FFTW in Fortran result contains only zeros - fortran

I have been trying to write a simple program to perform an fft on a 1D input array using fftw3. Here I am using a seismogram as an input. The output array is, however, coming out to contain only zeroes.
I know that the input is correct as I have tried doing the fft of the same input file in MATLAB as well, which gives correct results. There is no compilation error. I am using f95 to compile this, however, gfortran was also giving pretty much the same results. Here is the code that I wrote:-
program fft
use functions
implicit none
include 'fftw3.f90'
integer nl,row,col
double precision, allocatable :: data(:,:),time(:),amplitude(:)
double complex, allocatable :: out(:)
integer*8 plan
open(1,file='test-seismogram.xy')
nl=nlines(1,'test-seismogram.xy')
allocate(data(nl,2))
allocate(time(nl))
allocate(amplitude(nl))
allocate(out(nl/2+1))
do row = 1,nl
read(1,*,end=101) data(row,1),data(row,2)
amplitude(row)=data(row,2)
end do
101 close(1)
call dfftw_plan_dft_r2c_1d(plan,nl,amplitude,out,FFTW_R2HC,FFTW_PATIENT)
call dfftw_execute_dft_r2c(plan, amplitude, out)
call dfftw_destroy_plan(plan)
do row=1,(nl/2+1)
print *,out(row)
end do
deallocate(data)
deallocate(amplitude)
deallocate(time)
deallocate(out)
end program fft
The nlines() function is a function which is used to calculate the number of lines in a file, and it works correctly. It is defined in the module called functions.
This program pretty much tries to follow the example at http://www.fftw.org/fftw3_doc/Fortran-Examples.html
There might just be a very simple logical error that I am making, but I am seriously unable to figure out what is going wrong here. Any pointers would be very helpful.
This is pretty much how the whole output looks like:-
.
.
.
(0.0000000000000000,0.0000000000000000)
(0.0000000000000000,0.0000000000000000)
(0.0000000000000000,0.0000000000000000)
(0.0000000000000000,0.0000000000000000)
(0.0000000000000000,0.0000000000000000)
.
.
.
My doubt is directly regarding fftw, since there is a tag for fftw on SO, so I hope this question is not off topic

As explained in the comments first by #roygvib and #Ross, the plan subroutines overwrite the input arrays because they try the transform many times with different parameters. I will add some practical use considerations.
You claim you do care about performance. Then there are two possibilities:
You do the transform only once as you show in your code. Then there is no point to use FFTW_MEASURE. The planning subroutine is many times slower than actual plan execute subroutine. Use FFTW_ESTIMATE and it will be much faster.
FFTW_MEASURE tells FFTW to find an optimized plan by actually
computing several FFTs and measuring their execution time. Depending
on your machine, this can take some time (often a few seconds).
FFTW_MEASURE is the default planning option.
FFTW_ESTIMATE specifies that, instead of actual measurements of
different algorithms, a simple heuristic is used to pick a (probably
sub-optimal) plan quickly. With this flag, the input/output arrays are
not overwritten during planning.
http://www.fftw.org/fftw3_doc/Planner-Flags.html
You do the same transform many times for different data. Then you must do the planning only once before the first transform and than re-use the plan. Just make the plan first and only then you fill the array with the first input data. Making the plan before every transport would make the program extremely slow.

Related

Gestion of memory in the modular structure of a Fortran 95 program with heavy computations and variables

