Items tagged with matrix

Consider the following code:

LM := [
   Matrix([[1,2],[3,4]]),
   Matrix([[5,6],[7,8]])
];
A := Matrix([[0,1],[1,0]]);
map(x -> A . x,LM);
A .~ LM;

where LM is a list of two matrices (just a test example), and A is some (test)matrix that I want to multiply onto each of these two matrices from the left, say. The map-construction works, as expected, but the elementwise operation .~ produces an error. Why?

Hello, im a total begineer with maple and i need help defining a matrix, i need to get this into a matrix

 anyone knows how could i put this in a matriz of n x 1?   (the one thats only a column)

any help would be greatly appreciated

 

Thanks in advance!

Hello I was trying to manipulate maple to write a procedure checking a matrix , say A with n rows and n columns. That matrix A given any row/column the sum of the entries for every row and column are equal. For example matrix [(-1,2)(2,-1)], every row and column in this matrix sums to 1. The entries in the matrix can be any real number.

Hi

I would like to extract the Anew matrix from the old matrix A. such that each row from Anew matrix has a square form of old matrix i.e all number from each row in the Anew form a square in my old matrix A ...

Is there any loop to determie  the Anew matrix in general  case

Such that A new

A := Matrix([[1, 2, 3, 4, 5, 6, 7, 8, 9, 10], [11, 12, 13, 14, 15, 16, 17, 18, 19, 20], [21, 22, 23, 24, 25, 26, 27, 28, 29, 30], [31, 32, 33, 34, 35, 36, 37, 38, 39, 40], [41, 42, 43, 44, 45, 46, 47, 48, 49, 50]])

Anew = Matrix([[2, 13, 22, 11], [4, 15, 24, 13], [6, 17, 26, 15], [8, 19, 28, 17], [13, 24, 33, 22], [15, 26, 35, 24], [17, 28, 37, 26], [19, 30, 39, 28], [24, 35, 44, 33], [26, 37, 46, 35], [28, 39, 48, 37]])

Many thanks

all
I need your help  to give an answer to  this question
I would like to construct a matrix with condtion that comes in picture
How can i do this with maple????
my matrix is n+1*n+1

Hey,

    I'm doing a little experimenting on Maple and I want to display 3 Matrixes side by side with text explaining what is what. I have a for cycle in which 5 sets of 3 matrixes are made. And my goal is to display each of the 5 sets.
How would I go about doing that? I've tried the following:

display(Array(print(cat("Matriz A", k, AA[k])), print(cat("Matriz B", k, BB[k])), print(cat("Matriz D", k, DD[k]))))

But with this I end up getting this instead of what I want:

http://i.imgur.com/p087Upr.png

Any ideas are welcome, thanks in advance.

Rafael.

Hello,

I have a optimization question in the following picture.

 

Question: find matrix T(t). 

 

I writed a maple code. Could you view it ? You think that it is right?

The code file I writed: maple_code_of_theory.mw

 It is really very important for me. Can you help me?

Thank you. 

 

I've read the spec online for LinearSolve but it's not clear on the function of inplace on nonsquare matrices. For example, consider the following:

A:=<0;1>;
B:=<0:2>;
LinearSolve(A,B,inplace=true)

This last line outputs <2;0>, which is also the value stored in B after the operation, whereas [2] would be the desired result. In the case of A being a row vector an error is encountered due to lack of storage. Does what happened above generalise for any matrix with more rows than columns: storing the result in B, but adding zeroes to the bottom unused parts of B, due to B being larger than the solution?

Also, does anyone have any advice on an efficient method for solving A.x=b, in the case where b is a vector, and A is a large but tall (varying size, but often 5x as many rows as columns, e.g. 10000x2000) integer matrix, where most of the entries in any particular column are zero (more than 90%)? I've found the option method='modular' helps quite a lot, but not enough, any ideas for quick fixes?

I'm sorry if this sounds like a noob question. I am trying to make a matrix from a table, something like Gauss-Jordan Elimination tutor.

