#define NULL ((void *)0)
typedef unsigned long size_t; // Customize by platform.
typedef long intptr_t;
typedef unsigned long uintptr_t;
typedef long scalar_t__; // Either arithmetic or pointer type.
/* By default, we understand bool (as a convenience). */
typedef int bool;
#define false 0
#define true 1

/* Forward declarations */

/* Type definitions */

/* Variables and functions */
int /*<<< orphan*/ printf(char *);
void mads_info() {
  printf("MADS is an open-source code designed as an integrated "
         "high-performance computational framework performing\n");
  printf("a wide range of model-based analyses: Sensitivity Analysis (SA), "
         "Parameter Estimation (PE), Model Inversion and Calibration,\n");
  printf("Uncertainty Quantification (UQ), Model Selection and Averaging, and "
         "Decision Support (DS).\n\n");
  printf("MADS utilizes adaptive rules and techniques which allows the "
         "analyses to be performed with minimum user input. The code\n");
  printf("provides a series of alternative algorithms to perform each type of "
         "model analyses. The code allows for coupled model\n");
  printf("parameters and regularization terms that are internally computed "
         "based on user-defined mathematical expressions.\n\n");
  printf("USAGE: mads problem_name    [ keywords | options ]  OR\n");
  printf("       mads MADS_input_file [ keywords | options ]  OR\n");
  printf("       mads PEST_input_file [ keywords | options ]  (MADS is "
         "compatible with PEST control, template and instruction files)\n\n");
  printf("       problem_name:        name of the solved problem; "
         "MADS_input_file named problem_name.mads is expected\n");
  printf("       MADS_input_file:     problem input file in MADS format "
         "(typically *.mads)\n");
  printf("       PEST_input_file:     problem input file in PEST format (PEST "
         "control file; *.pst)\n\n");
  printf("keywords & options (can be provided in any order):\n\n");
  printf("problem type keywords:\n");
  printf("   check              - check model setup and input/output files (no "
         "model execution)\n");
  printf("   create             - create calibration problem based on provided "
         "model parameters (single model execution to compute calibration "
         "targets)\n");
  printf("   forward            - forward model run (no calibration); "
         "recommended for model setup checking\n");
  printf("   calibrate          - calibration run [default if no problem type "
         "keyword is provided]\n");
  printf("   montecarlo         - Monte-Carlo analysis\n");
  printf("   gsens              - global sensitivity analysis\n");
  printf("   glue               - Generalized Likelihood Uncertainty "
         "Estimation\n");
  printf("   lsens              - local sensitivity analysis (standalone or at "
         "the end of the calibration)\n");
  printf("   eigen              - local eigensystem analysis (standalone or at "
         "the end of the calibration)\n");
  printf("   abagus             - Agent-Based Global Uncertainty & Sensitivity "
         "Analysis\n");
  printf("   infogap            - Info-gap decision analysis\n");
  printf("   postpua            - predictive uncertainty analysis of sampling "
         "results (currently for abagus PSSA files only)\n");
  printf("   bayes              - Bayesian parameter sampling using DREAM "
         "(DiffeRential Evolution Adaptive Metropolis; Vrugt et al. 2009)\n");
  printf("\ncalibration method keywords (select one):\n");
  printf("   single             - single calibration using initial guesses "
         "provided in the input file [default]\n");
  printf("   igrnd              - sequential calibrations using a set of "
         "random initial values (number of realizations defined by real=X)\n");
  printf("   igpd               - sequential calibrations using a set of "
         "discretized initial values (discretization defined in the input "
         "file)\n");
  printf("   ppsd               - sequential calibrations using partial "
         "parameter space discretization (PPSD) method (discretization defined "
         "in the input file)\n");
  printf("\ncalibration termination criteria:\n");
  printf("   eval=[integer]     - functional evaluations exceed the predefined "
         "value [default eval=5000]\n");
  printf("   cutoff=[real]      - objective function is below the cutoff value "
         "[default cutoff=0]\n");
  printf("   obsrange           - model predictions are within predefined "
         "calibration ranges\n");
  printf("   obserror=[real]    - model predictions are within a predefined "
         "absolute error [default obserror=0.1]\n");
  printf(
      "   parerror=[real]    - model parameters are within a predefined "
      "absolute error from their known 'true' values [default parerror=0.1]\n");
  printf("\nuser-enforced termination:\n");
  printf("   problem_name.quit  - if file with this name exists in the running "
         "directory, MADS terminates as soon as possible.\n");
  printf("   problem_name.stop  - if file with this name exists in the running "
         "directory, MADS terminates after saving intermediate results.\n");
  printf("\noptimization method (opt=[string]; various combinations are "
         "possible, e.g. pso_std_lm_gsl):\n");
  printf("   opt=lm             - Local Levenberg-Marquardt optimization "
         "[default]\n");
  printf("   opt=lm_levmar      - Local Levenberg-Marquardt optimization using "
         "LEVMAR library\n");
  printf("   opt=lm_gsl         - Local Levenberg-Marquardt optimization using "
         "GSL library\n");
  printf("   opt=lm_ms          - Local Multi-Start (Multi-Try) "
         "Levenberg-Marquardt (MSLM) optimization using multiple random "
         "initial guesses\n");
  printf("   opt=pso            - Global Particle Swarm optimization (default "
         "Standard2006; http://clerc.maurice.free.fr/pso)\n");
  printf("   opt=apso           - Global Adaptive Particle Swarm optimization "
         "(default TRIBES)\n");
  printf("   opt=swarm          - Global Particle Swarm optimization "
         "Standard2006 (also opt=pso_std)\n");
  printf("   opt=tribes         - Global Particle Swarm optimization TRIBES-D "
         "(Clerc 2004; http://clerc.maurice.free.fr/pso)\n");
  printf("   opt=squads         - SQUADS: Adaptive hybrid optimization using "
         "coupled local and global optimization techniques\n");
  printf("\ngeneral calibration/optimization options:\n");
  printf("   retry=[integer]    - number of optimization retries [default "
         "retry=0]\n");
  printf("   particles=[integer]- number of initial particles or tribes "
         "[default particles=10+2*sqrt(Number_of_parameters)]\n");
  printf("   lmeigen|eigen      - eigen analysis of the intermediate / final "
         "optimized solution\n");
  printf("\nLevenberg-Marquardt optimization options:\n");
  printf(
      "   lmfactor=[double]  - multiplier applied to compute when to initiate "
      "LM searches within SQUADS algorithm [default lmfactor=1.0]\n");
  printf("   lmindirect         - Indirect computation of LM alpha coefficient "
         "[default DIRECT/Delayed gratification computation]\n");
  printf("   lmmu=[double]      - LM alpha multiplier for direct computation "
         "of LM alpha coefficient when OF decreases [default lmmu=0.1]\n");
  printf("   lmnu=[integer]     - LM alpha multiplier for direct computation "
         "of LM alpha coefficient when OF increases [default lmnu=10]\n");
  printf("   lmaccel            - LM geodesic acceleration as proposed by "
         "Transtrum et al (2011) [default NO acceleration]\n");
  printf("   lmratio=[double]   - LM acceleration velocity ratio for "
         "recomputing the Jacobian [default lmratio=(3/4)^2]\n");
  printf(
      "   lmh=[double]       - LM acceleration multiplier [default lmh=0.1]\n");
  printf("   lmiter=[integer]   - number of LM iterations [default computed "
         "internally based on number of evaluations]\n");
  printf("   lmnlam=[integer]   - Maximum number of linear solves (lambda "
         "searches) after each Jacobian estimate [default lmnlam=10]\n");
  printf("   lmnlamof=[integer] - Number of acceptable linear solves (lambda "
         "searches) with similar OF's during LM optimization [default "
         "lmnlamof=3]\n");
  printf("   lmnjacof=[integer] - Number of acceptable jacobian iterations "
         "with similar OF's during LM optimization [default lmnjacof=5]\n");
  printf(
      "   lmerror=[double]   - LM convergence error [default lmerror=1e-5]\n");
  printf("\nsampling method (smp=[string] OR mslm=[string] for Multi-Start "
         "Levenberg-Marquardt (MSLM) analysis using multiple retries):\n");
  printf("   smp=olhs           - Optimal Latin Hyper Cube sampling [default] "
         "(if real=1 RANDOM; if real>1 IDLHS; if real>500 LHS)\n");
  printf("   smp=lhs            - Latin Hyper Cube sampling (LHS)\n");
  printf("   smp=idlhs          - Improved Distributed Latin Hyper Cube "
         "sampling (IDLHS)\n");
  printf("   smp=random         - Random sampling\n");
  printf("\nsampling options:\n");
  printf("   real=[integer]     - number of random realizations / samples "
         "[default real=100]\n");
  printf("   case=[integer]     - execute a single case from all the "
         "realizations / samples (applied in PPSD, IGDP, IGRND, MONTECARLO)\n");
  printf("   seed=[integer]     - random seed value [randomly generated by "
         "default]\n");
  printf("\nobjective function functional form options (select one; "
         "regularizaiton terms can be added separately):\n");
  printf("   ssr                - sum of the squared residuals [default]\n");
  printf("   ssd0               - sum of the squared discrepancies\n");
  printf("   ssdx               - sum of the squared discrepancies increased "
         "to get in the bounds\n");
  printf("   ssda               - sum of the squared discrepancies and "
         "absolute residuals\n");
  printf("   ssdr               - sum of the squared discrepancies and squared "
         "residuals\n");
  printf("\ntransformation of parameter and observation properties:\n");
  printf("   nosin              - Sin transformation of optimized parameters "
         "is not applied [parameters are sin transformed by default]\n");
  printf("   sindx              - Parameter space step for numerical "
         "derivatives of sin transformed parameters\n");
  printf("                        [default sindx=1e-7 for internal problems; "
         "sindx=0.1 for external problems]\n");
  printf("   lindx              - Parameter space step for numerical "
         "derivatives of not transformed parameters [default lindx=0.001]\n");
  printf("   pardx              - Parameter space step for parameter space "
         "discretization [default pardx=0.1]\n");
  printf("   plog=[-1,0,1]      - Log transformation of all optimized "
         "parameters is enforced (1) or disabled (0)\n");
  printf("                        [default plog=-1; log transformation is "
         "explicitly defined for each parameter in the input file]\n");
  printf("   olog=[-1,0,1]      - Log transformation of all the observations "
         "(simulated and measured) is enforced (1) or disabled (0)\n");
  printf("                        [default olog=-1; log transformation is "
         "explicitly defined for each observation in the input file]\n");
  printf("   oweight=[-1,0,1,2] - Weights for all the observation residuals "
         "are defined:\n");
  printf("                        0 = zero weight, 1 = unit weight, 2 = weight "
         "reversely proportional to observation\n");
  printf("                        [default oweight=-1; weights for each "
         "observation are explicitly defined in the input file]\n");
  printf("   obsdomain=[float]  - observation space domain size [default "
         "provided in the MADS input file]\n");
  printf("   obsstep=[float]    - observation space domain step to explore "
         "info-gap observation uncertainty [default ignored]\n");
  printf("\nparallelization (available parallelization resources are "
         "internally detected by default; supported: Slurm, Moab, BProc, LSB, "
         "PBS, Beowulf, OpenMPI, OpenMP, POSIX, ...):\n");
  printf(
      "   np=[integer]       - Number of requested parallel jobs [optional]\n");
  printf("   mpi                - Use OpenMPI parallelization [optional]\n");
  printf("   posix[=integer]    - POSIX parallel threading [optional]; number "
         "of threads can be defined as well\n");
  printf("   omp[=integer]      - OpenMP parallel threading [optional]; number "
         "of threads can be defined as well\n");
  printf("   ssh                - Forces the use of ssh to execute external "
         "jobs at the comptuer nodes\n");
  printf("   ppt=[integer]      - Number of processors per an external task "
         "[optional]\n");
  printf(
      "   nplambda=[integer] - Number of requested parallel lambda runs in the "
      "case of Levenberg-Marquardt optimization [optional; nplambda <= np]\n");
  printf("   rstfile=[string]   - name of existing ZIP restart file to be used "
         "(created by previous Parallel MADS run) [optional]\n");
  printf("   rstdir=[string]    - name of existing restart directory to be "
         "used (created by previous Parallel MADS run) [optional]\n");
  printf(
      "   restart=[integer]  - restart=1 (default; automatic restart if "
      "possible); restart=0 (force no restart); restart=-1 (force restart)\n");
  printf("                        by default the analyses will be restarted "
         "automatically (restart=1)\n");
  printf(
      "   bin_restart        - restart information is stored in binary files "
      "(by default, model outputs are added in a zip file for restart)\n");
  printf("\nABAGUS (Agent-Based Global Uncertainty & Sensitivity Analysis) "
         "options:\n");
  printf("   infile=[string]    - name of previous results file to be used to "
         "initialize Kd-tree [default=NULL]\n");
  printf("   energy=[integer]   - initial energy for particles [default "
         "energy=10000]\n");
  printf("\noptions for the build-in analytical solutions:\n");
  printf(
      "   point              - point contaminant source in 3D flow domain\n");
  printf(
      "   plane              - plane contaminant source in 3D flow domain\n");
  printf(
      "   box                - brick contaminant source in 3D flow domain\n");
  printf("   obs_int=[1,2]      - concentration integration along observation "
         "well screens (1 - mid point; 2 - two end points [default=1]\n");
  printf("   disp_tied          - lateral and vertical transverse "
         "dispersivities are fractions of the longitudinal dispersivity\n");
  printf("   disp_scaled        - longitudinal dispersivity is scaled with the "
         "travel distance\n");
  printf("                        if disp_scaled and disp_tied are applied, "
         "longitudinal dispersivity is scaled and\n");
  printf(
      "                        lateral and vertical transverse dispersivities "
      "are fractions of the scaled longitudinal dispersivity\n");
  printf("   disp_scaled=2      - longitudinal, lateral and vertical "
         "transverse dispersivities are scaled with the travel distance\n");
  printf("   time_step          - parameter \"end time\" is representing the "
         "period (dt) within which the source is active\n");
  printf("\nbuild-in test problems for optimization / "
         "uncertainty-quantification techniques (local and global methods):\n");
  printf("   test=[integer]     - test problem ID [default=1]:\n");
