Modules

Blockkurs

ELEC446.Blockkurs History

Hide minor edits - Show changes to output

July 29, 2019, at 05:28 AM by 147.142.143.239 -
Changed line 42 from:
*'' [[https://www.mathcomp.uni-heidelberg.de/curriculum/ | HGS MathComp Curriculum page]]""
to:
*''[[https://www.mathcomp.uni-heidelberg.de/curriculum/ | HGS MathComp Curriculum page]]''
July 29, 2019, at 05:28 AM by 147.142.143.239 -
Added lines 41-42:

*'' [[https://www.mathcomp.uni-heidelberg.de/curriculum/ | HGS MathComp Curriculum page]]""
July 26, 2019, at 04:35 PM by 147.142.62.174 -
Changed lines 34-35 from:
*''Lecture 4''
 *
[[Attach:Lecture4Slides.pdf | slides]]
to:
*''Lecture 4'' [[Attach:Lecture4Slides.pdf | slides]]
July 26, 2019, at 04:01 PM by 147.142.62.174 -
Changed lines 32-34 from:
*Some good books on FEM
 *[[http://www.springer.com/us/book/9783540548225 | Hackbusch]]
 *[[http://www.springer.com/us/book/9780387205748 | Ern and Guermond]]
to:
*Some good books on FEM are [[http://www.springer.com/us/book/9783540548225 | Hackbusch]] and [[http://www.springer.com/us/book/9780387205748 | Ern and Guermond]]
July 26, 2019, at 03:59 PM by 147.142.62.174 -
Changed line 43 from:
 *Template for counting MCMC with moves [[Attach:counting_MCMC_template | counting_MCMC_template.m]]
to:
 *Template for counting MCMC with moves [[Attach:countingMCMCtemplate | countingMCMCtemplate.m]]
July 26, 2019, at 03:57 PM by 147.142.62.174 -
Changed lines 41-43 from:
 *Image of good and bad cells [[Attach:slide.tif|slide.tif]]. Matlab code [[Attach:makefake | makefake.m]] that generated the image, and uses functions [[Attach:putgood | putgood.m]] and [[Attach:putbad | putbad.m]].
to:
 *Image of good and bad cells [[Attach:slide.tif|slide.tif]].
 *Matlab
code [[Attach:makefake | makefake.m]] that generated the image, and uses functions [[Attach:putgood | putgood.m]] and [[Attach:putbad | putbad.m]].
 *Template for counting MCMC with moves [[Attach:counting_MCMC_template | counting_MCMC_template.m]]
July 26, 2019, at 03:51 PM by 147.142.62.174 -
Changed lines 37-38 from:
 *[[Attach:Lecture3Slides.pdf | slides]]
to:
 *[[Attach:Lecture4Slides.pdf | slides]]
Changed lines 40-41 from:
 *[[Attach:Compute3.pdf | Task sheet]]
 *Image of good and bad cells in Matlab mat format [[Attach:slide.mat | slide.mat]], or as [[Attach:slide.tif|slide.tif]]. Matlab code [[Attach:makefake.m | makefake.m]] that generated the image, and uses functions [[Attach:putgood.m | putgood.m]] and [[Attach:putbad.m | putbad.m]].
to:
 *[[Attach:Compute4.pdf | Task sheet]]
 *Image of good and bad cells [[Attach:slide.tif|slide.tif]]. Matlab code [[Attach:makefake | makefake.m]] that generated the image, and uses functions [[Attach:putgood | putgood.m]] and [[Attach:putbad | putbad.m]].
July 26, 2019, at 04:43 AM by 147.142.83.188 -
Changed line 27 from:
 *[[Attach:DJac |DJac.m]] function to return Jacobian matrix for inverse coefficient problem, built using secant approximation
to:
 *[[Attach:DJacc |DJac.m]] function to return Jacobian matrix for inverse coefficient problem, built using secant approximation
July 25, 2019, at 10:16 PM by 147.142.83.188 -
Changed line 29 from:
 *Task: Evaluate the Jacobian (linearized forward map) for D(x)->u(x,T), using the secant method in DJac, and FEM program in heatfem (or your own). What is the effective rank of this map? What happens to the rank as the discretization of D (and u) is refined?
to:
 *Task: Evaluate the Jacobian (linearized forward map) for D(x)->u(x,T), using the secant method in [=DJac=], and FEM program in heatfem (or your own). What is the effective rank of this map? What happens to the rank as the discretization of D (and u) is refined?
July 25, 2019, at 10:13 PM by 147.142.83.188 -
Changed line 29 from:
 *Evaluate the linearized forward map for D(x)->u(x,T), using the secant method and robfem.m FEM program (or your own). What is the effective rank of this map?
to:
 *Task: Evaluate the Jacobian (linearized forward map) for D(x)->u(x,T), using the secant method in DJac, and FEM program in heatfem (or your own). What is the effective rank of this map? What happens to the rank as the discretization of D (and u) is refined?
July 25, 2019, at 10:02 PM by 147.142.83.188 -
Changed line 27 from:
 *[[Attach:DJac |DJac.m]] function to return Jacobian matrix, built using secant approximation
to:
 *[[Attach:DJac |DJac.m]] function to return Jacobian matrix for inverse coefficient problem, built using secant approximation
July 25, 2019, at 10:01 PM by 147.142.83.188 -
Changed line 26 from:
 *[[Attach:heatIPsvals |heatIPsvals.m]] script file the plots the singular values for the inverse-source problem in the 1-dim heat equation
to:
 *[[Attach:heatIPsvals |heatIPsvals.m]] plot the singular values for the inverse-source problem in the 1-dim heat equation
July 25, 2019, at 10:01 PM by 147.142.83.188 -
Changed lines 26-27 from:
 *[[Attach:heatIPsvals |heatIPevals.m]] script file the plots the singular values for the inverse-source problem in the 1-dim heat equation
to:
 *[[Attach:heatIPsvals |heatIPsvals.m]] script file the plots the singular values for the inverse-source problem in the 1-dim heat equation
 *[[Attach:DJac |DJac.m]] function to return Jacobian matrix, built using secant approximation
July 25, 2019, at 09:57 PM by 147.142.83.188 -
Changed line 26 from:
 *[[Attach:heatIPevals |heatIPevals.m]] script file the plots the singular values for the inverse-source problem in the 1-dim heat equation
to:
 *[[Attach:heatIPsvals |heatIPevals.m]] script file the plots the singular values for the inverse-source problem in the 1-dim heat equation
July 25, 2019, at 09:57 PM by 147.142.83.188 -
Added line 26:
 *[[Attach:heatIPevals |heatIPevals.m]] script file the plots the singular values for the inverse-source problem in the 1-dim heat equation
July 25, 2019, at 04:44 PM by 147.142.143.249 -
Changed line 18 from:
 *[[Attach:heatfem | heatfem.m]] that builds FEM matrices for heat problem
to:
 *[[Attach:heatfem | heatfem.m]] that builds FEM mass and stiffness matrices for 1-dim heat problem
July 25, 2019, at 04:42 PM by 147.142.143.249 -
Deleted lines 13-14:

Changed line 26 from:
 *[[Attach:robfem |robfem.m]] that builds FEM mass and stiffness matrices for 1-dim space part
to:
 *[[Attach:robfem |robfem.m]] that builds FEM matrix for 1-dim operator -cu'' + alpha u
July 25, 2019, at 04:35 PM by 147.142.143.249 -
Changed lines 28-29 from:

*Evaluate the linearized forward map for D(x)->u(x,T), using the secant method and the simple FEM program supplied. What is the effective rank of this map?
to:
 *[[Attach:robfem |robfem.m]] that builds FEM mass and stiffness matrices for 1-dim space part
 *Evaluate the linearized forward map for D(x)->u(x,T), using the secant method and robfem.m FEM program (or your own)
. What is the effective rank of this map?
July 24, 2019, at 11:52 PM by 147.142.143.249 -
Added line 20:
 *[[Attach:heatfem | heatfem.m]] that builds FEM matrices for heat problem
Deleted lines 24-27:


*''Compute 3''
 *[[Attach:heatfem | heatfem.m]] that builds FEM matrices for heat problem
Added lines 26-28:

*''Compute 3''

July 24, 2019, at 10:43 PM by 147.142.143.249 -
Changed line 27 from:
 *[[Attach:heatfem.m | heatfem.m]] that builds FEM matrices for heat problem
to:
 *[[Attach:heatfem | heatfem.m]] that builds FEM matrices for heat problem
July 24, 2019, at 10:42 PM by 147.142.143.249 -
Changed line 28 from:
 *''Python code:'' Andres' python code [[Attach:Minicourse.zip |zip file]] for heat FEM
to:
 *''Python code:'' Andres' python code [[Attach:Minicourse.zip |zip file]] plus IP text
July 24, 2019, at 10:38 PM by 147.142.143.249 -
Changed lines 20-23 from:



to:
 * Write a sampler for the inverse heat-conductivity problem in (constant) D (or use my awful code, above)
 * Tune the window size for your RWM sampler, or better still (challenge question) plot a graph of IACT as function of window w to find the optimal w
 *Consider error in the final time T, T~Unif[1.8,2.2]. Perform joint inference for D and T, and say whether inference for D is significantly altered.