I am currently "optimizing" a scientific modelling program developed in Fortran 95. This program is basically making heavy computations in 3D to solve some equations, in addition numerous variable have to be saved and used ~ 50 tables with sizes likes (50; 50; 10000), I even have some 5D tables with sizes like (6;6;15;15;10000) to save in order to reduce the computation time.
I developed a perfectly working version of this code using a python3 interface to control my runs. Basically python is calling a fortran module containing my code to obtain all the results from my modelling. The problem with this method is that I cannot parallelize my code in some time consuming regions. Moreover, I would benefit from the computational time advantage of Fortran for a post treatment of the models that is now partially done in python due to interface.
In the first part of my optimization campaign for this code I want to add a control of the runs with Fortran. A program would call the module containing my code to obtain all the necessary and heavy variables. The Python interface would still be presented, the switch between the Fortran and python control run being done in the compilation in the Makefile directly, this Makefile is already done, everything is compiling well and the python interface is still perfectly working.
My troubles are concerning the Fortran control program and its gestion of the allocated memory I assume. As the size of my tables are not known in advance and requires to open some files I have to declare all my variable as ALLOCATABLE. I then allocate them with the correct sizes before calling my module containing my code. When calling my code errors related to memory problems are appearing, with the error message "Program received signal SIGSEV: Segmentation fault - invalid memory reference". This error appears when I'm setting a table to 0d0, if I'm reducing the size/precision of my modelling the program can proceed a bit further before crashing hence the memory related problem. I think that I'm doing something not correct in the utilisation of the variables between my control and my modelling module. Maybe some variables are stored in the wrong memory space, I precise that I'm using gfortran on ubuntu 22.04.1.
I have different possibilities to try to solve this issue using derived types and pointers or simply by breaking my modelling module. Before going into these heavy structural modifications I wanted to know if someone has experience an equivalent problem and what were the solutions.
Here is a schema of the structure of my code:
Run program:
program run_model
use coordinates
use file
use mathematical
use modelling_module
implicit none
integer :: n_x, n_y, n_z
real(8),dimension(:), ALLOCATABLE:: x,y,z
+ all other output variables in 3D
.
.
.
Some operations and file opening
ALLOCATE(x(n_x),y(n_y),z(n_z))
+ all other variables
CALL modelling(n_x, n_y, n_z, output variables)
end program run_model
Modelling module in a separated file:
module modelling_module
use coordinates
use file
use mathematical
implicit none
private
public :: modelling
contains
subroutine modelling(n_x, n_y, n_z, output variables)
integer, intent(in):: n_x, n_y, n_z,
real(8),dimension(n_x), intent(out):: x
real(8),dimension(n_y), intent(out):: y
real(8),dimension(n_z), intent(out):: z
+ all output variables
Computation of the model
.
.
.
end subroutine modelling
end module modelling_module
Thank you in advance for your answers !

Univac Math pack subroutines in old-school FORTRAN (pre-77)