  printf("                           1: Parabola (Sphere)\n");
  printf("                           2: Griewank\n");
  printf("                           3: Rosenbrock\n");
  printf("                           4: De Jong's Function #4\n");
  printf("                           5: Step\n");
  printf(
      "                           6: Alpine function (Clerc's Function #1)\n");
  printf("                           7: Rastrigin\n");
  printf("                           8: Krishna Kumar\n");
  printf("                           9: Tripod function 2D\n");
  printf("                          10: Shekel's Foxholes 2D\n");
  printf("                          11: Shekel's Foxholes 5D\n");
  printf("                          12: Shekel's Foxholes 10D\n");
  printf("                          20: Shekel's Foxholes 2D (alternative; "
         "global methods only)\n");
  printf("                          21: Polynomial fitting (global methods "
         "only)\n");
  printf("                          22: Ackley (global methods only)\n");
  printf("                          23: Eason 2D (global methods only)\n");
  printf(
      "                          31: Rosenbrock (2D simplified alternative)\n");
  printf("                          32: Griewank (alternative)\n");
  printf("                          33: Rosenbrock (alternative with d*(d-1) "
         "observations\n");
  printf("                          34: Powell's Quadratic\n");
  printf("                          35: Booth\n");
  printf("                          36: Beale\n");
  printf("                          37: Parsopoulos\n");
  printf("                          Curve-fitting test functions:\n");
  printf(
      "                          40: Sin/Cos test function (2 parameters)\n");
  printf(
      "                          41: Sin/Cos test function (4 parameters)\n");
  printf("                          42: Sin/Cos test function (2 parameters; "
         "simplified)\n");
  printf("                          43: Exponential Data Fitting I (5 "
         "parameters)\n");
  printf("                          44: Exponential Data Fitting II (11 "
         "parameters)\n");
  printf("   dim=[integer]      - dimensionality of parameter space for the "
         "test problem (fixed for some of the problems) [default=2]\n");
  printf("   npar=[integer]     - number of model parameters for the test "
         "problem (fixed for some of the problems) [default=2]\n");
  printf("   nobs=[integer]     - number of observations for the test problem "
         "(fixed for some of the problems) [default=2]\n");
  printf("   pardomain=[float]  - parameter space domain size [default "
         "pardomain=100]\n");
  printf("\ndebugging / verbose levels:\n");
  printf("   force | f          - enforce running even if a file *.running "
         "exists (the file *.running is to prevent overlapping executions)\n");
  printf("   quiet | q          - no screen output (all the screen output is "
         "saved in a file with extension mads_output\n");
  printf("   debug=[0-5]        - general debugging [default debug=0]\n");
  printf("   fdebug=[0-5]       - model evaluation debugging [default "
         "fdebug=0]\n");
  printf("   ldebug=[0-3]       - Levenberg-Marquardt optimization debugging "
         "[default ldebug=0]\n");
  printf("   pdebug=[0-3]       - Particle Swarm optimization debugging "
         "[default pdebug=0]\n");
  printf(
      "   mdebug=[0-3]       - Random sampling debugging [default mdebug=0]\n");
  printf("   odebug=[0-1]       - Record objective function progress in a file "
         "with extension \'ofe\' [default odebug=0]\n");
  printf("   tdebug=[0-1]       - Output process times for various tasks "
         "[default tdebug=0]\n");
  printf("   tpldebug=[0-3]     - Debug the writing of external files [default "
         "tpldebug=0]\n");
  printf("   insdebug=[0-3]     - Debug the reading of external files [default "
         "insdebug=0]\n");
  printf("   pardebug=[0-3]     - Debug the parallel execution [default "
         "pardebug=0]\n");
  printf("\npre-/post-processing:\n");
  printf("   yaml               - Reads/writes/converts MADS files in YAML "
         "format\n");
  printf("   xml                - Reads/writes/converts MADS files in XML "
         "format\n");
  printf("   resultsfile=[file] - Post process results saved in a previously "
         "generated resultsfile (e.g. using 'igrnd' analysis)\n");
  printf("   resultscase=[int]  - Post process specific case saved in "
         "resultsfile (if resultscase<0, first abs(resultscase) cases)\n");
  printf("   cutoff=[real]      - Post process all cases saved in resultsfile "
         "with objective function below the cutoff value\n");
  printf("   obsrange           - Post process all cases saved in resultsfile "
         "with model predictions within predefined calibration ranges\n");
  printf("   pargen             - Generate MADS input files for independent "
         "multi-processor runs [default pargen=0]\n");
  printf("   save               - Save MADS input/output files for successful "
         "parameter sets [default save=0]\n");
  printf("\nExamples:\n");
  printf("   mads a01 test=2 opt=lm eigen igrnd real=1 (no input files are "
         "needed for execution)\n");
  printf("   mads a01 test=2 opt=squads igrnd real=1\n");
  printf("   mads a01 test=2 abagus cutoff=0.1 eval=100000 (collect solutions "
         "of Griewank function below phi cutoff)\n");
  printf("   mads a01 test=3 abagus cutoff=20 eval=100000  (collect solutions "
         "of Rosenbrock function below phi cutoff)\n");
  printf("   mads examples/contamination/s01 ldebug lmeigen (file s01.mads is "
         "located in examples/contamination)\n");
  printf("   mads examples/contamination/s01 ldebug lmeigen igrnd real=1\n");
  printf("   mads examples/contamination/s01 seed=1549170842 obsrange igrnd "
         "real=1\n");
  printf("   mads examples/contamination/s01 opt=squads seed=1549170842 eigen "
         "obsrange pdebug igrnd real=1\n");
  printf("   mads examples/contamination/s01 opt=pso seed=1549170842 eigen "
         "obsrange igrnd real=1\n");
  printf("   mads examples/contamination/s01-flagged ppsd (Partial Parameter "
         "Space Discretization)\n");
  printf("   mads examples/contamination/s01-flagged igpd (Initial Guesses "
         "based on Discreetly distributed model parameters)\n");
  printf("   mads examples/contamination/s01 igrnd real=10 (Random Initial "
         "Guesses; all parameters)\n");
  printf("   mads examples/contamination/s01-flagged igrnd real=10 (Random "
         "Initial Guesses; only flagged parameters)\n");
  printf("   mads examples/contamination/s01 monte real=10 (Monte Carlo "
         "Analysis)\n");
  printf("   cd examples/wells; mads w01.mads igrnd real=1 seed=501228648 "
         "eigen\n");
  printf("\nParallel Levenberg-Marquardt optimization:\n");
  printf("   cd examples/wells-short\n");
  printf("   mads w01parallel.mads restart=0 np=2 ldebug pardebug=2 (Parallel "
         "optimization using 2 processors)\n");
  printf("   mads w01parallel.mads restart=0 np=11 nplambda=11\n");
  printf("   mads w01parallel.mads restart=0 np=3 nplambda=3 lmnlam=21 "
         "lmnlamof=12 (if a small number of processors is used, lmnlam & "
         "lmnlamof should be increased)\n");
  printf("\nComparisons between local and global methods:\n");
  printf("   mads a01 test=3 opt=lm     igrnd real=1000 cutoff=1e-3 "
         "(Levenberg-Marquardt optimization)\n");
  printf("   mads a01 test=3 opt=lm_ms  igrnd real=1000 cutoff=1e-3 "
         "(Multi-Start Levenberg-Marquardt optimization)\n");
  printf("   mads a01 test=3 opt=swarm  igrnd real=1000 cutoff=1e-3 (Particle "
         "Swarm optimization Standard2006)\n");
  printf("   mads a01 test=3 opt=tribes igrnd real=1000 cutoff=1e-3 (Particle "
         "Swarm optimization TRIBES-D)\n");
  printf("   mads a01 test=3 opt=squads igrnd real=1000 cutoff=1e-3 (Adaptive "
         "hybrid optimization Squads)\n");
  printf("\nComparisons with PEST (http://www.sspa.com/pest/):\n");
  printf("   cd examples/contamination\n");
  printf("   mads s02 lmeigen                  (file s02.mads is located in "
         "examples/contamination)\n");
  printf("   pest s02pest                   (file s02pest.pst is located in "
         "examples/contamination)\n");
  printf("   mads w01 lmeigen     (files associated with problem w01 are "
         "located in examples/wells)\n");
  printf("   pest w01pest     (files associated with problem w01pest are "
         "located in examples/wells)\n");
  printf("   pest w02pest     (files associated with problem w02pest are "
         "located in examples/wells)\n");
  printf("\nFor additional information:\n");
  printf("   web:   http://mads.lanl.gov -:- "
         "http://www.ees.lanl.gov/staff/monty/codes/mads\n");
  printf("   repo:  http://gitlab.com/monty/mads\n");
  printf("   git:   git clone git@gitlab.com:monty/mads.git\n");
  printf("   email: Velimir V Vesselinov (monty) vvv@lanl.gov -:- "
         "velimir.vesselinov@gmail.com\n");
}


x86 assembly (clang, -O0):
<mads_info>:
push   %rbp
mov    %rsp,%rbp
lea    0xee5(%rip),%rdi
call   1030 <printf@plt>
lea    0xf44(%rip),%rdi
call   1030 <printf@plt>
lea    0xfb6(%rip),%rdi
call   1030 <printf@plt>
lea    0x1007(%rip),%rdi
call   1030 <printf@plt>
lea    0x1074(%rip),%rdi
call   1030 <printf@plt>
lea    0x10df(%rip),%rdi
call   1030 <printf@plt>
lea    0x1146(%rip),%rdi
call   1030 <printf@plt>
lea    0x1172(%rip),%rdi
call   1030 <printf@plt>
lea    0x119e(%rip),%rdi
call   1030 <printf@plt>
lea    0x120f(%rip),%rdi
call   1030 <printf@plt>
lea    0x1270(%rip),%rdi
call   1030 <printf@plt>
lea    0x12b6(%rip),%rdi
call   1030 <printf@plt>
lea    0x1305(%rip),%rdi
call   1030 <printf@plt>
lea    0x132e(%rip),%rdi
call   1030 <printf@plt>
lea    0x133a(%rip),%rdi
call   1030 <printf@plt>
lea    0x1385(%rip),%rdi
call   1030 <printf@plt>
lea    0x1408(%rip),%rdi
call   1030 <printf@plt>
lea    0x145e(%rip),%rdi
call   1030 <printf@plt>
lea    0x14ac(%rip),%rdi
call   1030 <printf@plt>
lea    0x14ce(%rip),%rdi
call   1030 <printf@plt>
lea    0x14f7(%rip),%rdi
call   1030 <printf@plt>
lea    0x1532(%rip),%rdi
call   1030 <printf@plt>
lea    0x1588(%rip),%rdi
call   1030 <printf@plt>
lea    0x15de(%rip),%rdi
call   1030 <printf@plt>
lea    0x1621(%rip),%rdi
call   1030 <printf@plt>
lea    0x1649(%rip),%rdi
call   1030 <printf@plt>
lea    0x16b1(%rip),%rdi
call   1030 <printf@plt>
lea    0x1726(%rip),%rdi
call   1030 <printf@plt>
lea    0x1746(%rip),%rdi
call   1030 <printf@plt>
lea    0x17a1(%rip),%rdi
call   1030 <printf@plt>
lea    0x1816(%rip),%rdi
call   1030 <printf@plt>
lea    0x1890(%rip),%rdi
call   1030 <printf@plt>
lea    0x191b(%rip),%rdi
call   1030 <printf@plt>
lea    0x1933(%rip),%rdi
call   1030 <printf@plt>
lea    0x1987(%rip),%rdi
call   1030 <printf@plt>
lea    0x19d4(%rip),%rdi
call   1030 <printf@plt>
lea    0x1a1c(%rip),%rdi
call   1030 <printf@plt>
lea    0x1a79(%rip),%rdi
call   1030 <printf@plt>
lea    0x1af4(%rip),%rdi
call   1030 <printf@plt>
lea    0x1b05(%rip),%rdi
call   1030 <printf@plt>
lea    0x1b6f(%rip),%rdi
call   1030 <printf@plt>
lea    0x1be7(%rip),%rdi
call   1030 <printf@plt>
lea    0x1c39(%rip),%rdi
call   1030 <printf@plt>
lea    0x1c77(%rip),%rdi
call   1030 <printf@plt>
lea    0x1cc0(%rip),%rdi
call   1030 <printf@plt>
lea    0x1d06(%rip),%rdi
call   1030 <printf@plt>
lea    0x1d7f(%rip),%rdi
call   1030 <printf@plt>
lea    0x1de8(%rip),%rdi
call   1030 <printf@plt>
lea    0x1e32(%rip),%rdi
call   1030 <printf@plt>
lea    0x1e82(%rip),%rdi
call   1030 <printf@plt>
lea    0x1eea(%rip),%rdi
call   1030 <printf@plt>
lea    0x1f53(%rip),%rdi
call   1030 <printf@plt>
lea    0x1f73(%rip),%rdi
call   1030 <printf@plt>
lea    0x1fb1(%rip),%rdi
call   1030 <printf@plt>
lea    0x2018(%rip),%rdi
call   1030 <printf@plt>
lea    0x2063(%rip),%rdi
call   1030 <printf@plt>
lea    0x2083(%rip),%rdi
call   1030 <printf@plt>
lea    0x20fa(%rip),%rdi
call   1030 <printf@plt>
lea    0x2167(%rip),%rdi
call   1030 <printf@plt>
lea    0x21dc(%rip),%rdi
call   1030 <printf@plt>
lea    0x2250(%rip),%rdi
call   1030 <printf@plt>
lea    0x22b6(%rip),%rdi
call   1030 <printf@plt>
lea    0x2319(%rip),%rdi
call   1030 <printf@plt>
lea    0x2353(%rip),%rdi
call   1030 <printf@plt>
lea    0x23b5(%rip),%rdi
call   1030 <printf@plt>
lea    0x2425(%rip),%rdi
call   1030 <printf@plt>
lea    0x24a5(%rip),%rdi
call   1030 <printf@plt>
lea    0x2519(%rip),%rdi
call   1030 <printf@plt>
lea    0x2552(%rip),%rdi
call   1030 <printf@plt>
lea    0x25c4(%rip),%rdi
call   1030 <printf@plt>
lea    0x2632(%rip),%rdi
call   1030 <printf@plt>
lea    0x265f(%rip),%rdi
call   1030 <printf@plt>
lea    0x26a3(%rip),%rdi
call   1030 <printf@plt>
lea    0x26c0(%rip),%rdi
call   1030 <printf@plt>
lea    0x26c8(%rip),%rdi
call   1030 <printf@plt>
lea    0x2710(%rip),%rdi
call   1030 <printf@plt>
lea    0x2782(%rip),%rdi
call   1030 <printf@plt>
lea    0x27c1(%rip),%rdi
call   1030 <printf@plt>
lea    0x281e(%rip),%rdi
call   1030 <printf@plt>
lea    0x2852(%rip),%rdi
call   1030 <printf@plt>
lea    0x2880(%rip),%rdi
call   1030 <printf@plt>
lea    0x28cd(%rip),%rdi
call   1030 <printf@plt>
lea    0x2912(%rip),%rdi
call   1030 <printf@plt>
lea    0x2956(%rip),%rdi
call   1030 <printf@plt>
lea    0x2984(%rip),%rdi
call   1030 <printf@plt>
lea    0x29f7(%rip),%rdi
call   1030 <printf@plt>
lea    0x2a51(%rip),%rdi
call   1030 <printf@plt>
lea    0x2aaa(%rip),%rdi
call   1030 <printf@plt>
lea    0x2b1a(%rip),%rdi
call   1030 <printf@plt>
lea    0x2b73(%rip),%rdi
call   1030 <printf@plt>
lea    0x2bcf(%rip),%rdi
call   1030 <printf@plt>
lea    0x2c3d(%rip),%rdi
call   1030 <printf@plt>
lea    0x2cae(%rip),%rdi
call   1030 <printf@plt>
lea    0x2d1e(%rip),%rdi
call   1030 <printf@plt>
lea    0x2d62(%rip),%rdi
call   1030 <printf@plt>
lea    0x2dc2(%rip),%rdi
call   1030 <printf@plt>
lea    0x2e2b(%rip),%rdi
call   1030 <printf@plt>
lea    0x2e80(%rip),%rdi
call   1030 <printf@plt>
lea    0x2ee9(%rip),%rdi
call   1030 <printf@plt>
lea    0x2f88(%rip),%rdi
call   1030 <printf@plt>
lea    0x2fc2(%rip),%rdi
call   1030 <printf@plt>
lea    0x2ff6(%rip),%rdi
call   1030 <printf@plt>
lea    0x3051(%rip),%rdi
call   1030 <printf@plt>
lea    0x30ad(%rip),%rdi
call   1030 <printf@plt>
lea    0x30ff(%rip),%rdi
call   1030 <printf@plt>
lea    0x3141(%rip),%rdi
call   1030 <printf@plt>
lea    0x31c2(%rip),%rdi
call   1030 <printf@plt>
lea    0x322f(%rip),%rdi
call   1030 <printf@plt>
lea    0x329d(%rip),%rdi
call   1030 <printf@plt>
lea    0x3317(%rip),%rdi
call   1030 <printf@plt>
lea    0x3368(%rip),%rdi
call   1030 <printf@plt>
lea    0x33e3(%rip),%rdi
call   1030 <printf@plt>
lea    0x3421(%rip),%rdi
call   1030 <printf@plt>
lea    0x347c(%rip),%rdi
call   1030 <printf@plt>
lea    0x34bd(%rip),%rdi
call   1030 <printf@plt>
lea    0x34e2(%rip),%rdi
call   1030 <printf@plt>
lea    0x351a(%rip),%rdi
call   1030 <printf@plt>
lea    0x3552(%rip),%rdi
call   1030 <printf@plt>
lea    0x358a(%rip),%rdi
call   1030 <printf@plt>
lea    0x35ff(%rip),%rdi
call   1030 <printf@plt>
lea    0x366a(%rip),%rdi
call   1030 <printf@plt>
lea    0x36b4(%rip),%rdi
call   1030 <printf@plt>
lea    0x3713(%rip),%rdi
call   1030 <printf@plt>
lea    0x3785(%rip),%rdi
call   1030 <printf@plt>
lea    0x37f3(%rip),%rdi
call   1030 <printf@plt>
lea    0x3857(%rip),%rdi
call   1030 <printf@plt>
lea    0x38b9(%rip),%rdi
call   1030 <printf@plt>
lea    0x38e3(%rip),%rdi
call   1030 <printf@plt>
lea    0x3908(%rip),%rdi
call   1030 <printf@plt>
lea    0x3924(%rip),%rdi
call   1030 <printf@plt>
lea    0x3942(%rip),%rdi
call   1030 <printf@plt>
lea    0x396b(%rip),%rdi
call   1030 <printf@plt>
lea    0x3983(%rip),%rdi
call   1030 <printf@plt>