For example

maplet1 := Maplet([BoxCell(Table([A, B], [[1, 2], [3, 4]]), 'as_needed'), Button("OK", Shutdown())]);

How do I turn it to 2x2 matrix?Any help appreciated

restart; with(LinearAlgebra); with(Student[LinearAlgebra]); 
Z := Matrix([[3, 1, 5, 4, 5], [0, 0, 0, 0, 0], [28, 6, 4, 5, 9], [98, 5, 82, 2, 4], [24, 55, 23, 22, 90]]); 
B := Matrix([[0], [0], [0], [0], [0]]); 
A := <Z|B>:
if Row(A, 2) = ZeroVector[row](6) then A; end if;

I used the code above but it didn't work...any help appreciated

I have four matrix equations

P1, P2, P3 are known 4x4 matrix.

A1 A2 A3 A4 are known 1x4 matrix.

x1 x2 x3 x4 are 1x1 known matrix.

U is 4x4 unknown matrix.

These equations are 

(A1T*U*P1*A1) +( (P2*A1)T*U*P1*A1) + ( (P3*A1)T*U*A1) + ( ( P3*A 2)T*U*P1*A1) + x1 =0;

(A2T*U*P1*A2) +( (P2*A2)T*U*P1*A2) + ( (P3*A2)T*U*A2) + ( ( P3*A2 )T*U*P1*A2) + x2 =0;

(A3T*U*P1*A3) +( (P2*A3)T*U*P1*A3) + ( (P3*A3)T*U*A3) + ( ( P3*A3 )T*U*P1*A3) + x3 =0;

(A4T*U*P1*A4) +( (P2*A4)T*U*P1*A4) + ( (P3*A4)T*U*A4) + ( ( P3*A4 )T*U*P1*A4) + x4 =0;

How can i find 4x4 matrix U by using these above four equations??

Thank you

First Question: How to define nx1 matrix Y:=(y1,y2,...,yn) ? (n is a Natural number while it is ungiven)

Second Question: How to derivative of matrix Y with respect to nx1 matrix X:=(x1,x2,...,xn) ?

 


My efforts for the first question:  (I know to define 6x1 matrix etc. , but I dont know to define nx1 matrix

restart: Matrix(1..6,1,symbol=y) 

 

My efforts for the second question:

restart; with(VectorCalculus);
Matrix([x^2, x*y, x*z]);
Jacobian([x^2, x*y, x*z], [x, y, z]);


Can you help me? 

I have a vector x of this type:

x :=Vector[column]([A__11*u__1+A__12*u__2+...+A__1m*u__m,

A__21*u__1+A__22*u__2+...+A__2m*u__m,

...,

A__n1*u__1+A__n2*u__2+...+A__nm*u__m]);

If I define u:=Vector[column]([u__1,u__2,...,u__m]), then it is clear that the equation has the form x=A*u.

I want to extract the matrix A, for the given vectors x and u.

IMPORTANT: I know I could create a loop (i=1 to m) and set u__i=1 and all other u__j=0 (for all j not equal i) and then reconstruct each column by this method, but it seems to be a overkill for such an easy problem.

I would be glad, if someone could show me a method how one can achive this in maple.

For exaqmple, the quadratic equation w^2 + uw + v = 0 corresponds to the deter minant


| -u  1  1  |

| v    0  1  |  = 0

|w^2 w w-1|

Is there any way to find a determinant corresponding to an equation, as above?

This is an issue in the preparation of a nomograph for the initial equation.  

It is generally solved by trial and error.