I have been looking at an engineering paper here which describes an old FORTRAN code for solving pipe flow equations (it's dated 1974, before FORTRAN was standardised as Fortran 77). On page 42 of this document the old code calls the following subroutine:
C SYSTEM SUBROUTINE FROM UNIVAC MATH-PACK TO
C SOLVE LINEAR SYSTEM OF EQ.
CALL GJR(A,51,50,NP,NPP,$98,JC,V)
It's a bit of a long shot, but do any veterans or ancient code buffs recall this system subroutine and it's input arguments? I'm having trouble finding any information about it.
If I can adapt the old code my current application I may rewrite this in C++ or VBA, and will be looking for an equivalent function in these languages.
I'll add to this answer if I find anything more detailed, but I have a place to start looking for the arguments to GJR.
This function is part of the Sperry UNIVAC MATH-PACK library - a full list of functions in the library can be found in http://www.dtic.mil/dtic/tr/fulltext/u2/a170611.pdf GJR is described as "determinant; inverse; solution of simultaneous equations". Marginally helpful.
A better description comes from http://nvlpubs.nist.gov/nistpubs/jres/74B/jresv74Bn4p251_A1b.pdf
A FORTRAN subroutine, one of the Univac 1108 Math Pack programs,
available on the library tapes at the University of Maryland computing
center. It solves simultaneous equations, computes a determinant, or
inverts a matrix or any combination of the three above by using a
Gauss-Jordan elimination technique with column pivoting.
This is slightly more useful, but what we really want is "MATH-PACK, Programmer Reference", UP-7542 Rev. 1 from Sperry-UNIVAC (Unisys) I find a lot of references to this document but no full-text PDF of the document itself.
I'd take a look at the arguments in the function call, how they are set up and how the results are used, then look for equivalent routines in LAPACK or BLAS. See http://www.netlib.org/lapack/
I have a few books on piping networks including "Analysis of Flow in Pipe Networks" by Jeppson (same author as in the original PDF hosted by USU) https://books.google.com/books/about/Analysis_of_flow_in_pipe_networks.html?id=peZSAAAAMAAJ - I'll see if I can dig that up. The book may have a more portable matrix solver than the proprietary Sperry-UNIVAC library.
Update:
From p. 41 of http://ngds.egi.utah.edu/files/GL04099/GL04099_1.pdf I found documentation for the CGJR function, the complex version of GJR from the same library. It is likely the only difference in the arguments is variable type (COMPLEX instead of REAL):
CGJR is a subroutine which solves simultaneous equations, computes a determinant, inverts a matrix, or does any combination of these three operations, by using a Gauss-Jordan elimination technique with column pivoting.
The procedure for using CGJR is as follows:
Calling statement: CALL CGJR(A,NC,NR,N,MC,$K,JC,V)
where
A is the matrix whose inverse or determinant is to be determined. If simultaneous equations are solved, the last MC-N columns of the matrix are the constant vectors of the equations to be solved. On output, if the inverse is computed, it is stored in the first N columns of A. If simultaneous equations are solved, the last MC-N columns contain the solution vectors. A is a complex array.
NC is an integer representing the maximum number of columns of the array A.
NR is an integer representing the maximum number of rows of the array A.
N is an integer representing the number of rows of the array A to be operated on.
MC is the number of columns of the array A, representing the coefficient matrix if simultaneous equations are being solved; otherwise it is a dummy variable.
K is a statement number in the calling program to which control is returned if an overflow or singularity is detected.
1) If an overflow is detected, JC(1) is set to the negative of the last correctly completed row of the reduction and control is then returned to statement number K in the calling program.
2) If a singularity is detected, JC(1)is set to the number of the last correctly completed row, and V is set to (0.,0.) if the determinant was to be computed. Control is then returned to statement number K in the calling program.
JC is a one dimensional permutation array of N elements which is used for permuting the rows and columns of A if an inverse is being computed .. If an inverse is not computed, this array must have at least one cell for the error return identification. On output, JC(1) is N if control is returned normally.
V is a complex variable. On input REAL(V) is the option indicator, set as follows:
invert matrix
compute determinant
do 1. and 2.
solve system of equations
do 1. and 4.
do 2. and 4.
do 1., 2. and 4.
Notes on usage of row dimension arguments N and NR:
The arguments N and NR refer to the row dimensions of the A matrix.
N gives the number of rows operated on by the subroutine, while NR
refers to the total number of rows in the matrix as dimensioned by the
calling program. NR is used only in the dimension statement of the
subroutine. Through proper use of these parameters, the user may specify that only a submatrix, instead of the entire matrix, be operated on by the subroutine.
In your application (pipe flow), look at how matrix A and vector V are populated before the call to GJR and how they are used after the call.
You may be able to replace the call to GJR with a call to LAPACK's SGESV or DGESV without much difficulty.
Aside: The Fortran community really needs a drop-in 'Rosetta library' that wraps LAPACK, etc. for replacing legacy/proprietary IBM, UNIVAC, and Numerical Recipes math functions. The perfect case would be that maintainers would replace legacy functions with de facto standard math functions but in the real world, many of these older programs are un(der)maintained and there simply isn't the will (or, as in this case, the ability) to update them.
Update 2:
I started work on a compatibility library for the Sperry MATH-PACK and STAT-PACK routines as well as a few other legacy libraries, posted at https://bitbucket.org/apthorpe/alfc
Further, I located my copy of Jeppson's Analysis of Flow in Pipe Networks which is a slightly more legible version of the PDF of Steady Flow Analysis of Pipe Networks: An Instructional Manual and modernized the codes listed in the text. I have posted those at https://bitbucket.org/apthorpe/jeppson_pipeflow
Note that I found a number of errors in both the code listings and in the example problems given for many of the codes. If you're trying to learn how to write a pipe flow solver based on Jeppson's paper or text, I'd strongly suggest reviewing my updated codes and test cases because they will save you hours of effort trying to understand why the code doesn't work and why you can't replicate the example cases. This took a fair amount of forensic computing to sort out.
Update 3:
The source to CGJR and DGJR can be found in http://www.dtic.mil/dtic/tr/fulltext/u2/a110089.pdf. DGJR is the closest to what you want, though it references more routines that aren't available (proprietary UNIVAC error-handling routines). It should be easy to convert `DGJR' to single precision and skip the proprietary calls. Otherwise, use the compatibility library mentioned above.

Evaluate a function with different KIND

Consider a function that adds two number (e.g. integer, Real). I have to write the same function with the same code many times but with different precision and then create an interface.
Can somebody give me an example how to do the same with Fortran select type.
No... But it is possible in a module
All the math for scalars and doubles already does exactly what you want, so the procedures would be mostly for functions or subroutines that are doing significantly more bespoke work than a simple add or multiply.
Do you have any starting example?
Is this for a course you are taking?
If it is for a course then search for "module procedure interface".