lea    0x39bc(%rip),%rdi
call   1030 <printf@plt>
lea    0x39d9(%rip),%rdi
call   1030 <printf@plt>
lea    0x39fa(%rip),%rdi
call   1030 <printf@plt>
lea    0x3a20(%rip),%rdi
call   1030 <printf@plt>
lea    0x3a48(%rip),%rdi
call   1030 <printf@plt>
lea    0x3a70(%rip),%rdi
call   1030 <printf@plt>
lea    0x3a99(%rip),%rdi
call   1030 <printf@plt>
lea    0x3ae4(%rip),%rdi
call   1030 <printf@plt>
lea    0x3b20(%rip),%rdi
call   1030 <printf@plt>
lea    0x3b50(%rip),%rdi
call   1030 <printf@plt>
lea    0x3b82(%rip),%rdi
call   1030 <printf@plt>
lea    0x3bbc(%rip),%rdi
call   1030 <printf@plt>
lea    0x3be6(%rip),%rdi
call   1030 <printf@plt>
lea    0x3c2b(%rip),%rdi
call   1030 <printf@plt>
lea    0x3c51(%rip),%rdi
call   1030 <printf@plt>
lea    0x3c6a(%rip),%rdi
call   1030 <printf@plt>
lea    0x3c83(%rip),%rdi
call   1030 <printf@plt>
lea    0x3ca2(%rip),%rdi
call   1030 <printf@plt>
lea    0x3ccf(%rip),%rdi
call   1030 <printf@plt>
lea    0x3d07(%rip),%rdi
call   1030 <printf@plt>
lea    0x3d3f(%rip),%rdi
call   1030 <printf@plt>
lea    0x3d83(%rip),%rdi
call   1030 <printf@plt>
lea    0x3dc0(%rip),%rdi
call   1030 <printf@plt>
lea    0x3dff(%rip),%rdi
call   1030 <printf@plt>
lea    0x3e70(%rip),%rdi
call   1030 <printf@plt>
lea    0x3eda(%rip),%rdi
call   1030 <printf@plt>
lea    0x3f40(%rip),%rdi
call   1030 <printf@plt>
lea    0x3f81(%rip),%rdi
call   1030 <printf@plt>
lea    0x3f93(%rip),%rdi
call   1030 <printf@plt>
lea    0x400a(%rip),%rdi
call   1030 <printf@plt>
lea    0x406d(%rip),%rdi
call   1030 <printf@plt>
lea    0x409e(%rip),%rdi
call   1030 <printf@plt>
lea    0x40d9(%rip),%rdi
call   1030 <printf@plt>
lea    0x4124(%rip),%rdi
call   1030 <printf@plt>
lea    0x416a(%rip),%rdi
call   1030 <printf@plt>
lea    0x41a4(%rip),%rdi
call   1030 <printf@plt>
lea    0x4206(%rip),%rdi
call   1030 <printf@plt>
lea    0x424d(%rip),%rdi
call   1030 <printf@plt>
lea    0x4293(%rip),%rdi
call   1030 <printf@plt>
lea    0x42d9(%rip),%rdi
call   1030 <printf@plt>
lea    0x4318(%rip),%rdi
call   1030 <printf@plt>
lea    0x4324(%rip),%rdi
call   1030 <printf@plt>
lea    0x4361(%rip),%rdi
call   1030 <printf@plt>
lea    0x439d(%rip),%rdi
call   1030 <printf@plt>
lea    0x4409(%rip),%rdi
call   1030 <printf@plt>
lea    0x4477(%rip),%rdi
call   1030 <printf@plt>
lea    0x44df(%rip),%rdi
call   1030 <printf@plt>
lea    0x4554(%rip),%rdi
call   1030 <printf@plt>
lea    0x45b3(%rip),%rdi
call   1030 <printf@plt>
lea    0x460c(%rip),%rdi
call   1030 <printf@plt>
lea    0x460c(%rip),%rdi
call   1030 <printf@plt>
lea    0x4658(%rip),%rdi
call   1030 <printf@plt>
lea    0x4678(%rip),%rdi
call   1030 <printf@plt>
lea    0x46d8(%rip),%rdi
call   1030 <printf@plt>
lea    0x473a(%rip),%rdi
call   1030 <printf@plt>
lea    0x4796(%rip),%rdi
call   1030 <printf@plt>
lea    0x47ca(%rip),%rdi
call   1030 <printf@plt>
lea    0x4808(%rip),%rdi
call   1030 <printf@plt>
lea    0x485e(%rip),%rdi
call   1030 <printf@plt>
lea    0x48aa(%rip),%rdi
call   1030 <printf@plt>
lea    0x48f8(%rip),%rdi
call   1030 <printf@plt>
lea    0x4960(%rip),%rdi
call   1030 <printf@plt>
lea    0x49af(%rip),%rdi
call   1030 <printf@plt>
lea    0x4a0f(%rip),%rdi
call   1030 <printf@plt>
lea    0x4a4c(%rip),%rdi
call   1030 <printf@plt>
lea    0x4a87(%rip),%rdi
call   1030 <printf@plt>
lea    0x4aa8(%rip),%rdi
call   1030 <printf@plt>
lea    0x4ab8(%rip),%rdi
call   1030 <printf@plt>
lea    0x4b12(%rip),%rdi
call   1030 <printf@plt>
lea    0x4b3c(%rip),%rdi
call   1030 <printf@plt>
lea    0x4bcb(%rip),%rdi
call   1030 <printf@plt>
lea    0x4bef(%rip),%rdi
call   1030 <printf@plt>
lea    0x4c41(%rip),%rdi
call   1030 <printf@plt>
lea    0x4c9f(%rip),%rdi
call   1030 <printf@plt>
lea    0x4cf9(%rip),%rdi
call   1030 <printf@plt>
lea    0x4d4f(%rip),%rdi
call   1030 <printf@plt>
lea    0x4da4(%rip),%rdi
call   1030 <printf@plt>
lea    0x4dcd(%rip),%rdi
call   1030 <printf@plt>
lea    0x4ddf(%rip),%rdi
call   1030 <printf@plt>
lea    0x4e2e(%rip),%rdi
call   1030 <printf@plt>
lea    0x4e7d(%rip),%rdi
call   1030 <printf@plt>
lea    0x4ecc(%rip),%rdi
call   1030 <printf@plt>
lea    0x4f1b(%rip),%rdi
call   1030 <printf@plt>
lea    0x4f6a(%rip),%rdi
call   1030 <printf@plt>
lea    0x4f7c(%rip),%rdi
call   1030 <printf@plt>
lea    0x4fc3(%rip),%rdi
call   1030 <printf@plt>
lea    0x4fdf(%rip),%rdi
call   1030 <printf@plt>
lea    0x5006(%rip),%rdi
call   1030 <printf@plt>
pop    %rbp
ret

x86 assembly (clang, -O2):
<mads_info>:
push   %rax
lea    0xee8(%rip),%rdi
call   1030 <puts@plt>
lea    0xf46(%rip),%rdi
call   1030 <puts@plt>
lea    0xfb7(%rip),%rdi
call   1030 <puts@plt>
lea    0x1007(%rip),%rdi
call   1030 <puts@plt>
lea    0x1073(%rip),%rdi
call   1030 <puts@plt>
lea    0x10dd(%rip),%rdi
call   1030 <puts@plt>
lea    0x1143(%rip),%rdi
call   1030 <puts@plt>
lea    0x116e(%rip),%rdi
call   1030 <puts@plt>
lea    0x1199(%rip),%rdi
call   1030 <puts@plt>
lea    0x1209(%rip),%rdi
call   1030 <puts@plt>
lea    0x1269(%rip),%rdi
call   1030 <puts@plt>
lea    0x12ae(%rip),%rdi
call   1030 <puts@plt>
lea    0x12fc(%rip),%rdi
call   1030 <puts@plt>
lea    0x1324(%rip),%rdi
call   1030 <puts@plt>
lea    0x132f(%rip),%rdi
call   1030 <puts@plt>
lea    0x1379(%rip),%rdi
call   1030 <puts@plt>
lea    0x13fb(%rip),%rdi
call   1030 <puts@plt>
lea    0x1450(%rip),%rdi
call   1030 <puts@plt>
lea    0x149d(%rip),%rdi
call   1030 <puts@plt>
lea    0x14be(%rip),%rdi
call   1030 <puts@plt>
lea    0x14e6(%rip),%rdi
call   1030 <puts@plt>
lea    0x1520(%rip),%rdi
call   1030 <puts@plt>
lea    0x1575(%rip),%rdi
call   1030 <puts@plt>
lea    0x15ca(%rip),%rdi
call   1030 <puts@plt>
lea    0x160c(%rip),%rdi
call   1030 <puts@plt>
lea    0x1633(%rip),%rdi
call   1030 <puts@plt>
lea    0x169a(%rip),%rdi
call   1030 <puts@plt>
lea    0x170e(%rip),%rdi
call   1030 <puts@plt>
lea    0x172d(%rip),%rdi
call   1030 <puts@plt>
lea    0x1787(%rip),%rdi
call   1030 <puts@plt>
lea    0x17fb(%rip),%rdi
call   1030 <puts@plt>
lea    0x1874(%rip),%rdi
call   1030 <puts@plt>
lea    0x18fe(%rip),%rdi
call   1030 <puts@plt>
lea    0x1915(%rip),%rdi
call   1030 <puts@plt>
lea    0x1968(%rip),%rdi
call   1030 <puts@plt>
lea    0x19b4(%rip),%rdi
call   1030 <puts@plt>
lea    0x19fb(%rip),%rdi
call   1030 <puts@plt>
lea    0x1a57(%rip),%rdi
call   1030 <puts@plt>
lea    0x1ad1(%rip),%rdi
call   1030 <puts@plt>
lea    0x1ae1(%rip),%rdi
call   1030 <puts@plt>
lea    0x1b4a(%rip),%rdi
call   1030 <puts@plt>
lea    0x1bc1(%rip),%rdi
call   1030 <puts@plt>
lea    0x1c12(%rip),%rdi
call   1030 <puts@plt>
lea    0x1c4f(%rip),%rdi
call   1030 <puts@plt>
lea    0x1c97(%rip),%rdi
call   1030 <puts@plt>
lea    0x1cdc(%rip),%rdi
call   1030 <puts@plt>
lea    0x1d54(%rip),%rdi
call   1030 <puts@plt>
lea    0x1dbc(%rip),%rdi
call   1030 <puts@plt>
lea    0x1e05(%rip),%rdi
call   1030 <puts@plt>
lea    0x1e54(%rip),%rdi
call   1030 <puts@plt>
lea    0x1ebb(%rip),%rdi
call   1030 <puts@plt>
lea    0x1f23(%rip),%rdi
call   1030 <puts@plt>
lea    0x1f42(%rip),%rdi
call   1030 <puts@plt>
lea    0x1f7f(%rip),%rdi
call   1030 <puts@plt>
lea    0x1fe5(%rip),%rdi
call   1030 <puts@plt>
lea    0x202f(%rip),%rdi
call   1030 <puts@plt>
lea    0x204e(%rip),%rdi
call   1030 <puts@plt>
lea    0x20c4(%rip),%rdi
call   1030 <puts@plt>
lea    0x2130(%rip),%rdi
call   1030 <puts@plt>
lea    0x21a4(%rip),%rdi
call   1030 <puts@plt>
lea    0x2217(%rip),%rdi
call   1030 <puts@plt>
lea    0x227c(%rip),%rdi
call   1030 <puts@plt>
lea    0x22de(%rip),%rdi
call   1030 <puts@plt>
lea    0x2317(%rip),%rdi
call   1030 <puts@plt>
lea    0x2378(%rip),%rdi
call   1030 <puts@plt>
lea    0x23e7(%rip),%rdi
call   1030 <puts@plt>
lea    0x2466(%rip),%rdi
call   1030 <puts@plt>
lea    0x24d9(%rip),%rdi
call   1030 <puts@plt>
lea    0x2511(%rip),%rdi
call   1030 <puts@plt>
lea    0x2582(%rip),%rdi
call   1030 <puts@plt>
lea    0x25ef(%rip),%rdi
call   1030 <puts@plt>
lea    0x261b(%rip),%rdi
call   1030 <puts@plt>
lea    0x265e(%rip),%rdi
call   1030 <puts@plt>
lea    0x267a(%rip),%rdi
call   1030 <puts@plt>
lea    0x2681(%rip),%rdi
call   1030 <puts@plt>
lea    0x26c8(%rip),%rdi
call   1030 <puts@plt>
lea    0x2739(%rip),%rdi
call   1030 <puts@plt>
lea    0x2777(%rip),%rdi
call   1030 <puts@plt>
lea    0x27d3(%rip),%rdi
call   1030 <puts@plt>
lea    0x2806(%rip),%rdi
call   1030 <puts@plt>
lea    0x2833(%rip),%rdi
call   1030 <puts@plt>
lea    0x287f(%rip),%rdi
call   1030 <puts@plt>
lea    0x28c3(%rip),%rdi
call   1030 <puts@plt>
lea    0x2906(%rip),%rdi
call   1030 <puts@plt>
lea    0x2933(%rip),%rdi
call   1030 <puts@plt>
lea    0x29a5(%rip),%rdi
call   1030 <puts@plt>
lea    0x29fe(%rip),%rdi
call   1030 <puts@plt>
lea    0x2a56(%rip),%rdi
call   1030 <puts@plt>
lea    0x2ac5(%rip),%rdi
call   1030 <puts@plt>
lea    0x2b1d(%rip),%rdi
call   1030 <puts@plt>
lea    0x2b78(%rip),%rdi
call   1030 <puts@plt>
lea    0x2be5(%rip),%rdi
call   1030 <puts@plt>
lea    0x2c55(%rip),%rdi
call   1030 <puts@plt>
lea    0x2cc4(%rip),%rdi
call   1030 <puts@plt>
lea    0x2d07(%rip),%rdi
call   1030 <puts@plt>
lea    0x2d66(%rip),%rdi
call   1030 <puts@plt>
lea    0x2dce(%rip),%rdi
call   1030 <puts@plt>
lea    0x2e22(%rip),%rdi
call   1030 <puts@plt>
lea    0x2e8a(%rip),%rdi
call   1030 <puts@plt>
lea    0x2f28(%rip),%rdi
call   1030 <puts@plt>
lea    0x2f61(%rip),%rdi
call   1030 <puts@plt>
lea    0x2f94(%rip),%rdi
call   1030 <puts@plt>
lea    0x2fee(%rip),%rdi
call   1030 <puts@plt>
lea    0x3049(%rip),%rdi
call   1030 <puts@plt>
lea    0x309a(%rip),%rdi
call   1030 <puts@plt>
lea    0x30db(%rip),%rdi
call   1030 <puts@plt>
lea    0x315b(%rip),%rdi
call   1030 <puts@plt>
lea    0x31c7(%rip),%rdi
call   1030 <puts@plt>
lea    0x3234(%rip),%rdi
call   1030 <puts@plt>
lea    0x32ad(%rip),%rdi
call   1030 <puts@plt>
lea    0x32fd(%rip),%rdi
call   1030 <puts@plt>
lea    0x3377(%rip),%rdi
call   1030 <puts@plt>
lea    0x33b4(%rip),%rdi
call   1030 <puts@plt>
lea    0x340e(%rip),%rdi
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call   1030 <puts@plt>
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call   1030 <puts@plt>
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call   1030 <puts@plt>
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call   1030 <puts@plt>
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call   1030 <puts@plt>
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call   1030 <puts@plt>
lea    0x39e9(%rip),%rdi
call   1030 <puts@plt>
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call   1030 <puts@plt>
lea    0x3a5b(%rip),%rdi
call   1030 <puts@plt>
lea    0x3a96(%rip),%rdi
call   1030 <puts@plt>
lea    0x3ac5(%rip),%rdi
call   1030 <puts@plt>
lea    0x3af6(%rip),%rdi
call   1030 <puts@plt>
lea    0x3b2f(%rip),%rdi
call   1030 <puts@plt>
lea    0x3b58(%rip),%rdi
call   1030 <puts@plt>
lea    0x3b9c(%rip),%rdi
call   1030 <puts@plt>
lea    0x3bc1(%rip),%rdi
call   1030 <puts@plt>
lea    0x3bd9(%rip),%rdi
call   1030 <puts@plt>
lea    0x3bf1(%rip),%rdi
call   1030 <puts@plt>
lea    0x3c0f(%rip),%rdi
call   1030 <puts@plt>
lea    0x3c3b(%rip),%rdi
call   1030 <puts@plt>
lea    0x3c72(%rip),%rdi
call   1030 <puts@plt>
lea    0x3ca9(%rip),%rdi
call   1030 <puts@plt>
lea    0x3cec(%rip),%rdi
call   1030 <puts@plt>
lea    0x3d28(%rip),%rdi
call   1030 <puts@plt>
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call   1030 <puts@plt>
lea    0x3dd6(%rip),%rdi
call   1030 <puts@plt>
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call   1030 <puts@plt>
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call   1030 <puts@plt>
lea    0x3ee4(%rip),%rdi
call   1030 <puts@plt>
lea    0x3ef5(%rip),%rdi
call   1030 <puts@plt>
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call   1030 <puts@plt>
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call   1030 <puts@plt>
lea    0x3ffd(%rip),%rdi
call   1030 <puts@plt>
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call   1030 <puts@plt>
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call   1030 <puts@plt>
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call   1030 <puts@plt>
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call   1030 <puts@plt>
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call   1030 <puts@plt>
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call   1030 <puts@plt>
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call   1030 <puts@plt>
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call   1030 <puts@plt>
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call   1030 <puts@plt>
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call   1030 <puts@plt>
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call   1030 <puts@plt>
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call   1030 <puts@plt>
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call   1030 <puts@plt>
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call   1030 <puts@plt>
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call   1030 <puts@plt>
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call   1030 <puts@plt>
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call   1030 <puts@plt>
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call   1030 <puts@plt>
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call   1030 <puts@plt>
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call   1030 <puts@plt>
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call   1030 <puts@plt>
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call   1030 <puts@plt>
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call   1030 <puts@plt>
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call   1030 <puts@plt>
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call   1030 <puts@plt>
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call   1030 <puts@plt>
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call   1030 <puts@plt>
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call   1030 <puts@plt>
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call   1030 <puts@plt>
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call   1030 <puts@plt>
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call   1030 <puts@plt>
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call   1030 <puts@plt>
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call   1030 <puts@plt>
lea    0x4cd6(%rip),%rdi
call   1030 <puts@plt>
lea    0x4cfe(%rip),%rdi
call   1030 <puts@plt>
lea    0x4d0f(%rip),%rdi
call   1030 <puts@plt>
lea    0x4d5d(%rip),%rdi
call   1030 <puts@plt>
lea    0x4dab(%rip),%rdi
call   1030 <puts@plt>
lea    0x4df9(%rip),%rdi
call   1030 <puts@plt>
lea    0x4e47(%rip),%rdi
call   1030 <puts@plt>
lea    0x4e95(%rip),%rdi
call   1030 <puts@plt>
lea    0x4ea6(%rip),%rdi
call   1030 <puts@plt>
lea    0x4eec(%rip),%rdi
call   1030 <puts@plt>
lea    0x4f07(%rip),%rdi
call   1030 <puts@plt>
lea    0x4f2d(%rip),%rdi
pop    %rax
jmp    1030 <puts@plt>

LLVM IR (-O0):
@.str = [107 x i8] c"MADS is an open-source code designed as an integrated high-performance computational framework performing\0A\00"
@.str.1 = [126 x i8] c"a wide range of model-based analyses: Sensitivity Analysis (SA), Parameter Estimation (PE), Model Inversion and Calibration,\0A\00"
@.str.2 = [93 x i8] c"Uncertainty Quantification (UQ), Model Selection and Averaging, and Decision Support (DS).\0A\0A\00"
@.str.3 = [121 x i8] c"MADS utilizes adaptive rules and techniques which allows the analyses to be performed with minimum user input. The code\0A\00"
@.str.4 = [119 x i8] c"provides a series of alternative algorithms to perform each type of model analyses. The code allows for coupled model\0A\00"
@.str.5 = [115 x i8] c"parameters and regularization terms that are internally computed based on user-defined mathematical expressions.\0A\0A\00"
@.str.6 = [56 x i8] c"USAGE: mads problem_name [ keywords | options ] OR\0A\00"
