>> mp
Invalid MEX-file '/home/kva/Documents/MATLAB/AdvanpixMCT/mpimpl.mexa64': /home/kva/Documents/MATLAB/AdvanpixMCT/mpimpl.mexa64: undefined symbol:
_Z19mxGetPropertySharedPK11mxArray_tagmPKc.

Error in mp (line 1255)
           if nargin == 0,     this.id = mpimpl(0);             % create mp-entity of default precision

The latest version of AdvanpixMCT 4.4.6.12719 is not compatible with Matlab R2018a (linux version). Please could you fix it?

Hello Pavel.

I noticed some performance issues with the besselh-function.

I used mp.Digits(34), mp.GuardDigits(0) and got the following

value=mp(rand(100,100));
tic
value1=besselh(mp('2'),2,mp('1i').*value);
toc
tic
value2=besselj(mp('2'),mp('1i').*value)-mp('1i')*bessely(mp('2'),mp('1i').*value);
toc
tic
value3=besselk(mp('2'),-value)*mp('2')/(mp('1i')*mp('pi'));
toc
Elapsed time is 3.986968 seconds.
Elapsed time is 1.879375 seconds.
Elapsed time is 0.772351 seconds.

which gives of course the same results for value1, value2 and value3. Any possibilty to enhance the performance of besselh to that of besselk?

Best regrads,

Michael

Will the Multiprecision Computing Toolbox work under WindowsXP x32?

Hello Pavel.

I found another bug in the isreal() function.

If we store real and complex data in the same array, the function isreal() gives always 0, even for entries with 0 imaginary part.

test(1,1)=mp('1i');
test(1,2)=mp('1');
isreal(test(1,1))
isreal(test(1,2))

ans =

  logical

   0

ans =

  logical

   0

This is differnt compared to the standard Matlab behaviour:

test(1,1)=1i;
test(1,2)=1;
isreal(test(1,1))
isreal(test(1,2))

ans =

  logical

   0

ans =

  logical

   1

Best regards,

Michael

Hello Pavel.

There are some problems with contourf plots "contourf(X,Y,Z,v)" and multiprecision data. Setting the different levels with the parameter "v" does not work properly using multi-precision data. Furthermore using caxis(limits) with multiprecision data leads to an error.

Best regards,

Michael

Is there any possibility to use matlab function linprog with mp class?

There appears to be an error in computing the values of Airy functions and their derivatives of purely imaginary argument unless z is exactly 0. For example:

>> z = 1i; [ airy(0, z) airy(1, z) airy(2, z) airy(3, z) ].'

ans =

          0.331493305432141 -     0.317449858968444i
         -0.432492659841807 +    0.0980478562292432i
          0.648858208330395 +     0.344958634768048i
          0.135026646710819 -     0.128837386781255i

>> z = mp('1i'); [ airy(0, z) airy(1, z) airy(2, z) airy(3, z) ].'

ans =

        0    
        0    
        0    
        0  

This bug seems to affect only values of z with exactly zero real part:

>> z = mp('1e-100+1i'); [ airy(0, z) airy(1, z) airy(2, z) airy(3, z) ].'

ans =

         0.3314933054321411889845293326171343 -      0.3174498589684437734776429279092585i    
        -0.4324926598418070993062086217182285 +     0.09804785622924323238379104639440311i    
          0.648858208330394944584847653172865 +      0.3449586347680483702471086086672932i    
         0.1350266467108189726991698591958052 -       0.128837386781254879039817640967921i

Mathematica, for comparison

In[9]:= N[ { AiryAi[I], D[AiryAi[x], x] /. x -> I,  AiryBi[I],  D[AiryBi[x], x] /. x -> I }, 34]

Out[9]= {0.3314933054321411889845293326171343 -   0.3174498589684437734776429279092585 I,
-0.4324926598418070993062086217182286 +   0.0980478562292432323837910463944031 I,
 0.6488582083303949445848476531728650 +   0.3449586347680483702471086086672933 I,
 0.1350266467108189726991698591958051 -   0.1288373867812548790398176409679211 I}

There are obviously new releases for Windows during last few days, but not the same releases (relevant to same bug)  for Linux or OSX.

What is exactly the new releases policy? When will be available latest releases for Linux?

The following subscript assignment works fine in MATLAB, but not with the MP-toolbox. Obviously workaround exists, but this type of assignments are truly convenient.

A = zeros(3,3,3);
B = ones(3,1);
A(1,1,:) = B;

A = zeros(3,3,3,'mp');
B = ones(3,1,'mp');
A(1,1,:) = B;

Hi I am trying to compare latest versions MCT exp() speed on two platforms (windows and linux). 

Windows:

Windows 7 Pro 64bit, Matlab R2017b, MCT 4.4.4 Build 12668

Linux:

Ubuntu 16.04.3 64bit, Matlab R2017b, MCT 4.4.4 Build 12666

I found very strange results:

rng(1), n = 1000;
A = randn(n); A_mp = mp(A,34);

t = clock; X = exp(A);     t_dp = etime(clock, t)
t = clock; X = exp(A_mp);  t_mp = etime(clock, t)

Windows:

t_dp =

    0.0260

t_mp =

    0.0550

Linux:

t_dp =

    0.0065

t_mp =

    0.2184

Windows and Linux PC has different HW (Linux PC is significantly faster ... see double precision timing), but on linux is quadruple precision computing significantly slower.

Is there some bug in Linux release?