0 2 1 sys

α β δ K.p 41 mat 8.97 8.9768 3.067 97.284 41 mat :

B a k xc 41 mat 1.0115 - 99 0.101 14.5 41 mat :

1.0115 - 99 0.101 14.5 41 mat

x y B a k x xc - (* - exp - (exp (* + :

0 y 0.2981

x Xfr K.p x δ - Heaviside * β - α + α x δ - (- α / exp * - β x δ - (- β / exp * + β α - / * - :

x Oxy_1 x y 0 x ≤ (x xc ≤ (& N/A cases :

x Oxy_2 x Xfr xc x ≤ (x 100 ≤ (& N/A cases :

x Oxy_1 x Oxy_2 xc 35.4 + 100 green 1 5 mat Data 4 1 sys

xc Oxy_1 xc Oxy_2 21 mat 35.4086 35.4088 21 mat

more 00 0.78 0.46 1.94 1.37 2.33 2.28 3.1 3.2 3.88 4.57 4.65 5.94 5.43 7.31 5.81 8.22 6.59 9.59 7.36 11.42 8.53 14.15 122 mat :

vx more 1 col : vy more 2 col : Low vx vy . 10 black plotG : 31 line

Low x Oxy_1 2 1 sys