@.str.7 = [56 x i8] c" mads MADS_input_file [ keywords | options ] OR\0A\00"
@.str.8 = [125 x i8] c" mads PEST_input_file [ keywords | options ] (MADS is compatible with PEST control, template and instruction files)\0A\0A\00"
@.str.9 = [109 x i8] c" problem_name: name of the solved problem; MADS_input_file named problem_name.mads is expected\0A\00"
@.str.10 = [82 x i8] c" MADS_input_file: problem input file in MADS format (typically *.mads)\0A\00"
@.str.11 = [91 x i8] c" PEST_input_file: problem input file in PEST format (PEST control file; *.pst)\0A\0A\00"
@.str.12 = [53 x i8] c"keywords & options (can be provided in any order):\0A\0A\00"
@.str.13 = [24 x i8] c"problem type keywords:\0A\00"
@.str.14 = [87 x i8] c" check - check model setup and input/output files (no model execution)\0A\00"
@.str.15 = [143 x i8] c" create - create calibration problem based on provided model parameters (single model execution to compute calibration targets)\0A\00"
@.str.16 = [98 x i8] c" forward - forward model run (no calibration); recommended for model setup checking\0A\00"
@.str.17 = [90 x i8] c" calibrate - calibration run [default if no problem type keyword is provided]\0A\00"
@.str.18 = [46 x i8] c" montecarlo - Monte-Carlo analysis\0A\00"
@.str.19 = [53 x i8] c" gsens - global sensitivity analysis\0A\00"
@.str.20 = [71 x i8] c" glue - Generalized Likelihood Uncertainty Estimation\0A\00"
@.str.21 = [98 x i8] c" lsens - local sensitivity analysis (standalone or at the end of the calibration)\0A\00"
@.str.22 = [98 x i8] c" eigen - local eigensystem analysis (standalone or at the end of the calibration)\0A\00"
@.str.23 = [79 x i8] c" abagus - Agent-Based Global Uncertainty & Sensitivity Analysis\0A\00"
@.str.24 = [52 x i8] c" infogap - Info-gap decision analysis\0A\00"
@.str.25 = [116 x i8] c" postpua - predictive uncertainty analysis of sampling results (currently for abagus PSSA files only)\0A\00"
@.str.26 = [129 x i8] c" bayes - Bayesian parameter sampling using DREAM (DiffeRential Evolution Adaptive Metropolis; Vrugt et al. 2009)\0A\00"
@.str.27 = [44 x i8] c"\0Acalibration method keywords (select one):\0A\00"
@.str.28 = [103 x i8] c" single - single calibration using initial guesses provided in the input file [default]\0A\00"
@.str.29 = [129 x i8] c" igrnd - sequential calibrations using a set of random initial values (number of realizations defined by real=X)\0A\00"
@.str.30 = [134 x i8] c" igpd - sequential calibrations using a set of discretized initial values (discretization defined in the input file)\0A\00"
@.str.31 = [151 x i8] c" ppsd - sequential calibrations using partial parameter space discretization (PPSD) method (discretization defined in the input file)\0A\00"
@.str.32 = [36 x i8] c"\0Acalibration termination criteria:\0A\00"
@.str.33 = [96 x i8] c" eval=[integer] - functional evaluations exceed the predefined value [default eval=5000]\0A\00"
@.str.34 = [89 x i8] c" cutoff=[real] - objective function is below the cutoff value [default cutoff=0]\0A\00"
@.str.35 = [84 x i8] c" obsrange - model predictions are within predefined calibration ranges\0A\00"
@.str.36 = [105 x i8] c" obserror=[real] - model predictions are within a predefined absolute error [default obserror=0.1]\0A\00"
@.str.37 = [135 x i8] c" parerror=[real] - model parameters are within a predefined absolute error from their known 'true' values [default parerror=0.1]\0A\00"
@.str.38 = [29 x i8] c"\0Auser-enforced termination:\0A\00"
@.str.39 = [118 x i8] c" problem_name.quit - if file with this name exists in the running directory, MADS terminates as soon as possible.\0A\00"
@.str.40 = [132 x i8] c" problem_name.stop - if file with this name exists in the running directory, MADS terminates after saving intermediate results.\0A\00"
@.str.41 = [94 x i8] c"\0Aoptimization method (opt=[string]; various combinations are possible, e.g. pso_std_lm_gsl):\0A\00"
@.str.42 = [74 x i8] c" opt=lm - Local Levenberg-Marquardt optimization [default]\0A\00"
@.str.43 = [85 x i8] c" opt=lm_levmar - Local Levenberg-Marquardt optimization using LEVMAR library\0A\00"
@.str.44 = [82 x i8] c" opt=lm_gsl - Local Levenberg-Marquardt optimization using GSL library\0A\00"
@.str.45 = [133 x i8] c" opt=lm_ms - Local Multi-Start (Multi-Try) Levenberg-Marquardt (MSLM) optimization using multiple random initial guesses\0A\00"
@.str.46 = [117 x i8] c" opt=pso - Global Particle Swarm optimization (default Standard2006; http://clerc.maurice.free.fr/pso)\0A\00"
@.str.47 = [86 x i8] c" opt=apso - Global Adaptive Particle Swarm optimization (default TRIBES)\0A\00"
@.str.48 = [92 x i8] c" opt=swarm - Global Particle Swarm optimization Standard2006 (also opt=pso_std)\0A\00"
@.str.49 = [116 x i8] c" opt=tribes - Global Particle Swarm optimization TRIBES-D (Clerc 2004; http://clerc.maurice.free.fr/pso)\0A\00"
@.str.50 = [117 x i8] c" opt=squads - SQUADS: Adaptive hybrid optimization using coupled local and global optimization techniques\0A\00"
@.str.51 = [44 x i8] c"\0Ageneral calibration/optimization options:\0A\00"
@.str.52 = [74 x i8] c" retry=[integer] - number of optimization retries [default retry=0]\0A\00"
@.str.53 = [115 x i8] c" particles=[integer]- number of initial particles or tribes [default particles=10+2*sqrt(Number_of_parameters)]\0A\00"
@.str.54 = [87 x i8] c" lmeigen|eigen - eigen analysis of the intermediate / final optimized solution\0A\00"
@.str.55 = [44 x i8] c"\0ALevenberg-Marquardt optimization options:\0A\00"
@.str.56 = [131 x i8] c" lmfactor=[double] - multiplier applied to compute when to initiate LM searches within SQUADS algorithm [default lmfactor=1.0]\0A\00"
@.str.57 = [121 x i8] c" lmindirect - Indirect computation of LM alpha coefficient [default DIRECT/Delayed gratification computation]\0A\00"
@.str.58 = [129 x i8] c" lmmu=[double] - LM alpha multiplier for direct computation of LM alpha coefficient when OF decreases [default lmmu=0.1]\0A\00"
@.str.59 = [128 x i8] c" lmnu=[integer] - LM alpha multiplier for direct computation of LM alpha coefficient when OF increases [default lmnu=10]\0A\00"
@.str.60 = [114 x i8] c" lmaccel - LM geodesic acceleration as proposed by Transtrum et al (2011) [default NO acceleration]\0A\00"
@.str.61 = [111 x i8] c" lmratio=[double] - LM acceleration velocity ratio for recomputing the Jacobian [default lmratio=(3/4)^2]\0A\00"
@.str.62 = [70 x i8] c" lmh=[double] - LM acceleration multiplier [default lmh=0.1]\0A\00"
@.str.63 = [110 x i8] c" lmiter=[integer] - number of LM iterations [default computed internally based on number of evaluations]\0A\00"
@.str.64 = [124 x i8] c" lmnlam=[integer] - Maximum number of linear solves (lambda searches) after each Jacobian estimate [default lmnlam=10]\0A\00"
@.str.65 = [140 x i8] c" lmnlamof=[integer] - Number of acceptable linear solves (lambda searches) with similar OF's during LM optimization [default lmnlamof=3]\0A\00"
@.str.66 = [128 x i8] c" lmnjacof=[integer] - Number of acceptable jacobian iterations with similar OF's during LM optimization [default lmnjacof=5]\0A\00"
@.str.67 = [69 x i8] c" lmerror=[double] - LM convergence error [default lmerror=1e-5]\0A\00"
@.str.68 = [126 x i8] c"\0Asampling method (smp=[string] OR mslm=[string] for Multi-Start Levenberg-Marquardt (MSLM) analysis using multiple retries):\0A\00"
@.str.69 = [122 x i8] c" smp=olhs - Optimal Latin Hyper Cube sampling [default] (if real=1 RANDOM; if real>1 IDLHS; if real>500 LHS)\0A\00"
@.str.70 = [57 x i8] c" smp=lhs - Latin Hyper Cube sampling (LHS)\0A\00"
@.str.71 = [80 x i8] c" smp=idlhs - Improved Distributed Latin Hyper Cube sampling (IDLHS)\0A\00"
@.str.72 = [41 x i8] c" smp=random - Random sampling\0A\00"
@.str.73 = [20 x i8] c"\0Asampling options:\0A\00"
@.str.74 = [84 x i8] c" real=[integer] - number of random realizations / samples [default real=100]\0A\00"
@.str.75 = [126 x i8] c" case=[integer] - execute a single case from all the realizations / samples (applied in PPSD, IGDP, IGRND, MONTECARLO)\0A\00"
@.str.76 = [75 x i8] c" seed=[integer] - random seed value [randomly generated by default]\0A\00"
@.str.77 = [105 x i8] c"\0Aobjective function functional form options (select one; regularizaiton terms can be added separately):\0A\00"
@.str.78 = [64 x i8] c" ssr - sum of the squared residuals [default]\0A\00"
@.str.79 = [58 x i8] c" ssd0 - sum of the squared discrepancies\0A\00"
@.str.80 = [89 x i8] c" ssdx - sum of the squared discrepancies increased to get in the bounds\0A\00"
@.str.81 = [81 x i8] c" ssda - sum of the squared discrepancies and absolute residuals\0A\00"
@.str.82 = [80 x i8] c" ssdr - sum of the squared discrepancies and squared residuals\0A\00"
@.str.83 = [58 x i8] c"\0Atransformation of parameter and observation properties:\0A\00"
@.str.84 = [127 x i8] c" nosin - Sin transformation of optimized parameters is not applied [parameters are sin transformed by default]\0A\00"
@.str.85 = [102 x i8] c" sindx - Parameter space step for numerical derivatives of sin transformed parameters\0A\00"
@.str.86 = [101 x i8] c" [default sindx=1e-7 for internal problems; sindx=0.1 for external problems]\0A\00"
@.str.87 = [124 x i8] c" lindx - Parameter space step for numerical derivatives of not transformed parameters [default lindx=0.001]\0A\00"
@.str.88 = [101 x i8] c" pardx - Parameter space step for parameter space discretization [default pardx=0.1]\0A\00"
@.str.89 = [104 x i8] c" plog=[-1,0,1] - Log transformation of all optimized parameters is enforced (1) or disabled (0)\0A\00"
@.str.90 = [122 x i8] c" [default plog=-1; log transformation is explicitly defined for each parameter in the input file]\0A\00"
@.str.91 = [125 x i8] c" olog=[-1,0,1] - Log transformation of all the observations (simulated and measured) is enforced (1) or disabled (0)\0A\00"
@.str.92 = [124 x i8] c" [default olog=-1; log transformation is explicitly defined for each observation in the input file]\0A\00"
@.str.93 = [80 x i8] c" oweight=[-1,0,1,2] - Weights for all the observation residuals are defined:\0A\00"
@.str.94 = [108 x i8] c" 0 = zero weight, 1 = unit weight, 2 = weight reversely proportional to observation\0A\00"
@.str.95 = [117 x i8] c" [default oweight=-1; weights for each observation are explicitly defined in the input file]\0A\00"
@.str.96 = [97 x i8] c" obsdomain=[float] - observation space domain size [default provided in the MADS input file]\0A\00"
@.str.97 = [117 x i8] c" obsstep=[float] - observation space domain step to explore info-gap observation uncertainty [default ignored]\0A\00"
@.str.98 = [171 x i8] c"\0Aparallelization (available parallelization resources are internally detected by default; supported: Slurm, Moab, BProc, LSB, PBS, Beowulf, OpenMPI, OpenMP, POSIX, ...):\0A\00"
@.str.99 = [70 x i8] c" np=[integer] - Number of requested parallel jobs [optional]\0A\00"
@.str.100 = [64 x i8] c" mpi - Use OpenMPI parallelization [optional]\0A\00"
@.str.101 = [103 x i8] c" posix[=integer] - POSIX parallel threading [optional]; number of threads can be defined as well\0A\00"
@.str.102 = [104 x i8] c" omp[=integer] - OpenMP parallel threading [optional]; number of threads can be defined as well\0A\00"
@.str.103 = [94 x i8] c" ssh - Forces the use of ssh to execute external jobs at the comptuer nodes\0A\00"
@.str.104 = [78 x i8] c" ppt=[integer] - Number of processors per an external task [optional]\0A\00"
@.str.105 = [141 x i8] c" nplambda=[integer] - Number of requested parallel lambda runs in the case of Levenberg-Marquardt optimization [optional; nplambda <= np]\0A\00"
@.str.106 = [121 x i8] c" rstfile=[string] - name of existing ZIP restart file to be used (created by previous Parallel MADS run) [optional]\0A\00"
@.str.107 = [122 x i8] c" rstdir=[string] - name of existing restart directory to be used (created by previous Parallel MADS run) [optional]\0A\00"
@.str.108 = [134 x i8] c" restart=[integer] - restart=1 (default; automatic restart if possible); restart=0 (force no restart); restart=-1 (force restart)\0A\00"
@.str.109 = [93 x i8] c" by default the analyses will be restarted automatically (restart=1)\0A\00"
@.str.110 = [135 x i8] c" bin_restart - restart information is stored in binary files (by default, model outputs are added in a zip file for restart)\0A\00"
@.str.111 = [74 x i8] c"\0AABAGUS (Agent-Based Global Uncertainty & Sensitivity Analysis) options:\0A\00"
@.str.112 = [103 x i8] c" infile=[string] - name of previous results file to be used to initialize Kd-tree [default=NULL]\0A\00"
@.str.113 = [77 x i8] c" energy=[integer] - initial energy for particles [default energy=10000]\0A\00"
@.str.114 = [49 x i8] c"\0Aoptions for the build-in analytical solutions:\0A\00"
@.str.115 = [68 x i8] c" point - point contaminant source in 3D flow domain\0A\00"
@.str.116 = [68 x i8] c" plane - plane contaminant source in 3D flow domain\0A\00"
@.str.117 = [68 x i8] c" box - brick contaminant source in 3D flow domain\0A\00"
@.str.118 = [129 x i8] c" obs_int=[1,2] - concentration integration along observation well screens (1 - mid point; 2 - two end points [default=1]\0A\00"
@.str.119 = [119 x i8] c" disp_tied - lateral and vertical transverse dispersivities are fractions of the longitudinal dispersivity\0A\00"
@.str.120 = [86 x i8] c" disp_scaled - longitudinal dispersivity is scaled with the travel distance\0A\00"
@.str.121 = [107 x i8] c" if disp_scaled and disp_tied are applied, longitudinal dispersivity is scaled and\0A\00"
@.str.122 = [126 x i8] c" lateral and vertical transverse dispersivities are fractions of the scaled longitudinal dispersivity\0A\00"
@.str.123 = [122 x i8] c" disp_scaled=2 - longitudinal, lateral and vertical transverse dispersivities are scaled with the travel distance\0A\00"
@.str.124 = [112 x i8] c" time_step - parameter \22end time\22 is representing the period (dt) within which the source is active\0A\00"
@.str.125 = [110 x i8] c"\0Abuild-in test problems for optimization / uncertainty-quantification techniques (local and global methods):\0A\00"
@.str.126 = [54 x i8] c" test=[integer] - test problem ID [default=1]:\0A\00"
@.str.127 = [49 x i8] c" 1: Parabola (Sphere)\0A\00"
@.str.128 = [40 x i8] c" 2: Griewank\0A\00"
@.str.129 = [42 x i8] c" 3: Rosenbrock\0A\00"
@.str.130 = [53 x i8] c" 4: De Jong's Function\0A\00"
@.str.131 = [36 x i8] c" 5: Step\0A\00"
@.str.132 = [69 x i8] c" 6: Alpine function (Clerc's Function)\0A\00"
@.str.133 = [41 x i8] c" 7: Rastrigin\0A\00"
@.str.134 = [45 x i8] c" 8: Krishna Kumar\0A\00"
@.str.135 = [50 x i8] c" 9: Tripod function 2D\0A\00"
@.str.136 = [52 x i8] c" 10: Shekel's Foxholes 2D\0A\00"
@.str.137 = [52 x i8] c" 11: Shekel's Foxholes 5D\0A\00"
@.str.138 = [53 x i8] c" 12: Shekel's Foxholes 10D\0A\00"
@.str.139 = [87 x i8] c" 20: Shekel's Foxholes 2D (alternative; global methods only)\0A\00"
@.str.140 = [72 x i8] c" 21: Polynomial fitting (global methods only)\0A\00"
@.str.141 = [60 x i8] c" 22: Ackley (global methods only)\0A\00"
@.str.142 = [62 x i8] c" 23: Eason 2D (global methods only)\0A\00"
@.str.143 = [70 x i8] c" 31: Rosenbrock (2D simplified alternative)\0A\00"
@.str.144 = [54 x i8] c" 32: Griewank (alternative)\0A\00"
@.str.145 = [81 x i8] c" 33: Rosenbrock (alternative with d*(d-1) observations\0A\00"
@.str.146 = [50 x i8] c" 34: Powell's Quadratic\0A\00"
@.str.147 = [37 x i8] c" 35: Booth\0A\00"
@.str.148 = [37 x i8] c" 36: Beale\0A\00"
@.str.149 = [43 x i8] c" 37: Parsopoulos\0A\00"
@.str.150 = [57 x i8] c" Curve-fitting test functions:\0A\00"
@.str.151 = [68 x i8] c" 40: Sin/Cos test function (2 parameters)\0A\00"
@.str.152 = [68 x i8] c" 41: Sin/Cos test function (4 parameters)\0A\00"
@.str.153 = [80 x i8] c" 42: Sin/Cos test function (2 parameters; simplified)\0A\00"
@.str.154 = [73 x i8] c" 43: Exponential Data Fitting I (5 parameters)\0A\00"
@.str.155 = [75 x i8] c" 44: Exponential Data Fitting II (11 parameters)\0A\00"