h1_y_h2.mw
 

(-9.481411*10^(-6)*(T__1(t)+T__1s(t))^2+2.1356735*10^(-3)*(T__1(t)+T__1s(t))+.5599920949)*(.825+.387*(((-(9.8*.11^3*4190)*(4.216485*10^(-2)-7.097451*10^(-3)*(T__1(t)+T__1s(t))+2.63217825*10^(-5)*(T__1(t)+T__1s(t))^2-4.9518879*10^(-8)*(T__1(t)+T__1s(t))^3)/(999.9399+2.1082425*10^(-2)*(T__1(t)+T__1s(t))-1.77436275*10^(-3)*(T__1(t)+T__1s(t))^2+.438696375*10^(-5)*(T__1(t)+T__1s(t))^3-.6189861563*10^(-8)*(T__1(t)+T__1s(t))^4))*((999.9399+2.1082425*10^(-2)*(T__1(t)+T__1s(t))-1.77436275*10^(-3)*(T__1(t)+T__1s(t))^2+.438696375*10^(-5)*(T__1(t)+T__1s(t))^3-.6189861563*10^(-8)*(T__1(t)+T__1s(t))^4)^2))*(T__1(t)-T__1s(t))/((0.178910466924394e-2-(0.593656020810955e-4*(1/2))*(T__1(t)+T__1s(t))+(0.130419399687942e-5*(1/4))*(T__1(t)+T__1s(t))^2-(1.79236416162215*(1/8))*10^(-8)*(T__1(t)+T__1s(t))^3+(1.33479173942873*(1/16))*10^(-10)*(T__1(t)+T__1s(t))^4-(4.03880841196434*(1/32))*10^(-13)*(T__1(t)+T__1s(t))^5)*(-9.481411*10^(-6)*(T__1(t)+T__1s(t))^2+2.1356735*10^(-3)*(T__1(t)+T__1s(t))+.5599920949)))^(1/6)/(1+((.492*(-9.481411*10^(-6)*(T__1(t)+T__1s(t))^2+2.1356735*10^(-3)*(T__1(t)+T__1s(t))+.5599920949))/(4190*(0.178910466924394e-2-(0.593656020810955e-4*(1/2))*(T__1(t)+T__1s(t))+(0.130419399687942e-5*(1/4))*(T__1(t)+T__1s(t))^2-(1.79236416162215*(1/8))*10^(-8)*(T__1(t)+T__1s(t))^3+(1.33479173942873*(1/16))*10^(-10)*(T__1(t)+T__1s(t))^4-(4.03880841196434*(1/32))*10^(-13)*(T__1(t)+T__1s(t))^5)))^(9/16))^(8/27))^2/(.11)

subs({T__1(t) = T__1, T__1s(t) = T__1s}, (-9.481411*10^(-6)*(T__1(t)+T__1s(t))^2+2.1356735*10^(-3)*(T__1(t)+T__1s(t))+.5599920949)*(.825+.387*(((-(9.8*.11^3*4190)*(4.216485*10^(-2)-7.097451*10^(-3)*(T__1(t)+T__1s(t))+2.63217825*10^(-5)*(T__1(t)+T__1s(t))^2-4.9518879*10^(-8)*(T__1(t)+T__1s(t))^3)/(999.9399+2.1082425*10^(-2)*(T__1(t)+T__1s(t))-1.77436275*10^(-3)*(T__1(t)+T__1s(t))^2+.438696375*10^(-5)*(T__1(t)+T__1s(t))^3-.6189861563*10^(-8)*(T__1(t)+T__1s(t))^4))*((999.9399+2.1082425*10^(-2)*(T__1(t)+T__1s(t))-1.77436275*10^(-3)*(T__1(t)+T__1s(t))^2+.438696375*10^(-5)*(T__1(t)+T__1s(t))^3-.6189861563*10^(-8)*(T__1(t)+T__1s(t))^4)^2))*(T__1(t)-T__1s(t))/((0.178910466924394e-2-(0.593656020810955e-4*(1/2))*(T__1(t)+T__1s(t))+(0.130419399687942e-5*(1/4))*(T__1(t)+T__1s(t))^2-(1.79236416162215*(1/8))*10^(-8)*(T__1(t)+T__1s(t))^3+(1.33479173942873*(1/16))*10^(-10)*(T__1(t)+T__1s(t))^4-(4.03880841196434*(1/32))*10^(-13)*(T__1(t)+T__1s(t))^5)*(-9.481411*10^(-6)*(T__1(t)+T__1s(t))^2+2.1356735*10^(-3)*(T__1(t)+T__1s(t))+.5599920949)))^(1/6)/(1+((.492*(-9.481411*10^(-6)*(T__1(t)+T__1s(t))^2+2.1356735*10^(-3)*(T__1(t)+T__1s(t))+.5599920949))/(4190*(0.178910466924394e-2-(0.593656020810955e-4*(1/2))*(T__1(t)+T__1s(t))+(0.130419399687942e-5*(1/4))*(T__1(t)+T__1s(t))^2-(1.79236416162215*(1/8))*10^(-8)*(T__1(t)+T__1s(t))^3+(1.33479173942873*(1/16))*10^(-10)*(T__1(t)+T__1s(t))^4-(4.03880841196434*(1/32))*10^(-13)*(T__1(t)+T__1s(t))^5)))^(9/16))^(8/27))^2/(.11))