fortran77 to fortran90 differences in output

I have downloaded the following fortran program dragon.f at http://www.iamg.org/documents/oldftp/VOL32/v32-10-11.zip
I need to do a minor modification to the program which requires the program to be translated to fortran90 (see below to confirm if this is truly needed).
I have managed to do this (translation only) by three different methods:
replacing comment line indicators (c for !) and line continuation
indicators (* in column 6 for & at the end of last line)
using convert.f90 (see https ://wwwasdoc.web.cern.ch/wwwasdoc/WWW/f90/convert.f90)
using f2f.pl (see https :// bitbucket.org/lemonlab/f2f/downloads)
Both 1) and 3) worked (i.e. managed to compile program) while 2) didn't work straight away.
However, after testing the program I found that the results are different.
With the fortran77 program, I get the "expected" results for the example provided with the program (the program comes with an example data "grdata.txt", and its example output "flm.txt" and "check.txt"). However, after running the translated (fortran90) program the results I get are different.
I suspect there are some issues with the way some variables are declared.
Can you give me recommendations in how to properly translate this program so I get the exact same results?
The reason I need to do it in fortran90 is because I need to input the parameters via a text file instead of modifying the program. This shouldnt be an issue for most of the parameters involved, except for the declaration of the last one, in which the size is determined from parameters that the program does not know a priori (see below):
implicit double precision(a-h,o-z)
parameter(lmax=90,imax=45,jmax=30)
parameter(dcta=4.0d0,dfai=4.0d0)
parameter(thetaa=0.d0,thetab=180.d0,phaia=0.d0,phaib=120.d0)
dimension f(0:imax,0:jmax),coe(imax,jmax,4),coew(4),fw(4)
So for example, I will read lmax, imax, jmax, dcta, dfai, thetaa, thetab, phaia, and phaib and the program needs to declare f and coe but as far as I read after googling this issue, they cannot be declared with an unknown size in fortran77.
Edit: This was my attempt to do this modification:
character fname1*100
call getarg(1,fname1)
open(10,file=fname1)
read(10,*)lmax,imax,jmax,dcta,dfai,thetaa,thetab,phaia,phaib
close(10)
So the program will read these constants from a file (e.g. params.txt), where the name of the file is supplied as an argument when invoking the program. The problem when I do this is that I do not know how to modify the line
dimension f(0:imax,0:jmax)...
in order to declare this array when the values imax and jmax are not known when compiling the program (they depend on the size of the data that the user will use).
As has been pointed out in the comments above, parameters cannot be read from file since they are set at compile time. Read them in as integer, declare the arrays as allocatable, and then allocate.
integer imax,jmax
real(8), allocatable :: f(:,:),coe(:,:,:)
read(10,*) imax,jmax
allocate(f(0:imax,0:jmax),coe(imax,jmax,4))
I found out that the differences in the results were attributed to using different compilers.
PS I ended up adding a lot more code than I intended at the beginning to allow reading data from netcdf files. This program in particular is really helpful for spherical harmonic expansion. [tag:spherical harmonics]

gsl, pygsl, lmsder, memory leak, inconsistent output

I am using the multifit_nlin module from pygsl for nonlinear least squares fitting. pygsl is a python binding of the c numerical library gsl. The problem that I am experiencing does not seem to be related to pygsl or gsl, but it appears in this context only.
I am fitting parameters of a function to some data. To use pygsl for parameters fitting I need to define the function and its jacobian. Then multifit_nlin's fitter lmsder calls these two function when needed in the fitting process. When, I make a call to the jacobian, it produces a matrix of numbers. I can output this matrix to screen and I see that the number are correct. Next, I define a lmsder class and initialize it with the lmsder.set command. I output the jacobian matrix with the lmsder.getJ() command to screen and I see the same numbers as before. Of course, this is not what I want to do with my code but for illustrative and debugging purposes only.
The agreement between the outputs of jacobian and lmsder.getJ() are what you would expect since lmsder.getJ() accesses the jacobian matrix in memory which was produced by the jacobian function. However, if I insert a line a code, say print 'bob" (or anything else), as in the following
system = gsl_multifit_function_fdf(...) # jacobian is passed here
solver = lmsder(...) # system is passed here
solver.set(...) # first call to jacobian is in here
print "bob"
print solver.getJ()
where ... means the appropriate arguments. Then the print solver.getJ() prints a matrix which is a transpose of the jacobian matrix with lower rows filled with random content. So again, this only happens when there are extra lines of code between the set() and getJ() calls.
If I execute my code normally, i.e. the entire fitting process that I have, the code works error free. If the jacobian matrix was indeed what the getJ() command shows then, there would pretty of places where an exception could be raised. So, I know for certain that my code works and also because the values that I get for the parameters are reasonable.
I have also tracked the chain of calls that pygsl does all the way to the gsl's c library. There is nothing that causes this problem. Also, gsl has been round for ages and something as simple as displaying a matrix would have been fixed ages ago.
Any suggestions to what might be the cause of this problem? Garbage collector, incorrect ordering of import statements, multicore? What tools can I use to check for memory leaks, garbage collection process?
Thanks,
Alexander
There is a patch that deals with pygsl memory leak problems for fdf solvers.
http://pygsl.sf.net/pygsl-0.9.6.tar.gz