@.str.156 = [125 x i8] c" dim=[integer] - dimensionality of parameter space for the test problem (fixed for some of the problems) [default=2]\0A\00"
@.str.157 = [118 x i8] c" npar=[integer] - number of model parameters for the test problem (fixed for some of the problems) [default=2]\0A\00"
@.str.158 = [114 x i8] c" nobs=[integer] - number of observations for the test problem (fixed for some of the problems) [default=2]\0A\00"
@.str.159 = [77 x i8] c" pardomain=[float] - parameter space domain size [default pardomain=100]\0A\00"
@.str.160 = [30 x i8] c"\0Adebugging / verbose levels:\0A\00"
@.str.161 = [131 x i8] c" force | f - enforce running even if a file *.running exists (the file *.running is to prevent overlapping executions)\0A\00"
@.str.162 = [111 x i8] c" quiet | q - no screen output (all the screen output is saved in a file with extension mads_output\0A\00"
@.str.163 = [61 x i8] c" debug=[0-5] - general debugging [default debug=0]\0A\00"
@.str.164 = [71 x i8] c" fdebug=[0-5] - model evaluation debugging [default fdebug=0]\0A\00"
@.str.165 = [87 x i8] c" ldebug=[0-3] - Levenberg-Marquardt optimization debugging [default ldebug=0]\0A\00"
@.str.166 = [82 x i8] c" pdebug=[0-3] - Particle Swarm optimization debugging [default pdebug=0]\0A\00"
@.str.167 = [70 x i8] c" mdebug=[0-3] - Random sampling debugging [default mdebug=0]\0A\00"
@.str.168 = [110 x i8] c" odebug=[0-1] - Record objective function progress in a file with extension 'ofe' [default odebug=0]\0A\00"
@.str.169 = [83 x i8] c" tdebug=[0-1] - Output process times for various tasks [default tdebug=0]\0A\00"
@.str.170 = [82 x i8] c" tpldebug=[0-3] - Debug the writing of external files [default tpldebug=0]\0A\00"
@.str.171 = [82 x i8] c" insdebug=[0-3] - Debug the reading of external files [default insdebug=0]\0A\00"
@.str.172 = [75 x i8] c" pardebug=[0-3] - Debug the parallel execution [default pardebug=0]\0A\00"
@.str.173 = [24 x i8] c"\0Apre-/post-processing:\0A\00"
@.str.174 = [73 x i8] c" yaml - Reads/writes/converts MADS files in YAML format\0A\00"
@.str.175 = [72 x i8] c" xml - Reads/writes/converts MADS files in XML format\0A\00"
@.str.176 = [120 x i8] c" resultsfile=[file] - Post process results saved in a previously generated resultsfile (e.g. using 'igrnd' analysis)\0A\00"
@.str.177 = [122 x i8] c" resultscase=[int] - Post process specific case saved in resultsfile (if resultscase<0, first abs(resultscase) cases)\0A\00"
@.str.178 = [116 x i8] c" cutoff=[real] - Post process all cases saved in resultsfile with objective function below the cutoff value\0A\00"
@.str.179 = [129 x i8] c" obsrange - Post process all cases saved in resultsfile with model predictions within predefined calibration ranges\0A\00"
@.str.180 = [107 x i8] c" pargen - Generate MADS input files for independent multi-processor runs [default pargen=0]\0A\00"
@.str.181 = [101 x i8] c" save - Save MADS input/output files for successful parameter sets [default save=0]\0A\00"
@.str.182 = [12 x i8] c"\0AExamples:\0A\00"
@.str.183 = [88 x i8] c" mads a01 test=2 opt=lm eigen igrnd real=1 (no input files are needed for execution)\0A\00"
@.str.184 = [44 x i8] c" mads a01 test=2 opt=squads igrnd real=1\0A\00"
@.str.185 = [108 x i8] c" mads a01 test=2 abagus cutoff=0.1 eval=100000 (collect solutions of Griewank function below phi cutoff)\0A\00"
@.str.186 = [110 x i8] c" mads a01 test=3 abagus cutoff=20 eval=100000 (collect solutions of Rosenbrock function below phi cutoff)\0A\00"
@.str.187 = [104 x i8] c" mads examples/contamination/s01 ldebug lmeigen (file s01.mads is located in examples/contamination)\0A\00"
@.str.188 = [64 x i8] c" mads examples/contamination/s01 ldebug lmeigen igrnd real=1\0A\00"
@.str.189 = [74 x i8] c" mads examples/contamination/s01 seed=1549170842 obsrange igrnd real=1\0A\00"
@.str.190 = [98 x i8] c" mads examples/contamination/s01 opt=squads seed=1549170842 eigen obsrange pdebug igrnd real=1\0A\00"
@.str.191 = [88 x i8] c" mads examples/contamination/s01 opt=pso seed=1549170842 eigen obsrange igrnd real=1\0A\00"
@.str.192 = [90 x i8] c" mads examples/contamination/s01-flagged ppsd (Partial Parameter Space Discretization)\0A\00"
@.str.193 = [116 x i8] c" mads examples/contamination/s01-flagged igpd (Initial Guesses based on Discreetly distributed model parameters)\0A\00"
@.str.194 = [91 x i8] c" mads examples/contamination/s01 igrnd real=10 (Random Initial Guesses; all parameters)\0A\00"
@.str.195 = [108 x i8] c" mads examples/contamination/s01-flagged igrnd real=10 (Random Initial Guesses; only flagged parameters)\0A\00"
@.str.196 = [73 x i8] c" mads examples/contamination/s01 monte real=10 (Monte Carlo Analysis)\0A\00"
@.str.197 = [71 x i8] c" cd examples/wells; mads w01.mads igrnd real=1 seed=501228648 eigen\0A\00"
@.str.198 = [45 x i8] c"\0AParallel Levenberg-Marquardt optimization:\0A\00"
@.str.199 = [28 x i8] c" cd examples/wells-short\0A\00"
@.str.200 = [102 x i8] c" mads w01parallel.mads restart=0 np=2 ldebug pardebug=2 (Parallel optimization using 2 processors)\0A\00"
@.str.201 = [54 x i8] c" mads w01parallel.mads restart=0 np=11 nplambda=11\0A\00"
@.str.202 = [155 x i8] c" mads w01parallel.mads restart=0 np=3 nplambda=3 lmnlam=21 lmnlamof=12 (if a small number of processors is used, lmnlam & lmnlamof should be increased)\0A\00"
@.str.203 = [48 x i8] c"\0AComparisons between local and global methods:\0A\00"
@.str.204 = [94 x i8] c" mads a01 test=3 opt=lm igrnd real=1000 cutoff=1e-3 (Levenberg-Marquardt optimization)\0A\00"
@.str.205 = [106 x i8] c" mads a01 test=3 opt=lm_ms igrnd real=1000 cutoff=1e-3 (Multi-Start Levenberg-Marquardt optimization)\0A\00"
@.str.206 = [102 x i8] c" mads a01 test=3 opt=swarm igrnd real=1000 cutoff=1e-3 (Particle Swarm optimization Standard2006)\0A\00"
@.str.207 = [98 x i8] c" mads a01 test=3 opt=tribes igrnd real=1000 cutoff=1e-3 (Particle Swarm optimization TRIBES-D)\0A\00"
@.str.208 = [97 x i8] c" mads a01 test=3 opt=squads igrnd real=1000 cutoff=1e-3 (Adaptive hybrid optimization Squads)\0A\00"
@.str.209 = [53 x i8] c"\0AComparisons with PEST (http://www.sspa.com/pest/):\0A\00"
@.str.210 = [30 x i8] c" cd examples/contamination\0A\00"
@.str.211 = [91 x i8] c" mads s02 lmeigen (file s02.mads is located in examples/contamination)\0A\00"
@.str.212 = [91 x i8] c" pest s02pest (file s02pest.pst is located in examples/contamination)\0A\00"
@.str.213 = [91 x i8] c" mads w01 lmeigen (files associated with problem w01 are located in examples/wells)\0A\00"
@.str.214 = [91 x i8] c" pest w01pest (files associated with problem w01pest are located in examples/wells)\0A\00"
@.str.215 = [91 x i8] c" pest w02pest (files associated with problem w02pest are located in examples/wells)\0A\00"
@.str.216 = [30 x i8] c"\0AFor additional information:\0A\00"
@.str.217 = [83 x i8] c" web: http://mads.lanl.gov -:- http://www.ees.lanl.gov/staff/monty/codes/mads\0A\00"
@.str.218 = [40 x i8] c" repo: http://gitlab.com/monty/mads\0A\00"
@.str.219 = [51 x i8] c" git: git clone git@gitlab.com:monty/mads.git\0A\00"
@.str.220 = [86 x i8] c" email: Velimir V Vesselinov (monty) vvv@lanl.gov -:- velimir.vesselinov@gmail.com\0A\00"
define void @mads_info() {
%1 = call i32 @printf(i8* getelementptr inbounds ([107 x i8], [107 x i8]* @.str, i64 0, i64 0))
%2 = call i32 @printf(i8* getelementptr inbounds ([126 x i8], [126 x i8]* @.str.1, i64 0, i64 0))
%3 = call i32 @printf(i8* getelementptr inbounds ([93 x i8], [93 x i8]* @.str.2, i64 0, i64 0))
%4 = call i32 @printf(i8* getelementptr inbounds ([121 x i8], [121 x i8]* @.str.3, i64 0, i64 0))
%5 = call i32 @printf(i8* getelementptr inbounds ([119 x i8], [119 x i8]* @.str.4, i64 0, i64 0))
%6 = call i32 @printf(i8* getelementptr inbounds ([115 x i8], [115 x i8]* @.str.5, i64 0, i64 0))
%7 = call i32 @printf(i8* getelementptr inbounds ([56 x i8], [56 x i8]* @.str.6, i64 0, i64 0))
%8 = call i32 @printf(i8* getelementptr inbounds ([56 x i8], [56 x i8]* @.str.7, i64 0, i64 0))
%9 = call i32 @printf(i8* getelementptr inbounds ([125 x i8], [125 x i8]* @.str.8, i64 0, i64 0))
%10 = call i32 @printf(i8* getelementptr inbounds ([109 x i8], [109 x i8]* @.str.9, i64 0, i64 0))
%11 = call i32 @printf(i8* getelementptr inbounds ([82 x i8], [82 x i8]* @.str.10, i64 0, i64 0))
%12 = call i32 @printf(i8* getelementptr inbounds ([91 x i8], [91 x i8]* @.str.11, i64 0, i64 0))
%13 = call i32 @printf(i8* getelementptr inbounds ([53 x i8], [53 x i8]* @.str.12, i64 0, i64 0))
%14 = call i32 @printf(i8* getelementptr inbounds ([24 x i8], [24 x i8]* @.str.13, i64 0, i64 0))
%15 = call i32 @printf(i8* getelementptr inbounds ([87 x i8], [87 x i8]* @.str.14, i64 0, i64 0))
%16 = call i32 @printf(i8* getelementptr inbounds ([143 x i8], [143 x i8]* @.str.15, i64 0, i64 0))
%17 = call i32 @printf(i8* getelementptr inbounds ([98 x i8], [98 x i8]* @.str.16, i64 0, i64 0))
%18 = call i32 @printf(i8* getelementptr inbounds ([90 x i8], [90 x i8]* @.str.17, i64 0, i64 0))
%19 = call i32 @printf(i8* getelementptr inbounds ([46 x i8], [46 x i8]* @.str.18, i64 0, i64 0))
%20 = call i32 @printf(i8* getelementptr inbounds ([53 x i8], [53 x i8]* @.str.19, i64 0, i64 0))
%21 = call i32 @printf(i8* getelementptr inbounds ([71 x i8], [71 x i8]* @.str.20, i64 0, i64 0))
%22 = call i32 @printf(i8* getelementptr inbounds ([98 x i8], [98 x i8]* @.str.21, i64 0, i64 0))
%23 = call i32 @printf(i8* getelementptr inbounds ([98 x i8], [98 x i8]* @.str.22, i64 0, i64 0))
%24 = call i32 @printf(i8* getelementptr inbounds ([79 x i8], [79 x i8]* @.str.23, i64 0, i64 0))
%25 = call i32 @printf(i8* getelementptr inbounds ([52 x i8], [52 x i8]* @.str.24, i64 0, i64 0))
%26 = call i32 @printf(i8* getelementptr inbounds ([116 x i8], [116 x i8]* @.str.25, i64 0, i64 0))
%27 = call i32 @printf(i8* getelementptr inbounds ([129 x i8], [129 x i8]* @.str.26, i64 0, i64 0))
%28 = call i32 @printf(i8* getelementptr inbounds ([44 x i8], [44 x i8]* @.str.27, i64 0, i64 0))
%29 = call i32 @printf(i8* getelementptr inbounds ([103 x i8], [103 x i8]* @.str.28, i64 0, i64 0))
%30 = call i32 @printf(i8* getelementptr inbounds ([129 x i8], [129 x i8]* @.str.29, i64 0, i64 0))
%31 = call i32 @printf(i8* getelementptr inbounds ([134 x i8], [134 x i8]* @.str.30, i64 0, i64 0))
%32 = call i32 @printf(i8* getelementptr inbounds ([151 x i8], [151 x i8]* @.str.31, i64 0, i64 0))
%33 = call i32 @printf(i8* getelementptr inbounds ([36 x i8], [36 x i8]* @.str.32, i64 0, i64 0))
%34 = call i32 @printf(i8* getelementptr inbounds ([96 x i8], [96 x i8]* @.str.33, i64 0, i64 0))
%35 = call i32 @printf(i8* getelementptr inbounds ([89 x i8], [89 x i8]* @.str.34, i64 0, i64 0))
%36 = call i32 @printf(i8* getelementptr inbounds ([84 x i8], [84 x i8]* @.str.35, i64 0, i64 0))
%37 = call i32 @printf(i8* getelementptr inbounds ([105 x i8], [105 x i8]* @.str.36, i64 0, i64 0))
%38 = call i32 @printf(i8* getelementptr inbounds ([135 x i8], [135 x i8]* @.str.37, i64 0, i64 0))
%39 = call i32 @printf(i8* getelementptr inbounds ([29 x i8], [29 x i8]* @.str.38, i64 0, i64 0))
%40 = call i32 @printf(i8* getelementptr inbounds ([118 x i8], [118 x i8]* @.str.39, i64 0, i64 0))
%41 = call i32 @printf(i8* getelementptr inbounds ([132 x i8], [132 x i8]* @.str.40, i64 0, i64 0))
%42 = call i32 @printf(i8* getelementptr inbounds ([94 x i8], [94 x i8]* @.str.41, i64 0, i64 0))
%43 = call i32 @printf(i8* getelementptr inbounds ([74 x i8], [74 x i8]* @.str.42, i64 0, i64 0))
%44 = call i32 @printf(i8* getelementptr inbounds ([85 x i8], [85 x i8]* @.str.43, i64 0, i64 0))
%45 = call i32 @printf(i8* getelementptr inbounds ([82 x i8], [82 x i8]* @.str.44, i64 0, i64 0))
%46 = call i32 @printf(i8* getelementptr inbounds ([133 x i8], [133 x i8]* @.str.45, i64 0, i64 0))
%47 = call i32 @printf(i8* getelementptr inbounds ([117 x i8], [117 x i8]* @.str.46, i64 0, i64 0))
%48 = call i32 @printf(i8* getelementptr inbounds ([86 x i8], [86 x i8]* @.str.47, i64 0, i64 0))
%49 = call i32 @printf(i8* getelementptr inbounds ([92 x i8], [92 x i8]* @.str.48, i64 0, i64 0))
%50 = call i32 @printf(i8* getelementptr inbounds ([116 x i8], [116 x i8]* @.str.49, i64 0, i64 0))
%51 = call i32 @printf(i8* getelementptr inbounds ([117 x i8], [117 x i8]* @.str.50, i64 0, i64 0))
%52 = call i32 @printf(i8* getelementptr inbounds ([44 x i8], [44 x i8]* @.str.51, i64 0, i64 0))
%53 = call i32 @printf(i8* getelementptr inbounds ([74 x i8], [74 x i8]* @.str.52, i64 0, i64 0))
%54 = call i32 @printf(i8* getelementptr inbounds ([115 x i8], [115 x i8]* @.str.53, i64 0, i64 0))
%55 = call i32 @printf(i8* getelementptr inbounds ([87 x i8], [87 x i8]* @.str.54, i64 0, i64 0))
%56 = call i32 @printf(i8* getelementptr inbounds ([44 x i8], [44 x i8]* @.str.55, i64 0, i64 0))
%57 = call i32 @printf(i8* getelementptr inbounds ([131 x i8], [131 x i8]* @.str.56, i64 0, i64 0))
%58 = call i32 @printf(i8* getelementptr inbounds ([121 x i8], [121 x i8]* @.str.57, i64 0, i64 0))
%59 = call i32 @printf(i8* getelementptr inbounds ([129 x i8], [129 x i8]* @.str.58, i64 0, i64 0))
%60 = call i32 @printf(i8* getelementptr inbounds ([128 x i8], [128 x i8]* @.str.59, i64 0, i64 0))
%61 = call i32 @printf(i8* getelementptr inbounds ([114 x i8], [114 x i8]* @.str.60, i64 0, i64 0))
%62 = call i32 @printf(i8* getelementptr inbounds ([111 x i8], [111 x i8]* @.str.61, i64 0, i64 0))
%63 = call i32 @printf(i8* getelementptr inbounds ([70 x i8], [70 x i8]* @.str.62, i64 0, i64 0))
%64 = call i32 @printf(i8* getelementptr inbounds ([110 x i8], [110 x i8]* @.str.63, i64 0, i64 0))
%65 = call i32 @printf(i8* getelementptr inbounds ([124 x i8], [124 x i8]* @.str.64, i64 0, i64 0))
%66 = call i32 @printf(i8* getelementptr inbounds ([140 x i8], [140 x i8]* @.str.65, i64 0, i64 0))
%67 = call i32 @printf(i8* getelementptr inbounds ([128 x i8], [128 x i8]* @.str.66, i64 0, i64 0))
%68 = call i32 @printf(i8* getelementptr inbounds ([69 x i8], [69 x i8]* @.str.67, i64 0, i64 0))
%69 = call i32 @printf(i8* getelementptr inbounds ([126 x i8], [126 x i8]* @.str.68, i64 0, i64 0))
%70 = call i32 @printf(i8* getelementptr inbounds ([122 x i8], [122 x i8]* @.str.69, i64 0, i64 0))
%71 = call i32 @printf(i8* getelementptr inbounds ([57 x i8], [57 x i8]* @.str.70, i64 0, i64 0))
%72 = call i32 @printf(i8* getelementptr inbounds ([80 x i8], [80 x i8]* @.str.71, i64 0, i64 0))
%73 = call i32 @printf(i8* getelementptr inbounds ([41 x i8], [41 x i8]* @.str.72, i64 0, i64 0))
%74 = call i32 @printf(i8* getelementptr inbounds ([20 x i8], [20 x i8]* @.str.73, i64 0, i64 0))
%75 = call i32 @printf(i8* getelementptr inbounds ([84 x i8], [84 x i8]* @.str.74, i64 0, i64 0))
%76 = call i32 @printf(i8* getelementptr inbounds ([126 x i8], [126 x i8]* @.str.75, i64 0, i64 0))
%77 = call i32 @printf(i8* getelementptr inbounds ([75 x i8], [75 x i8]* @.str.76, i64 0, i64 0))
%78 = call i32 @printf(i8* getelementptr inbounds ([105 x i8], [105 x i8]* @.str.77, i64 0, i64 0))
%79 = call i32 @printf(i8* getelementptr inbounds ([64 x i8], [64 x i8]* @.str.78, i64 0, i64 0))
%80 = call i32 @printf(i8* getelementptr inbounds ([58 x i8], [58 x i8]* @.str.79, i64 0, i64 0))
%81 = call i32 @printf(i8* getelementptr inbounds ([89 x i8], [89 x i8]* @.str.80, i64 0, i64 0))
%82 = call i32 @printf(i8* getelementptr inbounds ([81 x i8], [81 x i8]* @.str.81, i64 0, i64 0))
%83 = call i32 @printf(i8* getelementptr inbounds ([80 x i8], [80 x i8]* @.str.82, i64 0, i64 0))
%84 = call i32 @printf(i8* getelementptr inbounds ([58 x i8], [58 x i8]* @.str.83, i64 0, i64 0))
%85 = call i32 @printf(i8* getelementptr inbounds ([127 x i8], [127 x i8]* @.str.84, i64 0, i64 0))
%86 = call i32 @printf(i8* getelementptr inbounds ([102 x i8], [102 x i8]* @.str.85, i64 0, i64 0))
%87 = call i32 @printf(i8* getelementptr inbounds ([101 x i8], [101 x i8]* @.str.86, i64 0, i64 0))
%88 = call i32 @printf(i8* getelementptr inbounds ([124 x i8], [124 x i8]* @.str.87, i64 0, i64 0))