Changed lines 28-32 from:
 *''Python code''
 *Andres' python code [[Attach:Minicourse.zip |zip file]] for heat FEM
 *Complete your sampler for the inverse problem in (constant) D
 *Tune the window size for your RWM sampler, or better still (challenge question) plot a graph of IACT as function of window w to find the optimal w
 *Consider error in the final time T, T~Unif[1.8,2.2]. Perform joint inference for D and T, and say whether inference for D is significantly altered.
to:
 *''Python code:'' Andres' python code [[Attach:Minicourse.zip |zip file]] for heat FEM
Changed line 36 from:
*''Lecture 3''
to:
*''Lecture 4''
Changed line 39 from:
*''Compute 3''
to:
*''Compute 4''
Deleted lines 42-44:
*''Public Lecture''
 *[[Attach:Fox_IMI_PL.pdf | slides]]
 *[[Attach:Fox_IMI_movie.mp4 | movie]]
July 24, 2019, at 10:34 PM by 147.142.143.249 -
Changed lines 18-19 from:
 *[[Attach:tauvsw.m |Code to plot IACT as function of window using mcgauss.m]]
 *[[Attach:Dmcmc.m |Code to sample inverse heat problem]]
to:
 *[[Attach:tauvsw |Code to plot IACT as function of window using mcgauss.m]]
 *[[Attach:Dmcmc |Code to sample inverse heat problem]]




*''Compute 3''
Changed lines 26-27 from:

*''Python code''
to:
 *''Python code''
Deleted lines 27-28:

*''Compute 2''
July 24, 2019, at 10:19 PM by 147.142.143.249 -
Changed lines 11-13 from:
 *[[Attach:mcgauss.m | mcgauss.m]] MH for sampling a Gaussian in 1-dim, with mean and covariance

to:
 *[[Attach:mcgaus | mcgaus.m]] MH for sampling a Gaussian in 1-dim
 *[[Attach:mcgaus_demo | mcgaus_demo.m]] Traces of Gaussian sampler for different window sizes


Deleted line 16:
 *[[Attach:mcgauss.m | mcgauss.m]]
July 24, 2019, at 10:16 PM by 147.142.143.249 -
Changed lines 9-10 from:
*''Compute 1'' (for m-files, right click to 'Save As' to get formatting correct)
 *[[Attach:mcmc.m | mcmc
.m]] is a basic Metropolis-Hastings algorithm
to:
*''Compute 1'' (for m-files, right click to 'Save As' to get formatting correct, and add .m extension (my silly Wiki does not allow .m extensions))
 *[[Attach:mcmc | mcmc.m]].m is a basic Metropolis-Hastings algorithm, with acceptance prob. for exponential distribution
July 24, 2019, at 10:01 PM by 147.142.143.249 -
Deleted line 8:
Added lines 10-14:
 *[[Attach:mcmc.m | mcmc.m]] is a basic Metropolis-Hastings algorithm
 *[[Attach:mcgauss.m | mcgauss.m]] MH for sampling a Gaussian in 1-dim, with mean and covariance