9.090909091*(-0.9481411000e-5*(T__1+T__1s)^2+0.2135673500e-2*T__1+0.2135673500e-2*T__1s+.5599920949)*(.825+.387*(-54.6535220*(0.4216485000e-1-0.7097451000e-2*T__1-0.7097451000e-2*T__1s+0.2632178250e-4*(T__1+T__1s)^2-0.4951887900e-7*(T__1+T__1s)^3)*(999.9399+0.2108242500e-1*T__1+0.2108242500e-1*T__1s-0.1774362750e-2*(T__1+T__1s)^2+0.4386963750e-5*(T__1+T__1s)^3-0.6189861563e-8*(T__1+T__1s)^4)*(T__1-T__1s)/((0.178910466924394e-2-0.2968280104e-4*T__1-0.2968280104e-4*T__1s+0.3260484992e-6*(T__1+T__1s)^2-0.2240455202e-8*(T__1+T__1s)^3+0.8342448369e-11*(T__1+T__1s)^4-0.1262127629e-13*(T__1+T__1s)^5)*(-0.9481411000e-5*(T__1+T__1s)^2+0.2135673500e-2*T__1+0.2135673500e-2*T__1s+.5599920949)))^(1/6)/(1+.6710121288*((-0.9481411000e-5*(T__1+T__1s)^2+0.2135673500e-2*T__1+0.2135673500e-2*T__1s+.5599920949)/(7.496348563-.1243709364*T__1-.1243709364*T__1s+0.1366143212e-2*(T__1+T__1s)^2-0.9387507296e-5*(T__1+T__1s)^3+0.3495485867e-7*(T__1+T__1s)^4-0.5288314766e-10*(T__1+T__1s)^5))^(9/16))^(8/27))^2

(1)

h__1 := proc (T__1, T__1s) options operator, arrow; (-0.9481411000e-5*(T__1+T__1s)^2+0.2135673500e-2*T__1+0.2135673500e-2*T__1s+.5599920949)*(.825+.387*((0.4216485000e-1-0.7097451000e-2*T__1-0.7097451000e-2*T__1s+0.2632178250e-4*(T__1+T__1s)^2-0.4951887900e-7*(T__1+T__1s)^3)*(999.9399+0.2108242500e-1*T__1+0.2108242500e-1*T__1s-0.1774362750e-2*(T__1+T__1s)^2+0.4386963750e-5*(T__1+T__1s)^3-0.6189861563e-8*(T__1+T__1s)^4)*(T__1-T__1s)*(-54.6535220)/((0.178910466924394e-2-0.2968280104e-4*T__1-0.2968280104e-4*T__1s+0.3260484992e-6*(T__1+T__1s)^2-0.2240455202e-8*(T__1+T__1s)^3+0.8342448369e-11*(T__1+T__1s)^4-0.1262127629e-13*(T__1+T__1s)^5)*(-0.9481411000e-5*(T__1+T__1s)^2+0.2135673500e-2*T__1+0.2135673500e-2*T__1s+.5599920949)))^(1/6)/(1+.6710121288*((-0.9481411000e-5*(T__1+T__1s)^2+0.2135673500e-2*T__1+0.2135673500e-2*T__1s+.5599920949)/(7.496348563-.1243709364*T__1-.1243709364*T__1s+0.1366143212e-2*(T__1+T__1s)^2-0.9387507296e-5*(T__1+T__1s)^3+0.3495485867e-7*(T__1+T__1s)^4-0.5288314766e-10*(T__1+T__1s)^5))^(9/16))^(8/27))^2*9.090909091 end proc