%89 = call i32 @printf(i8* getelementptr inbounds ([101 x i8], [101 x i8]* @.str.88, i64 0, i64 0))
%90 = call i32 @printf(i8* getelementptr inbounds ([104 x i8], [104 x i8]* @.str.89, i64 0, i64 0))
%91 = call i32 @printf(i8* getelementptr inbounds ([122 x i8], [122 x i8]* @.str.90, i64 0, i64 0))
%92 = call i32 @printf(i8* getelementptr inbounds ([125 x i8], [125 x i8]* @.str.91, i64 0, i64 0))
%93 = call i32 @printf(i8* getelementptr inbounds ([124 x i8], [124 x i8]* @.str.92, i64 0, i64 0))
%94 = call i32 @printf(i8* getelementptr inbounds ([80 x i8], [80 x i8]* @.str.93, i64 0, i64 0))
%95 = call i32 @printf(i8* getelementptr inbounds ([108 x i8], [108 x i8]* @.str.94, i64 0, i64 0))
%96 = call i32 @printf(i8* getelementptr inbounds ([117 x i8], [117 x i8]* @.str.95, i64 0, i64 0))
%97 = call i32 @printf(i8* getelementptr inbounds ([97 x i8], [97 x i8]* @.str.96, i64 0, i64 0))
%98 = call i32 @printf(i8* getelementptr inbounds ([117 x i8], [117 x i8]* @.str.97, i64 0, i64 0))
%99 = call i32 @printf(i8* getelementptr inbounds ([171 x i8], [171 x i8]* @.str.98, i64 0, i64 0))
%100 = call i32 @printf(i8* getelementptr inbounds ([70 x i8], [70 x i8]* @.str.99, i64 0, i64 0))
%101 = call i32 @printf(i8* getelementptr inbounds ([64 x i8], [64 x i8]* @.str.100, i64 0, i64 0))
%102 = call i32 @printf(i8* getelementptr inbounds ([103 x i8], [103 x i8]* @.str.101, i64 0, i64 0))
%103 = call i32 @printf(i8* getelementptr inbounds ([104 x i8], [104 x i8]* @.str.102, i64 0, i64 0))
%104 = call i32 @printf(i8* getelementptr inbounds ([94 x i8], [94 x i8]* @.str.103, i64 0, i64 0))
%105 = call i32 @printf(i8* getelementptr inbounds ([78 x i8], [78 x i8]* @.str.104, i64 0, i64 0))
%106 = call i32 @printf(i8* getelementptr inbounds ([141 x i8], [141 x i8]* @.str.105, i64 0, i64 0))
%107 = call i32 @printf(i8* getelementptr inbounds ([121 x i8], [121 x i8]* @.str.106, i64 0, i64 0))
%108 = call i32 @printf(i8* getelementptr inbounds ([122 x i8], [122 x i8]* @.str.107, i64 0, i64 0))
%109 = call i32 @printf(i8* getelementptr inbounds ([134 x i8], [134 x i8]* @.str.108, i64 0, i64 0))
%110 = call i32 @printf(i8* getelementptr inbounds ([93 x i8], [93 x i8]* @.str.109, i64 0, i64 0))
%111 = call i32 @printf(i8* getelementptr inbounds ([135 x i8], [135 x i8]* @.str.110, i64 0, i64 0))
%112 = call i32 @printf(i8* getelementptr inbounds ([74 x i8], [74 x i8]* @.str.111, i64 0, i64 0))
%113 = call i32 @printf(i8* getelementptr inbounds ([103 x i8], [103 x i8]* @.str.112, i64 0, i64 0))
%114 = call i32 @printf(i8* getelementptr inbounds ([77 x i8], [77 x i8]* @.str.113, i64 0, i64 0))
%115 = call i32 @printf(i8* getelementptr inbounds ([49 x i8], [49 x i8]* @.str.114, i64 0, i64 0))
%116 = call i32 @printf(i8* getelementptr inbounds ([68 x i8], [68 x i8]* @.str.115, i64 0, i64 0))
%117 = call i32 @printf(i8* getelementptr inbounds ([68 x i8], [68 x i8]* @.str.116, i64 0, i64 0))
%118 = call i32 @printf(i8* getelementptr inbounds ([68 x i8], [68 x i8]* @.str.117, i64 0, i64 0))
%119 = call i32 @printf(i8* getelementptr inbounds ([129 x i8], [129 x i8]* @.str.118, i64 0, i64 0))
%120 = call i32 @printf(i8* getelementptr inbounds ([119 x i8], [119 x i8]* @.str.119, i64 0, i64 0))
%121 = call i32 @printf(i8* getelementptr inbounds ([86 x i8], [86 x i8]* @.str.120, i64 0, i64 0))
%122 = call i32 @printf(i8* getelementptr inbounds ([107 x i8], [107 x i8]* @.str.121, i64 0, i64 0))
%123 = call i32 @printf(i8* getelementptr inbounds ([126 x i8], [126 x i8]* @.str.122, i64 0, i64 0))
%124 = call i32 @printf(i8* getelementptr inbounds ([122 x i8], [122 x i8]* @.str.123, i64 0, i64 0))
%125 = call i32 @printf(i8* getelementptr inbounds ([112 x i8], [112 x i8]* @.str.124, i64 0, i64 0))
%126 = call i32 @printf(i8* getelementptr inbounds ([110 x i8], [110 x i8]* @.str.125, i64 0, i64 0))
%127 = call i32 @printf(i8* getelementptr inbounds ([54 x i8], [54 x i8]* @.str.126, i64 0, i64 0))
%128 = call i32 @printf(i8* getelementptr inbounds ([49 x i8], [49 x i8]* @.str.127, i64 0, i64 0))
%129 = call i32 @printf(i8* getelementptr inbounds ([40 x i8], [40 x i8]* @.str.128, i64 0, i64 0))
%130 = call i32 @printf(i8* getelementptr inbounds ([42 x i8], [42 x i8]* @.str.129, i64 0, i64 0))
%131 = call i32 @printf(i8* getelementptr inbounds ([53 x i8], [53 x i8]* @.str.130, i64 0, i64 0))
%132 = call i32 @printf(i8* getelementptr inbounds ([36 x i8], [36 x i8]* @.str.131, i64 0, i64 0))
%133 = call i32 @printf(i8* getelementptr inbounds ([69 x i8], [69 x i8]* @.str.132, i64 0, i64 0))
%134 = call i32 @printf(i8* getelementptr inbounds ([41 x i8], [41 x i8]* @.str.133, i64 0, i64 0))
%135 = call i32 @printf(i8* getelementptr inbounds ([45 x i8], [45 x i8]* @.str.134, i64 0, i64 0))
%136 = call i32 @printf(i8* getelementptr inbounds ([50 x i8], [50 x i8]* @.str.135, i64 0, i64 0))
%137 = call i32 @printf(i8* getelementptr inbounds ([52 x i8], [52 x i8]* @.str.136, i64 0, i64 0))
%138 = call i32 @printf(i8* getelementptr inbounds ([52 x i8], [52 x i8]* @.str.137, i64 0, i64 0))
%139 = call i32 @printf(i8* getelementptr inbounds ([53 x i8], [53 x i8]* @.str.138, i64 0, i64 0))
%140 = call i32 @printf(i8* getelementptr inbounds ([87 x i8], [87 x i8]* @.str.139, i64 0, i64 0))
%141 = call i32 @printf(i8* getelementptr inbounds ([72 x i8], [72 x i8]* @.str.140, i64 0, i64 0))
%142 = call i32 @printf(i8* getelementptr inbounds ([60 x i8], [60 x i8]* @.str.141, i64 0, i64 0))
%143 = call i32 @printf(i8* getelementptr inbounds ([62 x i8], [62 x i8]* @.str.142, i64 0, i64 0))
%144 = call i32 @printf(i8* getelementptr inbounds ([70 x i8], [70 x i8]* @.str.143, i64 0, i64 0))
%145 = call i32 @printf(i8* getelementptr inbounds ([54 x i8], [54 x i8]* @.str.144, i64 0, i64 0))
%146 = call i32 @printf(i8* getelementptr inbounds ([81 x i8], [81 x i8]* @.str.145, i64 0, i64 0))
%147 = call i32 @printf(i8* getelementptr inbounds ([50 x i8], [50 x i8]* @.str.146, i64 0, i64 0))
%148 = call i32 @printf(i8* getelementptr inbounds ([37 x i8], [37 x i8]* @.str.147, i64 0, i64 0))
%149 = call i32 @printf(i8* getelementptr inbounds ([37 x i8], [37 x i8]* @.str.148, i64 0, i64 0))
%150 = call i32 @printf(i8* getelementptr inbounds ([43 x i8], [43 x i8]* @.str.149, i64 0, i64 0))
%151 = call i32 @printf(i8* getelementptr inbounds ([57 x i8], [57 x i8]* @.str.150, i64 0, i64 0))
%152 = call i32 @printf(i8* getelementptr inbounds ([68 x i8], [68 x i8]* @.str.151, i64 0, i64 0))
%153 = call i32 @printf(i8* getelementptr inbounds ([68 x i8], [68 x i8]* @.str.152, i64 0, i64 0))
%154 = call i32 @printf(i8* getelementptr inbounds ([80 x i8], [80 x i8]* @.str.153, i64 0, i64 0))
%155 = call i32 @printf(i8* getelementptr inbounds ([73 x i8], [73 x i8]* @.str.154, i64 0, i64 0))
%156 = call i32 @printf(i8* getelementptr inbounds ([75 x i8], [75 x i8]* @.str.155, i64 0, i64 0))
%157 = call i32 @printf(i8* getelementptr inbounds ([125 x i8], [125 x i8]* @.str.156, i64 0, i64 0))
%158 = call i32 @printf(i8* getelementptr inbounds ([118 x i8], [118 x i8]* @.str.157, i64 0, i64 0))
%159 = call i32 @printf(i8* getelementptr inbounds ([114 x i8], [114 x i8]* @.str.158, i64 0, i64 0))
%160 = call i32 @printf(i8* getelementptr inbounds ([77 x i8], [77 x i8]* @.str.159, i64 0, i64 0))
%161 = call i32 @printf(i8* getelementptr inbounds ([30 x i8], [30 x i8]* @.str.160, i64 0, i64 0))
%162 = call i32 @printf(i8* getelementptr inbounds ([131 x i8], [131 x i8]* @.str.161, i64 0, i64 0))
%163 = call i32 @printf(i8* getelementptr inbounds ([111 x i8], [111 x i8]* @.str.162, i64 0, i64 0))
%164 = call i32 @printf(i8* getelementptr inbounds ([61 x i8], [61 x i8]* @.str.163, i64 0, i64 0))
%165 = call i32 @printf(i8* getelementptr inbounds ([71 x i8], [71 x i8]* @.str.164, i64 0, i64 0))
%166 = call i32 @printf(i8* getelementptr inbounds ([87 x i8], [87 x i8]* @.str.165, i64 0, i64 0))
%167 = call i32 @printf(i8* getelementptr inbounds ([82 x i8], [82 x i8]* @.str.166, i64 0, i64 0))
%168 = call i32 @printf(i8* getelementptr inbounds ([70 x i8], [70 x i8]* @.str.167, i64 0, i64 0))
%169 = call i32 @printf(i8* getelementptr inbounds ([110 x i8], [110 x i8]* @.str.168, i64 0, i64 0))
%170 = call i32 @printf(i8* getelementptr inbounds ([83 x i8], [83 x i8]* @.str.169, i64 0, i64 0))
%171 = call i32 @printf(i8* getelementptr inbounds ([82 x i8], [82 x i8]* @.str.170, i64 0, i64 0))
%172 = call i32 @printf(i8* getelementptr inbounds ([82 x i8], [82 x i8]* @.str.171, i64 0, i64 0))
%173 = call i32 @printf(i8* getelementptr inbounds ([75 x i8], [75 x i8]* @.str.172, i64 0, i64 0))
%174 = call i32 @printf(i8* getelementptr inbounds ([24 x i8], [24 x i8]* @.str.173, i64 0, i64 0))
%175 = call i32 @printf(i8* getelementptr inbounds ([73 x i8], [73 x i8]* @.str.174, i64 0, i64 0))
%176 = call i32 @printf(i8* getelementptr inbounds ([72 x i8], [72 x i8]* @.str.175, i64 0, i64 0))
%177 = call i32 @printf(i8* getelementptr inbounds ([120 x i8], [120 x i8]* @.str.176, i64 0, i64 0))
%178 = call i32 @printf(i8* getelementptr inbounds ([122 x i8], [122 x i8]* @.str.177, i64 0, i64 0))
%179 = call i32 @printf(i8* getelementptr inbounds ([116 x i8], [116 x i8]* @.str.178, i64 0, i64 0))
%180 = call i32 @printf(i8* getelementptr inbounds ([129 x i8], [129 x i8]* @.str.179, i64 0, i64 0))
%181 = call i32 @printf(i8* getelementptr inbounds ([107 x i8], [107 x i8]* @.str.180, i64 0, i64 0))
%182 = call i32 @printf(i8* getelementptr inbounds ([101 x i8], [101 x i8]* @.str.181, i64 0, i64 0))
%183 = call i32 @printf(i8* getelementptr inbounds ([12 x i8], [12 x i8]* @.str.182, i64 0, i64 0))
%184 = call i32 @printf(i8* getelementptr inbounds ([88 x i8], [88 x i8]* @.str.183, i64 0, i64 0))
%185 = call i32 @printf(i8* getelementptr inbounds ([44 x i8], [44 x i8]* @.str.184, i64 0, i64 0))
%186 = call i32 @printf(i8* getelementptr inbounds ([108 x i8], [108 x i8]* @.str.185, i64 0, i64 0))
%187 = call i32 @printf(i8* getelementptr inbounds ([110 x i8], [110 x i8]* @.str.186, i64 0, i64 0))
%188 = call i32 @printf(i8* getelementptr inbounds ([104 x i8], [104 x i8]* @.str.187, i64 0, i64 0))
%189 = call i32 @printf(i8* getelementptr inbounds ([64 x i8], [64 x i8]* @.str.188, i64 0, i64 0))
%190 = call i32 @printf(i8* getelementptr inbounds ([74 x i8], [74 x i8]* @.str.189, i64 0, i64 0))
%191 = call i32 @printf(i8* getelementptr inbounds ([98 x i8], [98 x i8]* @.str.190, i64 0, i64 0))
%192 = call i32 @printf(i8* getelementptr inbounds ([88 x i8], [88 x i8]* @.str.191, i64 0, i64 0))
%193 = call i32 @printf(i8* getelementptr inbounds ([90 x i8], [90 x i8]* @.str.192, i64 0, i64 0))
%194 = call i32 @printf(i8* getelementptr inbounds ([116 x i8], [116 x i8]* @.str.193, i64 0, i64 0))
%195 = call i32 @printf(i8* getelementptr inbounds ([91 x i8], [91 x i8]* @.str.194, i64 0, i64 0))
%196 = call i32 @printf(i8* getelementptr inbounds ([108 x i8], [108 x i8]* @.str.195, i64 0, i64 0))
%197 = call i32 @printf(i8* getelementptr inbounds ([73 x i8], [73 x i8]* @.str.196, i64 0, i64 0))
%198 = call i32 @printf(i8* getelementptr inbounds ([71 x i8], [71 x i8]* @.str.197, i64 0, i64 0))
%199 = call i32 @printf(i8* getelementptr inbounds ([45 x i8], [45 x i8]* @.str.198, i64 0, i64 0))
%200 = call i32 @printf(i8* getelementptr inbounds ([28 x i8], [28 x i8]* @.str.199, i64 0, i64 0))
%201 = call i32 @printf(i8* getelementptr inbounds ([102 x i8], [102 x i8]* @.str.200, i64 0, i64 0))
%202 = call i32 @printf(i8* getelementptr inbounds ([54 x i8], [54 x i8]* @.str.201, i64 0, i64 0))
%203 = call i32 @printf(i8* getelementptr inbounds ([155 x i8], [155 x i8]* @.str.202, i64 0, i64 0))
%204 = call i32 @printf(i8* getelementptr inbounds ([48 x i8], [48 x i8]* @.str.203, i64 0, i64 0))
%205 = call i32 @printf(i8* getelementptr inbounds ([94 x i8], [94 x i8]* @.str.204, i64 0, i64 0))
%206 = call i32 @printf(i8* getelementptr inbounds ([106 x i8], [106 x i8]* @.str.205, i64 0, i64 0))
%207 = call i32 @printf(i8* getelementptr inbounds ([102 x i8], [102 x i8]* @.str.206, i64 0, i64 0))
%208 = call i32 @printf(i8* getelementptr inbounds ([98 x i8], [98 x i8]* @.str.207, i64 0, i64 0))
%209 = call i32 @printf(i8* getelementptr inbounds ([97 x i8], [97 x i8]* @.str.208, i64 0, i64 0))
%210 = call i32 @printf(i8* getelementptr inbounds ([53 x i8], [53 x i8]* @.str.209, i64 0, i64 0))
%211 = call i32 @printf(i8* getelementptr inbounds ([30 x i8], [30 x i8]* @.str.210, i64 0, i64 0))
%212 = call i32 @printf(i8* getelementptr inbounds ([91 x i8], [91 x i8]* @.str.211, i64 0, i64 0))
%213 = call i32 @printf(i8* getelementptr inbounds ([91 x i8], [91 x i8]* @.str.212, i64 0, i64 0))
%214 = call i32 @printf(i8* getelementptr inbounds ([91 x i8], [91 x i8]* @.str.213, i64 0, i64 0))
%215 = call i32 @printf(i8* getelementptr inbounds ([91 x i8], [91 x i8]* @.str.214, i64 0, i64 0))
%216 = call i32 @printf(i8* getelementptr inbounds ([91 x i8], [91 x i8]* @.str.215, i64 0, i64 0))
%217 = call i32 @printf(i8* getelementptr inbounds ([30 x i8], [30 x i8]* @.str.216, i64 0, i64 0))
%218 = call i32 @printf(i8* getelementptr inbounds ([83 x i8], [83 x i8]* @.str.217, i64 0, i64 0))
%219 = call i32 @printf(i8* getelementptr inbounds ([40 x i8], [40 x i8]* @.str.218, i64 0, i64 0))
%220 = call i32 @printf(i8* getelementptr inbounds ([51 x i8], [51 x i8]* @.str.219, i64 0, i64 0))
%221 = call i32 @printf(i8* getelementptr inbounds ([86 x i8], [86 x i8]* @.str.220, i64 0, i64 0))
ret void
}

LLVM IR (-O2):
@str = [106 x i8] c"MADS is an open-source code designed as an integrated high-performance computational framework performing\00"
@str.221 = [125 x i8] c"a wide range of model-based analyses: Sensitivity Analysis (SA), Parameter Estimation (PE), Model Inversion and Calibration,\00"
@str.222 = [92 x i8] c"Uncertainty Quantification (UQ), Model Selection and Averaging, and Decision Support (DS).\0A\00"
@str.223 = [120 x i8] c"MADS utilizes adaptive rules and techniques which allows the analyses to be performed with minimum user input. The code\00"
@str.224 = [118 x i8] c"provides a series of alternative algorithms to perform each type of model analyses. The code allows for coupled model\00"
@str.225 = [114 x i8] c"parameters and regularization terms that are internally computed based on user-defined mathematical expressions.\0A\00"
@str.226 = [55 x i8] c"USAGE: mads problem_name [ keywords | options ] OR\00"
@str.227 = [55 x i8] c" mads MADS_input_file [ keywords | options ] OR\00"
@str.228 = [124 x i8] c" mads PEST_input_file [ keywords | options ] (MADS is compatible with PEST control, template and instruction files)\0A\00"
@str.229 = [108 x i8] c" problem_name: name of the solved problem; MADS_input_file named problem_name.mads is expected\00"
@str.230 = [81 x i8] c" MADS_input_file: problem input file in MADS format (typically *.mads)\00"
@str.231 = [90 x i8] c" PEST_input_file: problem input file in PEST format (PEST control file; *.pst)\0A\00"
@str.232 = [52 x i8] c"keywords & options (can be provided in any order):\0A\00"
@str.233 = [23 x i8] c"problem type keywords:\00"
@str.234 = [86 x i8] c" check - check model setup and input/output files (no model execution)\00"
@str.235 = [142 x i8] c" create - create calibration problem based on provided model parameters (single model execution to compute calibration targets)\00"
@str.236 = [97 x i8] c" forward - forward model run (no calibration); recommended for model setup checking\00"
@str.237 = [89 x i8] c" calibrate - calibration run [default if no problem type keyword is provided]\00"
@str.238 = [45 x i8] c" montecarlo - Monte-Carlo analysis\00"
@str.239 = [52 x i8] c" gsens - global sensitivity analysis\00"
@str.240 = [70 x i8] c" glue - Generalized Likelihood Uncertainty Estimation\00"
@str.241 = [97 x i8] c" lsens - local sensitivity analysis (standalone or at the end of the calibration)\00"
@str.242 = [97 x i8] c" eigen - local eigensystem analysis (standalone or at the end of the calibration)\00"
