ivan-pi

subroutine f(mu, Sigma, H, INFO, R, Sigmavar_2, data, muvar_2, k, n)
implicit none

integer, intent(in) :: k
integer, intent(in) :: n
real*8, intent(in) :: Sigma(n, n)        !  Sigma
real*8, intent(in) :: H(k, n)            !  H
real*8, intent(in) :: mu(n)              !  mu
real*8, intent(in) :: R(k, k)            !  R, H*Sigma*H' + R
real*8, intent(in) :: data(k)            !  (H*Sigma*H' + R)^-1*((-1)*data + H*mu), data, (-1)*   data + H*mu

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! # Check out the link below for specific compile instructions for your system:
! # https://software.intel.com/en-us/articles/intel-mkl-link-line-advisor/
!
! To compile use:
! LINK="${MKLROOT}/lib/intel64/libmkl_lapack95_lp64.a -Wl,--start-group ${MKLROOT}/lib/intel64/libmkl_intel_lp64.a ${MKLROOT}/lib/intel64/libmkl_sequential.a ${MKLROOT}/lib/intel64/libmkl_core.a -Wl,--end-group -lpthread -lm -ldl"
! INC="-I${MKLROOT}/include/intel64/lp64/ -I${MKLROOT}/include/"
! ifort -warn all -o example3 $INC example3.f90 $LINK 

module m_least_squares

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! LINK="${MKLROOT}/lib/intel64/libmkl_lapack95_lp64.a -Wl,--start-group ${MKLROOT}/lib/intel64/libmkl_intel_lp64.a ${MKLROOT}/lib/intel64/libmkl_sequential.a ${MKLROOT}/lib/intel64/libmkl_core.a -Wl,--end-group -lpthread -lm -ldl"
! INC="-I${MKLROOT}/include/intel64/lp64/ -I${MKLROOT}/include/"
! ifort -warn all -o test_gttrf $INC test_gttrf.f90 $LINK 

! ./test_gttrf > test_gttrf.out
! gnuplot
! gnuplot> Th = 1
! gnuplot> plot "test_gttrf.out" u 1:2 w p pt 7, cosh((1-x)*Th)/cosh(Th)

module rd_setup

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! See link below for details:
! https://scicomp.stackexchange.com/questions/6854/mehrstellenverfahren-for-poisson
!
program poisson_higher_order

    implicit none

    integer, parameter :: wp = kind(1.0d0)
    real(wp), parameter :: pi = 4._wp*atan(0._wp)

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import numpy as np
import matplotlib.pyplot as plt

from scipy.integrate import solve_ivp

# LMTD case
def f(t,y,params):

    p2, p3, Tin = params

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def biperiodic_weight_matrix(bbox,x, p, n, diffs, 
                  coeffs=None,
                  phi=phs3, 
                  order=None,
                  eps=1.0, 
                  stencils=None):
  ''' 
  Returns a weight matrix which maps a functions values at `p` to an
  approximation of that functions derivative at `x`. This is a convenience
  function which first creates stencils and then computes the RBF-FD weights

ivan-pi

subroutine C_F_STRPOINTER (STRARRAY, FSTRPTR, MAXLEN)
  use, intrinsic :: ISO_C_BINDING
  implicit none
  character, dimension(*), target, intent(in) :: STRARRAY
  character(:), pointer, intent(out) :: FSTRPTR
  integer, intent(in), optional :: MAXLEN

  integer :: curlen

  curlen = 0

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import math
from fractions import Fraction

def continued_fraction(r,steps=10):

	cf = []

	for step in range(steps):
		i = math.floor(r)
		cf.append(i)

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module cbrt_mod1

implicit none
private

public :: cbrt, sp, r

interface cbrt
  module procedure cbrt_sp_sp
  module procedure cbrt_csp_csp

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module cbrt_mod2

implicit none
private

public :: cbrt, sp

interface cbrt
  module procedure cbrt_sp_sp
  module procedure cbrt_sp_csp