proc (T__1, T__1s) options operator, arrow; (-0.9481411000e-5*((T__1+T__1s)^2)+0.2135673500e-2*T__1+0.2135673500e-2*T__1s+.5599920949)*(.825+.387*(((0.4216485000e-1-0.7097451000e-2*T__1-0.7097451000e-2*T__1s+0.2632178250e-4*((T__1+T__1s)^2)-0.4951887900e-7*((T__1+T__1s)^3))*(999.9399+0.2108242500e-1*T__1+0.2108242500e-1*T__1s-0.1774362750e-2*((T__1+T__1s)^2)+0.4386963750e-5*((T__1+T__1s)^3)-0.6189861563e-8*((T__1+T__1s)^4))*(T__1-T__1s)*(-1)*54.6535220/(((0.178910466924394e-2-0.2968280104e-4*T__1-0.2968280104e-4*T__1s+0.3260484992e-6*((T__1+T__1s)^2)-0.2240455202e-8*((T__1+T__1s)^3)+0.8342448369e-11*((T__1+T__1s)^4)-0.1262127629e-13*((T__1+T__1s)^5))*(-0.9481411000e-5*((T__1+T__1s)^2)+0.2135673500e-2*T__1+0.2135673500e-2*T__1s+.5599920949))))^(1/6))/(((1+.6710121288*(((-0.9481411000e-5*((T__1+T__1s)^2)+0.2135673500e-2*T__1+0.2135673500e-2*T__1s+.5599920949)/(7.496348563-.1243709364*T__1-.1243709364*T__1s+0.1366143212e-2*((T__1+T__1s)^2)-0.9387507296e-5*((T__1+T__1s)^3)+0.3495485867e-7*((T__1+T__1s)^4)-0.5288314766e-10*((T__1+T__1s)^5)))^(9/16)))^(8/27))))^2*9.090909091 end proc

(2)

(-9.481411*10^(-6)*(T__2(t)+T__2s(t))^2+2.1356735*10^(-3)*(T__2(t)+T__2s(t))+.5599920949)*(.825+.387*(((-(9.8*.11^3*4190)*(4.216485*10^(-2)-7.097451*10^(-3)*(T__2(t)+T__2s(t))+2.63217825*10^(-5)*(T__2(t)+T__2s(t))^2-4.9518879*10^(-8)*(T__2(t)+T__2s(t))^3)/(999.9399+2.1082425*10^(-2)*(T__2(t)+T__2s(t))-1.77436275*10^(-3)*(T__2(t)+T__2s(t))^2+.438696375*10^(-5)*(T__2(t)+T__2s(t))^3-.6189861563*10^(-8)*(T__2(t)+T__2s(t))^4))*((999.9399+2.1082425*10^(-2)*(T__2(t)+T__2s(t))-1.77436275*10^(-3)*(T__2(t)+T__2s(t))^2+.438696375*10^(-5)*(T__2(t)+T__2s(t))^3-.6189861563*10^(-8)*(T__2(t)+T__2s(t))^4)^2))*(T__2s(t)-T__2(t))/((0.178910466924394e-2-(0.593656020810955e-4*(1/2))*(T__2(t)+T__2s(t))+(0.130419399687942e-5*(1/4))*(T__2(t)+T__2s(t))^2-(1.79236416162215*(1/8))*10^(-8)*(T__2(t)+T__2s(t))^3+(1.33479173942873*(1/16))*10^(-10)*(T__2(t)+T__2s(t))^4-(4.03880841196434*(1/32))*10^(-13)*(T__2(t)+T__2s(t))^5)*(-9.481411*10^(-6)*(T__2(t)+T__2s(t))^2+2.1356735*10^(-3)*(T__2(t)+T__2s(t))+.5599920949)))^(1/6)/(1+((.492*(-9.481411*10^(-6)*(T__2(t)+T__2s(t))^2+2.1356735*10^(-3)*(T__2(t)+T__2s(t))+.5599920949))/(4190*(0.178910466924394e-2-(0.593656020810955e-4*(1/2))*(T__2(t)+T__2s(t))+(0.130419399687942e-5*(1/4))*(T__2(t)+T__2s(t))^2-(1.79236416162215*(1/8))*10^(-8)*(T__2(t)+T__2s(t))^3+(1.33479173942873*(1/16))*10^(-10)*(T__2(t)+T__2s(t))^4-(4.03880841196434*(1/32))*10^(-13)*(T__2(t)+T__2s(t))^5)))^(9/16))^(8/27))^2/(.11)