@str.243 = [78 x i8] c" abagus - Agent-Based Global Uncertainty & Sensitivity Analysis\00"
@str.244 = [51 x i8] c" infogap - Info-gap decision analysis\00"
@str.245 = [115 x i8] c" postpua - predictive uncertainty analysis of sampling results (currently for abagus PSSA files only)\00"
@str.246 = [128 x i8] c" bayes - Bayesian parameter sampling using DREAM (DiffeRential Evolution Adaptive Metropolis; Vrugt et al. 2009)\00"
@str.247 = [43 x i8] c"\0Acalibration method keywords (select one):\00"
@str.248 = [102 x i8] c" single - single calibration using initial guesses provided in the input file [default]\00"
@str.249 = [128 x i8] c" igrnd - sequential calibrations using a set of random initial values (number of realizations defined by real=X)\00"
@str.250 = [133 x i8] c" igpd - sequential calibrations using a set of discretized initial values (discretization defined in the input file)\00"
@str.251 = [150 x i8] c" ppsd - sequential calibrations using partial parameter space discretization (PPSD) method (discretization defined in the input file)\00"
@str.252 = [35 x i8] c"\0Acalibration termination criteria:\00"
@str.253 = [95 x i8] c" eval=[integer] - functional evaluations exceed the predefined value [default eval=5000]\00"
@str.254 = [88 x i8] c" cutoff=[real] - objective function is below the cutoff value [default cutoff=0]\00"
@str.255 = [83 x i8] c" obsrange - model predictions are within predefined calibration ranges\00"
@str.256 = [104 x i8] c" obserror=[real] - model predictions are within a predefined absolute error [default obserror=0.1]\00"
@str.257 = [134 x i8] c" parerror=[real] - model parameters are within a predefined absolute error from their known 'true' values [default parerror=0.1]\00"
@str.258 = [28 x i8] c"\0Auser-enforced termination:\00"
@str.259 = [117 x i8] c" problem_name.quit - if file with this name exists in the running directory, MADS terminates as soon as possible.\00"
@str.260 = [131 x i8] c" problem_name.stop - if file with this name exists in the running directory, MADS terminates after saving intermediate results.\00"
@str.261 = [93 x i8] c"\0Aoptimization method (opt=[string]; various combinations are possible, e.g. pso_std_lm_gsl):\00"
@str.262 = [73 x i8] c" opt=lm - Local Levenberg-Marquardt optimization [default]\00"
@str.263 = [84 x i8] c" opt=lm_levmar - Local Levenberg-Marquardt optimization using LEVMAR library\00"
@str.264 = [81 x i8] c" opt=lm_gsl - Local Levenberg-Marquardt optimization using GSL library\00"
@str.265 = [132 x i8] c" opt=lm_ms - Local Multi-Start (Multi-Try) Levenberg-Marquardt (MSLM) optimization using multiple random initial guesses\00"
@str.266 = [116 x i8] c" opt=pso - Global Particle Swarm optimization (default Standard2006; http://clerc.maurice.free.fr/pso)\00"
@str.267 = [85 x i8] c" opt=apso - Global Adaptive Particle Swarm optimization (default TRIBES)\00"
@str.268 = [91 x i8] c" opt=swarm - Global Particle Swarm optimization Standard2006 (also opt=pso_std)\00"
@str.269 = [115 x i8] c" opt=tribes - Global Particle Swarm optimization TRIBES-D (Clerc 2004; http://clerc.maurice.free.fr/pso)\00"
@str.270 = [116 x i8] c" opt=squads - SQUADS: Adaptive hybrid optimization using coupled local and global optimization techniques\00"
@str.271 = [43 x i8] c"\0Ageneral calibration/optimization options:\00"
@str.272 = [73 x i8] c" retry=[integer] - number of optimization retries [default retry=0]\00"
@str.273 = [114 x i8] c" particles=[integer]- number of initial particles or tribes [default particles=10+2*sqrt(Number_of_parameters)]\00"
@str.274 = [86 x i8] c" lmeigen|eigen - eigen analysis of the intermediate / final optimized solution\00"
@str.275 = [43 x i8] c"\0ALevenberg-Marquardt optimization options:\00"
@str.276 = [130 x i8] c" lmfactor=[double] - multiplier applied to compute when to initiate LM searches within SQUADS algorithm [default lmfactor=1.0]\00"
@str.277 = [120 x i8] c" lmindirect - Indirect computation of LM alpha coefficient [default DIRECT/Delayed gratification computation]\00"
@str.278 = [128 x i8] c" lmmu=[double] - LM alpha multiplier for direct computation of LM alpha coefficient when OF decreases [default lmmu=0.1]\00"
@str.279 = [127 x i8] c" lmnu=[integer] - LM alpha multiplier for direct computation of LM alpha coefficient when OF increases [default lmnu=10]\00"
@str.280 = [113 x i8] c" lmaccel - LM geodesic acceleration as proposed by Transtrum et al (2011) [default NO acceleration]\00"
@str.281 = [110 x i8] c" lmratio=[double] - LM acceleration velocity ratio for recomputing the Jacobian [default lmratio=(3/4)^2]\00"
@str.282 = [69 x i8] c" lmh=[double] - LM acceleration multiplier [default lmh=0.1]\00"
@str.283 = [109 x i8] c" lmiter=[integer] - number of LM iterations [default computed internally based on number of evaluations]\00"
@str.284 = [123 x i8] c" lmnlam=[integer] - Maximum number of linear solves (lambda searches) after each Jacobian estimate [default lmnlam=10]\00"
@str.285 = [139 x i8] c" lmnlamof=[integer] - Number of acceptable linear solves (lambda searches) with similar OF's during LM optimization [default lmnlamof=3]\00"
@str.286 = [127 x i8] c" lmnjacof=[integer] - Number of acceptable jacobian iterations with similar OF's during LM optimization [default lmnjacof=5]\00"
@str.287 = [68 x i8] c" lmerror=[double] - LM convergence error [default lmerror=1e-5]\00"
@str.288 = [125 x i8] c"\0Asampling method (smp=[string] OR mslm=[string] for Multi-Start Levenberg-Marquardt (MSLM) analysis using multiple retries):\00"
@str.289 = [121 x i8] c" smp=olhs - Optimal Latin Hyper Cube sampling [default] (if real=1 RANDOM; if real>1 IDLHS; if real>500 LHS)\00"
@str.290 = [56 x i8] c" smp=lhs - Latin Hyper Cube sampling (LHS)\00"
@str.291 = [79 x i8] c" smp=idlhs - Improved Distributed Latin Hyper Cube sampling (IDLHS)\00"
@str.292 = [40 x i8] c" smp=random - Random sampling\00"
@str.293 = [19 x i8] c"\0Asampling options:\00"
@str.294 = [83 x i8] c" real=[integer] - number of random realizations / samples [default real=100]\00"
@str.295 = [125 x i8] c" case=[integer] - execute a single case from all the realizations / samples (applied in PPSD, IGDP, IGRND, MONTECARLO)\00"
@str.296 = [74 x i8] c" seed=[integer] - random seed value [randomly generated by default]\00"
@str.297 = [104 x i8] c"\0Aobjective function functional form options (select one; regularizaiton terms can be added separately):\00"
@str.298 = [63 x i8] c" ssr - sum of the squared residuals [default]\00"
@str.299 = [57 x i8] c" ssd0 - sum of the squared discrepancies\00"
@str.300 = [88 x i8] c" ssdx - sum of the squared discrepancies increased to get in the bounds\00"
@str.301 = [80 x i8] c" ssda - sum of the squared discrepancies and absolute residuals\00"
@str.302 = [79 x i8] c" ssdr - sum of the squared discrepancies and squared residuals\00"
@str.303 = [57 x i8] c"\0Atransformation of parameter and observation properties:\00"
@str.304 = [126 x i8] c" nosin - Sin transformation of optimized parameters is not applied [parameters are sin transformed by default]\00"
@str.305 = [101 x i8] c" sindx - Parameter space step for numerical derivatives of sin transformed parameters\00"
@str.306 = [100 x i8] c" [default sindx=1e-7 for internal problems; sindx=0.1 for external problems]\00"
@str.307 = [123 x i8] c" lindx - Parameter space step for numerical derivatives of not transformed parameters [default lindx=0.001]\00"
@str.308 = [100 x i8] c" pardx - Parameter space step for parameter space discretization [default pardx=0.1]\00"
@str.309 = [103 x i8] c" plog=[-1,0,1] - Log transformation of all optimized parameters is enforced (1) or disabled (0)\00"
@str.310 = [121 x i8] c" [default plog=-1; log transformation is explicitly defined for each parameter in the input file]\00"
@str.311 = [124 x i8] c" olog=[-1,0,1] - Log transformation of all the observations (simulated and measured) is enforced (1) or disabled (0)\00"
@str.312 = [123 x i8] c" [default olog=-1; log transformation is explicitly defined for each observation in the input file]\00"
@str.313 = [79 x i8] c" oweight=[-1,0,1,2] - Weights for all the observation residuals are defined:\00"
@str.314 = [107 x i8] c" 0 = zero weight, 1 = unit weight, 2 = weight reversely proportional to observation\00"
@str.315 = [116 x i8] c" [default oweight=-1; weights for each observation are explicitly defined in the input file]\00"
@str.316 = [96 x i8] c" obsdomain=[float] - observation space domain size [default provided in the MADS input file]\00"
@str.317 = [116 x i8] c" obsstep=[float] - observation space domain step to explore info-gap observation uncertainty [default ignored]\00"
@str.318 = [170 x i8] c"\0Aparallelization (available parallelization resources are internally detected by default; supported: Slurm, Moab, BProc, LSB, PBS, Beowulf, OpenMPI, OpenMP, POSIX, ...):\00"
@str.319 = [69 x i8] c" np=[integer] - Number of requested parallel jobs [optional]\00"
@str.320 = [63 x i8] c" mpi - Use OpenMPI parallelization [optional]\00"
@str.321 = [102 x i8] c" posix[=integer] - POSIX parallel threading [optional]; number of threads can be defined as well\00"
@str.322 = [103 x i8] c" omp[=integer] - OpenMP parallel threading [optional]; number of threads can be defined as well\00"
@str.323 = [93 x i8] c" ssh - Forces the use of ssh to execute external jobs at the comptuer nodes\00"
@str.324 = [77 x i8] c" ppt=[integer] - Number of processors per an external task [optional]\00"
@str.325 = [140 x i8] c" nplambda=[integer] - Number of requested parallel lambda runs in the case of Levenberg-Marquardt optimization [optional; nplambda <= np]\00"
@str.326 = [120 x i8] c" rstfile=[string] - name of existing ZIP restart file to be used (created by previous Parallel MADS run) [optional]\00"
@str.327 = [121 x i8] c" rstdir=[string] - name of existing restart directory to be used (created by previous Parallel MADS run) [optional]\00"
@str.328 = [133 x i8] c" restart=[integer] - restart=1 (default; automatic restart if possible); restart=0 (force no restart); restart=-1 (force restart)\00"
@str.329 = [92 x i8] c" by default the analyses will be restarted automatically (restart=1)\00"
@str.330 = [134 x i8] c" bin_restart - restart information is stored in binary files (by default, model outputs are added in a zip file for restart)\00"
@str.331 = [73 x i8] c"\0AABAGUS (Agent-Based Global Uncertainty & Sensitivity Analysis) options:\00"
@str.332 = [102 x i8] c" infile=[string] - name of previous results file to be used to initialize Kd-tree [default=NULL]\00"
@str.333 = [76 x i8] c" energy=[integer] - initial energy for particles [default energy=10000]\00"
@str.334 = [48 x i8] c"\0Aoptions for the build-in analytical solutions:\00"
@str.335 = [67 x i8] c" point - point contaminant source in 3D flow domain\00"
@str.336 = [67 x i8] c" plane - plane contaminant source in 3D flow domain\00"
@str.337 = [67 x i8] c" box - brick contaminant source in 3D flow domain\00"
@str.338 = [128 x i8] c" obs_int=[1,2] - concentration integration along observation well screens (1 - mid point; 2 - two end points [default=1]\00"
@str.339 = [118 x i8] c" disp_tied - lateral and vertical transverse dispersivities are fractions of the longitudinal dispersivity\00"
@str.340 = [85 x i8] c" disp_scaled - longitudinal dispersivity is scaled with the travel distance\00"
@str.341 = [106 x i8] c" if disp_scaled and disp_tied are applied, longitudinal dispersivity is scaled and\00"
@str.342 = [125 x i8] c" lateral and vertical transverse dispersivities are fractions of the scaled longitudinal dispersivity\00"
@str.343 = [121 x i8] c" disp_scaled=2 - longitudinal, lateral and vertical transverse dispersivities are scaled with the travel distance\00"
@str.344 = [111 x i8] c" time_step - parameter \22end time\22 is representing the period (dt) within which the source is active\00"
@str.345 = [109 x i8] c"\0Abuild-in test problems for optimization / uncertainty-quantification techniques (local and global methods):\00"
@str.346 = [53 x i8] c" test=[integer] - test problem ID [default=1]:\00"
@str.347 = [48 x i8] c" 1: Parabola (Sphere)\00"
@str.348 = [39 x i8] c" 2: Griewank\00"
@str.349 = [41 x i8] c" 3: Rosenbrock\00"
@str.350 = [52 x i8] c" 4: De Jong's Function\00"
@str.351 = [35 x i8] c" 5: Step\00"
@str.352 = [68 x i8] c" 6: Alpine function (Clerc's Function)\00"
@str.353 = [40 x i8] c" 7: Rastrigin\00"
@str.354 = [44 x i8] c" 8: Krishna Kumar\00"
@str.355 = [49 x i8] c" 9: Tripod function 2D\00"
@str.356 = [51 x i8] c" 10: Shekel's Foxholes 2D\00"
@str.357 = [51 x i8] c" 11: Shekel's Foxholes 5D\00"
@str.358 = [52 x i8] c" 12: Shekel's Foxholes 10D\00"
@str.359 = [86 x i8] c" 20: Shekel's Foxholes 2D (alternative; global methods only)\00"
@str.360 = [71 x i8] c" 21: Polynomial fitting (global methods only)\00"
@str.361 = [59 x i8] c" 22: Ackley (global methods only)\00"
@str.362 = [61 x i8] c" 23: Eason 2D (global methods only)\00"
@str.363 = [69 x i8] c" 31: Rosenbrock (2D simplified alternative)\00"
@str.364 = [53 x i8] c" 32: Griewank (alternative)\00"
@str.365 = [80 x i8] c" 33: Rosenbrock (alternative with d*(d-1) observations\00"
@str.366 = [49 x i8] c" 34: Powell's Quadratic\00"
@str.367 = [36 x i8] c" 35: Booth\00"
@str.368 = [36 x i8] c" 36: Beale\00"
@str.369 = [42 x i8] c" 37: Parsopoulos\00"
@str.370 = [56 x i8] c" Curve-fitting test functions:\00"
@str.371 = [67 x i8] c" 40: Sin/Cos test function (2 parameters)\00"
@str.372 = [67 x i8] c" 41: Sin/Cos test function (4 parameters)\00"
@str.373 = [79 x i8] c" 42: Sin/Cos test function (2 parameters; simplified)\00"
@str.374 = [72 x i8] c" 43: Exponential Data Fitting I (5 parameters)\00"
@str.375 = [74 x i8] c" 44: Exponential Data Fitting II (11 parameters)\00"
@str.376 = [124 x i8] c" dim=[integer] - dimensionality of parameter space for the test problem (fixed for some of the problems) [default=2]\00"
@str.377 = [117 x i8] c" npar=[integer] - number of model parameters for the test problem (fixed for some of the problems) [default=2]\00"
@str.378 = [113 x i8] c" nobs=[integer] - number of observations for the test problem (fixed for some of the problems) [default=2]\00"
@str.379 = [76 x i8] c" pardomain=[float] - parameter space domain size [default pardomain=100]\00"
@str.380 = [29 x i8] c"\0Adebugging / verbose levels:\00"
@str.381 = [130 x i8] c" force | f - enforce running even if a file *.running exists (the file *.running is to prevent overlapping executions)\00"
@str.382 = [110 x i8] c" quiet | q - no screen output (all the screen output is saved in a file with extension mads_output\00"
@str.383 = [60 x i8] c" debug=[0-5] - general debugging [default debug=0]\00"
@str.384 = [70 x i8] c" fdebug=[0-5] - model evaluation debugging [default fdebug=0]\00"
@str.385 = [86 x i8] c" ldebug=[0-3] - Levenberg-Marquardt optimization debugging [default ldebug=0]\00"
@str.386 = [81 x i8] c" pdebug=[0-3] - Particle Swarm optimization debugging [default pdebug=0]\00"
@str.387 = [69 x i8] c" mdebug=[0-3] - Random sampling debugging [default mdebug=0]\00"
@str.388 = [109 x i8] c" odebug=[0-1] - Record objective function progress in a file with extension 'ofe' [default odebug=0]\00"
@str.389 = [82 x i8] c" tdebug=[0-1] - Output process times for various tasks [default tdebug=0]\00"
@str.390 = [81 x i8] c" tpldebug=[0-3] - Debug the writing of external files [default tpldebug=0]\00"
@str.391 = [81 x i8] c" insdebug=[0-3] - Debug the reading of external files [default insdebug=0]\00"
@str.392 = [74 x i8] c" pardebug=[0-3] - Debug the parallel execution [default pardebug=0]\00"
@str.393 = [23 x i8] c"\0Apre-/post-processing:\00"
@str.394 = [72 x i8] c" yaml - Reads/writes/converts MADS files in YAML format\00"
@str.395 = [71 x i8] c" xml - Reads/writes/converts MADS files in XML format\00"
@str.396 = [119 x i8] c" resultsfile=[file] - Post process results saved in a previously generated resultsfile (e.g. using 'igrnd' analysis)\00"