*''Compute 2'' (for m-files, right click to 'Save As' to get formatting correct)
Changed line 22 from:
 *Andres' [[Attach:Minicourse.zip |zip file]]
to:
 *Andres' python code [[Attach:Minicourse.zip |zip file]] for heat FEM
July 24, 2019, at 09:55 PM by 147.142.143.249 -
Changed lines 3-4 from:
Instructors: [[http://elecphysics.otago.ac.nz/w/index.php/Colin_Fox|Colin Fox]] and [[http://www.cimat.mx/~jac/| J Andres Christen]]
to:
Instructors: [[http://elecphysics.otago.ac.nz/w/index.php/Colin_Fox|Colin Fox]]
Changed lines 6-7 from:
 * [[Attach:BUC5notes.pdf | lecture notes]] (so far)
 *Gareth Roberts'
[[http://www2.warwick.ac.uk/fac/sci/statistics/staff/academic-research/roberts/st911/notes2012partiii.pdf | notes on Statistical Inference]] has useful statements of basic  MCMC methods and theorems
to:
 * Book by Jun Liu: [[https://www.springer.com/de/book/9780387763699 | Monte Carlo Strategies in Scientific Computing]]
 * Gareth Roberts' [[Attach:
notes2012partiii.pdf | notes on Statistical Inference]] has useful statements of basic  MCMC methods and theorems
July 24, 2019, at 09:50 PM by 147.142.143.249 -
Changed line 1 from:
'+Resources for [[https://www.mathcomp.uni-heidelberg.de/curriculum/ | Blockkurs]] on Markov Chain Monte Carlo for Inverse Problems in PDEs+'
to:
'+Resources for [[https://www.mathcomp.uni-heidelberg.de/curriculum/ | Blockkurs]] on Markov Chain Monte Carlo for Inverse Problems in [=PDEs=]+'
July 24, 2019, at 09:49 PM by 147.142.143.249 -
Changed line 1 from:
'+Resources for [[https://www.mathcomp.uni-heidelberg.de/curriculum/ | Blockkurs]] on Markov Chain Monte Carlo for Inverse Problems in PDEs:+'
to:
'+Resources for [[https://www.mathcomp.uni-heidelberg.de/curriculum/ | Blockkurs]] on Markov Chain Monte Carlo for Inverse Problems in PDEs+'
July 24, 2019, at 09:47 PM by 147.142.143.249 -
Changed line 1 from:
'+Resources for BUC5 computing labs:+'
to:
'+Resources for [[https://www.mathcomp.uni-heidelberg.de/curriculum/ | Blockkurs]] on Markov Chain Monte Carlo for Inverse Problems in PDEs:+'
July 24, 2019, at 09:45 PM by 147.142.143.249 -
Added lines 1-40:
'+Resources for BUC5 computing labs:+'

Instructors: [[http://elecphysics.otago.ac.nz/w/index.php/Colin_Fox|Colin Fox]] and [[http://www.cimat.mx/~jac/| J Andres Christen]]

*''Some Reading ''
 * [[Attach:BUC5notes.pdf | lecture notes]] (so far)
 *Gareth Roberts' [[http://www2.warwick.ac.uk/fac/sci/statistics/staff/academic-research/roberts/st911/notes2012partiii.pdf | notes on Statistical Inference]] has useful statements of basic  MCMC methods and theorems


*''Compute 1'' (for m-files, right click to 'Save As' to get formatting correct)
 *[[Attach:mcgauss.m | mcgauss.m]]
 *Ulli Wollf's [[http://www.physik.hu-berlin.de/com/ALPHAsoft/ | UWerr MatLab code]] and documentation
 *[[Attach:tauvsw.m |Code to plot IACT as function of window using mcgauss.m]]
 *[[Attach:Dmcmc.m |Code to sample inverse heat problem]]
 *[[Attach:heatfem.m | heatfem.m]] that builds FEM matrices for heat problem

*''Python code''
 *Andres' [[Attach:Minicourse.zip |zip file]]

*''Compute 2''
 *Complete your sampler for the inverse problem in (constant) D
 *Tune the window size for your RWM sampler, or better still (challenge question) plot a graph of IACT as function of window w to find the optimal w
 *Consider error in the final time T, T~Unif[1.8,2.2]. Perform joint inference for D and T, and say whether inference for D is significantly altered.
 *Evaluate the linearized forward map for D(x)->u(x,T), using the secant method and the simple FEM program supplied. What is the effective rank of this map?


*Some good books on FEM
 *[[http://www.springer.com/us/book/9783540548225 | Hackbusch]]
 *[[http://www.springer.com/us/book/9780387205748 | Ern and Guermond]]

*''Lecture 3''
 *[[Attach:Lecture3Slides.pdf | slides]]

*''Compute 3''
 *[[Attach:Compute3.pdf | Task sheet]]
 *Image of good and bad cells in Matlab mat format [[Attach:slide.mat | slide.mat]], or as [[Attach:slide.tif|slide.tif]]. Matlab code [[Attach:makefake.m | makefake.m]] that generated the image, and uses functions [[Attach:putgood.m | putgood.m]] and [[Attach:putbad.m | putbad.m]].

*''Public Lecture''
 *[[Attach:Fox_IMI_PL.pdf | slides]]
 *[[Attach:Fox_IMI_movie.mp4 | movie]]