subs({T__2(t) = T__2, T__2s(t) = T__2s}, (-9.481411*10^(-6)*(T__2(t)+T__2s(t))^2+2.1356735*10^(-3)*(T__2(t)+T__2s(t))+.5599920949)*(.825+.387*(((-(9.8*.11^3*4190)*(4.216485*10^(-2)-7.097451*10^(-3)*(T__2(t)+T__2s(t))+2.63217825*10^(-5)*(T__2(t)+T__2s(t))^2-4.9518879*10^(-8)*(T__2(t)+T__2s(t))^3)/(999.9399+2.1082425*10^(-2)*(T__2(t)+T__2s(t))-1.77436275*10^(-3)*(T__2(t)+T__2s(t))^2+.438696375*10^(-5)*(T__2(t)+T__2s(t))^3-.6189861563*10^(-8)*(T__2(t)+T__2s(t))^4))*((999.9399+2.1082425*10^(-2)*(T__2(t)+T__2s(t))-1.77436275*10^(-3)*(T__2(t)+T__2s(t))^2+.438696375*10^(-5)*(T__2(t)+T__2s(t))^3-.6189861563*10^(-8)*(T__2(t)+T__2s(t))^4)^2))*(T__2s(t)-T__2(t))/((0.178910466924394e-2-(0.593656020810955e-4*(1/2))*(T__2(t)+T__2s(t))+(0.130419399687942e-5*(1/4))*(T__2(t)+T__2s(t))^2-(1.79236416162215*(1/8))*10^(-8)*(T__2(t)+T__2s(t))^3+(1.33479173942873*(1/16))*10^(-10)*(T__2(t)+T__2s(t))^4-(4.03880841196434*(1/32))*10^(-13)*(T__2(t)+T__2s(t))^5)*(-9.481411*10^(-6)*(T__2(t)+T__2s(t))^2+2.1356735*10^(-3)*(T__2(t)+T__2s(t))+.5599920949)))^(1/6)/(1+((.492*(-9.481411*10^(-6)*(T__2(t)+T__2s(t))^2+2.1356735*10^(-3)*(T__2(t)+T__2s(t))+.5599920949))/(4190*(0.178910466924394e-2-(0.593656020810955e-4*(1/2))*(T__2(t)+T__2s(t))+(0.130419399687942e-5*(1/4))*(T__2(t)+T__2s(t))^2-(1.79236416162215*(1/8))*10^(-8)*(T__2(t)+T__2s(t))^3+(1.33479173942873*(1/16))*10^(-10)*(T__2(t)+T__2s(t))^4-(4.03880841196434*(1/32))*10^(-13)*(T__2(t)+T__2s(t))^5)))^(9/16))^(8/27))^2/(.11))

9.090909091*(-0.9481411000e-5*(T__2+T__2s)^2+0.2135673500e-2*T__2+0.2135673500e-2*T__2s+.5599920949)*(.825+.387*(-54.6535220*(0.4216485000e-1-0.7097451000e-2*T__2-0.7097451000e-2*T__2s+0.2632178250e-4*(T__2+T__2s)^2-0.4951887900e-7*(T__2+T__2s)^3)*(999.9399+0.2108242500e-1*T__2+0.2108242500e-1*T__2s-0.1774362750e-2*(T__2+T__2s)^2+0.4386963750e-5*(T__2+T__2s)^3-0.6189861563e-8*(T__2+T__2s)^4)*(T__2s-T__2)/((0.178910466924394e-2-0.2968280104e-4*T__2-0.2968280104e-4*T__2s+0.3260484992e-6*(T__2+T__2s)^2-0.2240455202e-8*(T__2+T__2s)^3+0.8342448369e-11*(T__2+T__2s)^4-0.1262127629e-13*(T__2+T__2s)^5)*(-0.9481411000e-5*(T__2+T__2s)^2+0.2135673500e-2*T__2+0.2135673500e-2*T__2s+.5599920949)))^(1/6)/(1+.6710121288*((-0.9481411000e-5*(T__2+T__2s)^2+0.2135673500e-2*T__2+0.2135673500e-2*T__2s+.5599920949)/(7.496348563-.1243709364*T__2-.1243709364*T__2s+0.1366143212e-2*(T__2+T__2s)^2-0.9387507296e-5*(T__2+T__2s)^3+0.3495485867e-7*(T__2+T__2s)^4-0.5288314766e-10*(T__2+T__2s)^5))^(9/16))^(8/27))^2

(3)

h__2 := proc (T__2, T__2s) options operator, arrow; (-0.9481411000e-5*(T__2+T__2s)^2+0.2135673500e-2*T__2+0.2135673500e-2*T__2s+.5599920949)*(.825+.387*((0.4216485000e-1-0.7097451000e-2*T__2-0.7097451000e-2*T__2s+0.2632178250e-4*(T__2+T__2s)^2-0.4951887900e-7*(T__2+T__2s)^3)*(999.9399+0.2108242500e-1*T__2+0.2108242500e-1*T__2s-0.1774362750e-2*(T__2+T__2s)^2+0.4386963750e-5*(T__2+T__2s)^3-0.6189861563e-8*(T__2+T__2s)^4)*(T__2s-T__2)*(-54.6535220)/((0.178910466924394e-2-0.2968280104e-4*T__2-0.2968280104e-4*T__2s+0.3260484992e-6*(T__2+T__2s)^2-0.2240455202e-8*(T__2+T__2s)^3+0.8342448369e-11*(T__2+T__2s)^4-0.1262127629e-13*(T__2+T__2s)^5)*(-0.9481411000e-5*(T__2+T__2s)^2+0.2135673500e-2*T__2+0.2135673500e-2*T__2s+.5599920949)))^(1/6)/(1+.6710121288*((-0.9481411000e-5*(T__2+T__2s)^2+0.2135673500e-2*T__2+0.2135673500e-2*T__2s+.5599920949)/(7.496348563-.1243709364*T__2-.1243709364*T__2s+0.1366143212e-2*(T__2+T__2s)^2-0.9387507296e-5*(T__2+T__2s)^3+0.3495485867e-7*(T__2+T__2s)^4-0.5288314766e-10*(T__2+T__2s)^5))^(9/16))^(8/27))^2*9.090909091 end proc

proc (T__2, T__2s) options operator, arrow; (-0.9481411000e-5*((T__2+T__2s)^2)+0.2135673500e-2*T__2+0.2135673500e-2*T__2s+.5599920949)*(.825+.387*(((0.4216485000e-1-0.7097451000e-2*T__2-0.7097451000e-2*T__2s+0.2632178250e-4*((T__2+T__2s)^2)-0.4951887900e-7*((T__2+T__2s)^3))*(999.9399+0.2108242500e-1*T__2+0.2108242500e-1*T__2s-0.1774362750e-2*((T__2+T__2s)^2)+0.4386963750e-5*((T__2+T__2s)^3)-0.6189861563e-8*((T__2+T__2s)^4))*(T__2s-T__2)*(-1)*54.6535220/(((0.178910466924394e-2-0.2968280104e-4*T__2-0.2968280104e-4*T__2s+0.3260484992e-6*((T__2+T__2s)^2)-0.2240455202e-8*((T__2+T__2s)^3)+0.8342448369e-11*((T__2+T__2s)^4)-0.1262127629e-13*((T__2+T__2s)^5))*(-0.9481411000e-5*((T__2+T__2s)^2)+0.2135673500e-2*T__2+0.2135673500e-2*T__2s+.5599920949))))^(1/6))/(((1+.6710121288*(((-0.9481411000e-5*((T__2+T__2s)^2)+0.2135673500e-2*T__2+0.2135673500e-2*T__2s+.5599920949)/(7.496348563-.1243709364*T__2-.1243709364*T__2s+0.1366143212e-2*((T__2+T__2s)^2)-0.9387507296e-5*((T__2+T__2s)^3)+0.3495485867e-7*((T__2+T__2s)^4)-0.5288314766e-10*((T__2+T__2s)^5)))^(9/16)))^(8/27))))^2*9.090909091 end proc

(4)

``

``

im trying to build a matrix starting from a function, so i can later use this matrix to get a more simple function using linearfit from the statistics package, like a kind of regression.

i want to get a matrix starting from h__1(T1,T__1s) so it has to be a 3 columns matrix (T__1,T__1s,h__1). so as you can see, i have got the functions h__1 and h__2, but i need to evaluate it at differents values for T__1 and T__1s and building a kind of value-table in matrix form.

for h__1, T__1 must be higher than T__1s, or you could get imaginary values, don't know if that important for building the matrix.

thank you very much for your help.

Download h1_y_h2.mw

 

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