@str.397 = [121 x i8] c" resultscase=[int] - Post process specific case saved in resultsfile (if resultscase<0, first abs(resultscase) cases)\00"
@str.398 = [115 x i8] c" cutoff=[real] - Post process all cases saved in resultsfile with objective function below the cutoff value\00"
@str.399 = [128 x i8] c" obsrange - Post process all cases saved in resultsfile with model predictions within predefined calibration ranges\00"
@str.400 = [106 x i8] c" pargen - Generate MADS input files for independent multi-processor runs [default pargen=0]\00"
@str.401 = [100 x i8] c" save - Save MADS input/output files for successful parameter sets [default save=0]\00"
@str.402 = [11 x i8] c"\0AExamples:\00"
@str.403 = [87 x i8] c" mads a01 test=2 opt=lm eigen igrnd real=1 (no input files are needed for execution)\00"
@str.404 = [43 x i8] c" mads a01 test=2 opt=squads igrnd real=1\00"
@str.405 = [107 x i8] c" mads a01 test=2 abagus cutoff=0.1 eval=100000 (collect solutions of Griewank function below phi cutoff)\00"
@str.406 = [109 x i8] c" mads a01 test=3 abagus cutoff=20 eval=100000 (collect solutions of Rosenbrock function below phi cutoff)\00"
@str.407 = [103 x i8] c" mads examples/contamination/s01 ldebug lmeigen (file s01.mads is located in examples/contamination)\00"
@str.408 = [63 x i8] c" mads examples/contamination/s01 ldebug lmeigen igrnd real=1\00"
@str.409 = [73 x i8] c" mads examples/contamination/s01 seed=1549170842 obsrange igrnd real=1\00"
@str.410 = [97 x i8] c" mads examples/contamination/s01 opt=squads seed=1549170842 eigen obsrange pdebug igrnd real=1\00"
@str.411 = [87 x i8] c" mads examples/contamination/s01 opt=pso seed=1549170842 eigen obsrange igrnd real=1\00"
@str.412 = [89 x i8] c" mads examples/contamination/s01-flagged ppsd (Partial Parameter Space Discretization)\00"
@str.413 = [115 x i8] c" mads examples/contamination/s01-flagged igpd (Initial Guesses based on Discreetly distributed model parameters)\00"
@str.414 = [90 x i8] c" mads examples/contamination/s01 igrnd real=10 (Random Initial Guesses; all parameters)\00"
@str.415 = [107 x i8] c" mads examples/contamination/s01-flagged igrnd real=10 (Random Initial Guesses; only flagged parameters)\00"
@str.416 = [72 x i8] c" mads examples/contamination/s01 monte real=10 (Monte Carlo Analysis)\00"
@str.417 = [70 x i8] c" cd examples/wells; mads w01.mads igrnd real=1 seed=501228648 eigen\00"
@str.418 = [44 x i8] c"\0AParallel Levenberg-Marquardt optimization:\00"
@str.419 = [27 x i8] c" cd examples/wells-short\00"
@str.420 = [101 x i8] c" mads w01parallel.mads restart=0 np=2 ldebug pardebug=2 (Parallel optimization using 2 processors)\00"
@str.421 = [53 x i8] c" mads w01parallel.mads restart=0 np=11 nplambda=11\00"
@str.422 = [154 x i8] c" mads w01parallel.mads restart=0 np=3 nplambda=3 lmnlam=21 lmnlamof=12 (if a small number of processors is used, lmnlam & lmnlamof should be increased)\00"
@str.423 = [47 x i8] c"\0AComparisons between local and global methods:\00"
@str.424 = [93 x i8] c" mads a01 test=3 opt=lm igrnd real=1000 cutoff=1e-3 (Levenberg-Marquardt optimization)\00"
@str.425 = [105 x i8] c" mads a01 test=3 opt=lm_ms igrnd real=1000 cutoff=1e-3 (Multi-Start Levenberg-Marquardt optimization)\00"
@str.426 = [101 x i8] c" mads a01 test=3 opt=swarm igrnd real=1000 cutoff=1e-3 (Particle Swarm optimization Standard2006)\00"
@str.427 = [97 x i8] c" mads a01 test=3 opt=tribes igrnd real=1000 cutoff=1e-3 (Particle Swarm optimization TRIBES-D)\00"
@str.428 = [96 x i8] c" mads a01 test=3 opt=squads igrnd real=1000 cutoff=1e-3 (Adaptive hybrid optimization Squads)\00"
@str.429 = [52 x i8] c"\0AComparisons with PEST (http://www.sspa.com/pest/):\00"
@str.430 = [29 x i8] c" cd examples/contamination\00"
@str.431 = [90 x i8] c" mads s02 lmeigen (file s02.mads is located in examples/contamination)\00"
@str.432 = [90 x i8] c" pest s02pest (file s02pest.pst is located in examples/contamination)\00"
@str.433 = [90 x i8] c" mads w01 lmeigen (files associated with problem w01 are located in examples/wells)\00"
@str.434 = [90 x i8] c" pest w01pest (files associated with problem w01pest are located in examples/wells)\00"
@str.435 = [90 x i8] c" pest w02pest (files associated with problem w02pest are located in examples/wells)\00"
@str.436 = [29 x i8] c"\0AFor additional information:\00"
@str.437 = [82 x i8] c" web: http://mads.lanl.gov -:- http://www.ees.lanl.gov/staff/monty/codes/mads\00"
@str.438 = [39 x i8] c" repo: http://gitlab.com/monty/mads\00"
@str.439 = [50 x i8] c" git: git clone git@gitlab.com:monty/mads.git\00"
@str.440 = [85 x i8] c" email: Velimir V Vesselinov (monty) vvv@lanl.gov -:- velimir.vesselinov@gmail.com\00"
define void @mads_info() {
%1 = tail call i32 @puts(i8* dereferenceable(1) getelementptr inbounds ([106 x i8], [106 x i8]* @str, i64 0, i64 0))
%2 = tail call i32 @puts(i8* dereferenceable(1) getelementptr inbounds ([125 x i8], [125 x i8]* @str.221, i64 0, i64 0))
%3 = tail call i32 @puts(i8* dereferenceable(1) getelementptr inbounds ([92 x i8], [92 x i8]* @str.222, i64 0, i64 0))
%4 = tail call i32 @puts(i8* dereferenceable(1) getelementptr inbounds ([120 x i8], [120 x i8]* @str.223, i64 0, i64 0))
%5 = tail call i32 @puts(i8* dereferenceable(1) getelementptr inbounds ([118 x i8], [118 x i8]* @str.224, i64 0, i64 0))
%6 = tail call i32 @puts(i8* dereferenceable(1) getelementptr inbounds ([114 x i8], [114 x i8]* @str.225, i64 0, i64 0))
%7 = tail call i32 @puts(i8* dereferenceable(1) getelementptr inbounds ([55 x i8], [55 x i8]* @str.226, i64 0, i64 0))
%8 = tail call i32 @puts(i8* dereferenceable(1) getelementptr inbounds ([55 x i8], [55 x i8]* @str.227, i64 0, i64 0))
%9 = tail call i32 @puts(i8* dereferenceable(1) getelementptr inbounds ([124 x i8], [124 x i8]* @str.228, i64 0, i64 0))
%10 = tail call i32 @puts(i8* dereferenceable(1) getelementptr inbounds ([108 x i8], [108 x i8]* @str.229, i64 0, i64 0))
%11 = tail call i32 @puts(i8* dereferenceable(1) getelementptr inbounds ([81 x i8], [81 x i8]* @str.230, i64 0, i64 0))
%12 = tail call i32 @puts(i8* dereferenceable(1) getelementptr inbounds ([90 x i8], [90 x i8]* @str.231, i64 0, i64 0))
%13 = tail call i32 @puts(i8* dereferenceable(1) getelementptr inbounds ([52 x i8], [52 x i8]* @str.232, i64 0, i64 0))
%14 = tail call i32 @puts(i8* dereferenceable(1) getelementptr inbounds ([23 x i8], [23 x i8]* @str.233, i64 0, i64 0))
%15 = tail call i32 @puts(i8* dereferenceable(1) getelementptr inbounds ([86 x i8], [86 x i8]* @str.234, i64 0, i64 0))
%16 = tail call i32 @puts(i8* dereferenceable(1) getelementptr inbounds ([142 x i8], [142 x i8]* @str.235, i64 0, i64 0))
%17 = tail call i32 @puts(i8* dereferenceable(1) getelementptr inbounds ([97 x i8], [97 x i8]* @str.236, i64 0, i64 0))
%18 = tail call i32 @puts(i8* dereferenceable(1) getelementptr inbounds ([89 x i8], [89 x i8]* @str.237, i64 0, i64 0))
%19 = tail call i32 @puts(i8* dereferenceable(1) getelementptr inbounds ([45 x i8], [45 x i8]* @str.238, i64 0, i64 0))
%20 = tail call i32 @puts(i8* dereferenceable(1) getelementptr inbounds ([52 x i8], [52 x i8]* @str.239, i64 0, i64 0))
%21 = tail call i32 @puts(i8* dereferenceable(1) getelementptr inbounds ([70 x i8], [70 x i8]* @str.240, i64 0, i64 0))
%22 = tail call i32 @puts(i8* dereferenceable(1) getelementptr inbounds ([97 x i8], [97 x i8]* @str.241, i64 0, i64 0))
%23 = tail call i32 @puts(i8* dereferenceable(1) getelementptr inbounds ([97 x i8], [97 x i8]* @str.242, i64 0, i64 0))
%24 = tail call i32 @puts(i8* dereferenceable(1) getelementptr inbounds ([78 x i8], [78 x i8]* @str.243, i64 0, i64 0))
%25 = tail call i32 @puts(i8* dereferenceable(1) getelementptr inbounds ([51 x i8], [51 x i8]* @str.244, i64 0, i64 0))
%26 = tail call i32 @puts(i8* dereferenceable(1) getelementptr inbounds ([115 x i8], [115 x i8]* @str.245, i64 0, i64 0))
%27 = tail call i32 @puts(i8* dereferenceable(1) getelementptr inbounds ([128 x i8], [128 x i8]* @str.246, i64 0, i64 0))
%28 = tail call i32 @puts(i8* dereferenceable(1) getelementptr inbounds ([43 x i8], [43 x i8]* @str.247, i64 0, i64 0))
%29 = tail call i32 @puts(i8* dereferenceable(1) getelementptr inbounds ([102 x i8], [102 x i8]* @str.248, i64 0, i64 0))
%30 = tail call i32 @puts(i8* dereferenceable(1) getelementptr inbounds ([128 x i8], [128 x i8]* @str.249, i64 0, i64 0))
%31 = tail call i32 @puts(i8* dereferenceable(1) getelementptr inbounds ([133 x i8], [133 x i8]* @str.250, i64 0, i64 0))
%32 = tail call i32 @puts(i8* dereferenceable(1) getelementptr inbounds ([150 x i8], [150 x i8]* @str.251, i64 0, i64 0))
%33 = tail call i32 @puts(i8* dereferenceable(1) getelementptr inbounds ([35 x i8], [35 x i8]* @str.252, i64 0, i64 0))
%34 = tail call i32 @puts(i8* dereferenceable(1) getelementptr inbounds ([95 x i8], [95 x i8]* @str.253, i64 0, i64 0))
%35 = tail call i32 @puts(i8* dereferenceable(1) getelementptr inbounds ([88 x i8], [88 x i8]* @str.254, i64 0, i64 0))
%36 = tail call i32 @puts(i8* dereferenceable(1) getelementptr inbounds ([83 x i8], [83 x i8]* @str.255, i64 0, i64 0))
%37 = tail call i32 @puts(i8* dereferenceable(1) getelementptr inbounds ([104 x i8], [104 x i8]* @str.256, i64 0, i64 0))
%38 = tail call i32 @puts(i8* dereferenceable(1) getelementptr inbounds ([134 x i8], [134 x i8]* @str.257, i64 0, i64 0))
%39 = tail call i32 @puts(i8* dereferenceable(1) getelementptr inbounds ([28 x i8], [28 x i8]* @str.258, i64 0, i64 0))
%40 = tail call i32 @puts(i8* dereferenceable(1) getelementptr inbounds ([117 x i8], [117 x i8]* @str.259, i64 0, i64 0))
%41 = tail call i32 @puts(i8* dereferenceable(1) getelementptr inbounds ([131 x i8], [131 x i8]* @str.260, i64 0, i64 0))
%42 = tail call i32 @puts(i8* dereferenceable(1) getelementptr inbounds ([93 x i8], [93 x i8]* @str.261, i64 0, i64 0))
%43 = tail call i32 @puts(i8* dereferenceable(1) getelementptr inbounds ([73 x i8], [73 x i8]* @str.262, i64 0, i64 0))
%44 = tail call i32 @puts(i8* dereferenceable(1) getelementptr inbounds ([84 x i8], [84 x i8]* @str.263, i64 0, i64 0))
%45 = tail call i32 @puts(i8* dereferenceable(1) getelementptr inbounds ([81 x i8], [81 x i8]* @str.264, i64 0, i64 0))
%46 = tail call i32 @puts(i8* dereferenceable(1) getelementptr inbounds ([132 x i8], [132 x i8]* @str.265, i64 0, i64 0))
%47 = tail call i32 @puts(i8* dereferenceable(1) getelementptr inbounds ([116 x i8], [116 x i8]* @str.266, i64 0, i64 0))
%48 = tail call i32 @puts(i8* dereferenceable(1) getelementptr inbounds ([85 x i8], [85 x i8]* @str.267, i64 0, i64 0))
%49 = tail call i32 @puts(i8* dereferenceable(1) getelementptr inbounds ([91 x i8], [91 x i8]* @str.268, i64 0, i64 0))
%50 = tail call i32 @puts(i8* dereferenceable(1) getelementptr inbounds ([115 x i8], [115 x i8]* @str.269, i64 0, i64 0))
%51 = tail call i32 @puts(i8* dereferenceable(1) getelementptr inbounds ([116 x i8], [116 x i8]* @str.270, i64 0, i64 0))
%52 = tail call i32 @puts(i8* dereferenceable(1) getelementptr inbounds ([43 x i8], [43 x i8]* @str.271, i64 0, i64 0))
%53 = tail call i32 @puts(i8* dereferenceable(1) getelementptr inbounds ([73 x i8], [73 x i8]* @str.272, i64 0, i64 0))
%54 = tail call i32 @puts(i8* dereferenceable(1) getelementptr inbounds ([114 x i8], [114 x i8]* @str.273, i64 0, i64 0))
%55 = tail call i32 @puts(i8* dereferenceable(1) getelementptr inbounds ([86 x i8], [86 x i8]* @str.274, i64 0, i64 0))
%56 = tail call i32 @puts(i8* dereferenceable(1) getelementptr inbounds ([43 x i8], [43 x i8]* @str.275, i64 0, i64 0))
%57 = tail call i32 @puts(i8* dereferenceable(1) getelementptr inbounds ([130 x i8], [130 x i8]* @str.276, i64 0, i64 0))
%58 = tail call i32 @puts(i8* dereferenceable(1) getelementptr inbounds ([120 x i8], [120 x i8]* @str.277, i64 0, i64 0))
%59 = tail call i32 @puts(i8* dereferenceable(1) getelementptr inbounds ([128 x i8], [128 x i8]* @str.278, i64 0, i64 0))
%60 = tail call i32 @puts(i8* dereferenceable(1) getelementptr inbounds ([127 x i8], [127 x i8]* @str.279, i64 0, i64 0))
%61 = tail call i32 @puts(i8* dereferenceable(1) getelementptr inbounds ([113 x i8], [113 x i8]* @str.280, i64 0, i64 0))
%62 = tail call i32 @puts(i8* dereferenceable(1) getelementptr inbounds ([110 x i8], [110 x i8]* @str.281, i64 0, i64 0))
%63 = tail call i32 @puts(i8* dereferenceable(1) getelementptr inbounds ([69 x i8], [69 x i8]* @str.282, i64 0, i64 0))
%64 = tail call i32 @puts(i8* dereferenceable(1) getelementptr inbounds ([109 x i8], [109 x i8]* @str.283, i64 0, i64 0))
%65 = tail call i32 @puts(i8* dereferenceable(1) getelementptr inbounds ([123 x i8], [123 x i8]* @str.284, i64 0, i64 0))
%66 = tail call i32 @puts(i8* dereferenceable(1) getelementptr inbounds ([139 x i8], [139 x i8]* @str.285, i64 0, i64 0))
%67 = tail call i32 @puts(i8* dereferenceable(1) getelementptr inbounds ([127 x i8], [127 x i8]* @str.286, i64 0, i64 0))
%68 = tail call i32 @puts(i8* dereferenceable(1) getelementptr inbounds ([68 x i8], [68 x i8]* @str.287, i64 0, i64 0))
%69 = tail call i32 @puts(i8* dereferenceable(1) getelementptr inbounds ([125 x i8], [125 x i8]* @str.288, i64 0, i64 0))
%70 = tail call i32 @puts(i8* dereferenceable(1) getelementptr inbounds ([121 x i8], [121 x i8]* @str.289, i64 0, i64 0))
%71 = tail call i32 @puts(i8* dereferenceable(1) getelementptr inbounds ([56 x i8], [56 x i8]* @str.290, i64 0, i64 0))
%72 = tail call i32 @puts(i8* dereferenceable(1) getelementptr inbounds ([79 x i8], [79 x i8]* @str.291, i64 0, i64 0))
%73 = tail call i32 @puts(i8* dereferenceable(1) getelementptr inbounds ([40 x i8], [40 x i8]* @str.292, i64 0, i64 0))
%74 = tail call i32 @puts(i8* dereferenceable(1) getelementptr inbounds ([19 x i8], [19 x i8]* @str.293, i64 0, i64 0))
%75 = tail call i32 @puts(i8* dereferenceable(1) getelementptr inbounds ([83 x i8], [83 x i8]* @str.294, i64 0, i64 0))
%76 = tail call i32 @puts(i8* dereferenceable(1) getelementptr inbounds ([125 x i8], [125 x i8]* @str.295, i64 0, i64 0))
%77 = tail call i32 @puts(i8* dereferenceable(1) getelementptr inbounds ([74 x i8], [74 x i8]* @str.296, i64 0, i64 0))
%78 = tail call i32 @puts(i8* dereferenceable(1) getelementptr inbounds ([104 x i8], [104 x i8]* @str.297, i64 0, i64 0))
%79 = tail call i32 @puts(i8* dereferenceable(1) getelementptr inbounds ([63 x i8], [63 x i8]* @str.298, i64 0, i64 0))
%80 = tail call i32 @puts(i8* dereferenceable(1) getelementptr inbounds ([57 x i8], [57 x i8]* @str.299, i64 0, i64 0))
%81 = tail call i32 @puts(i8* dereferenceable(1) getelementptr inbounds ([88 x i8], [88 x i8]* @str.300, i64 0, i64 0))
%82 = tail call i32 @puts(i8* dereferenceable(1) getelementptr inbounds ([80 x i8], [80 x i8]* @str.301, i64 0, i64 0))
%83 = tail call i32 @puts(i8* dereferenceable(1) getelementptr inbounds ([79 x i8], [79 x i8]* @str.302, i64 0, i64 0))
%84 = tail call i32 @puts(i8* dereferenceable(1) getelementptr inbounds ([57 x i8], [57 x i8]* @str.303, i64 0, i64 0))
%85 = tail call i32 @puts(i8* dereferenceable(1) getelementptr inbounds ([126 x i8], [126 x i8]* @str.304, i64 0, i64 0))
%86 = tail call i32 @puts(i8* dereferenceable(1) getelementptr inbounds ([101 x i8], [101 x i8]* @str.305, i64 0, i64 0))
%87 = tail call i32 @puts(i8* dereferenceable(1) getelementptr inbounds ([100 x i8], [100 x i8]* @str.306, i64 0, i64 0))
%88 = tail call i32 @puts(i8* dereferenceable(1) getelementptr inbounds ([123 x i8], [123 x i8]* @str.307, i64 0, i64 0))
%89 = tail call i32 @puts(i8* dereferenceable(1) getelementptr inbounds ([100 x i8], [100 x i8]* @str.308, i64 0, i64 0))
%90 = tail call i32 @puts(i8* dereferenceable(1) getelementptr inbounds ([103 x i8], [103 x i8]* @str.309, i64 0, i64 0))
%91 = tail call i32 @puts(i8* dereferenceable(1) getelementptr inbounds ([121 x i8], [121 x i8]* @str.310, i64 0, i64 0))
%92 = tail call i32 @puts(i8* dereferenceable(1) getelementptr inbounds ([124 x i8], [124 x i8]* @str.311, i64 0, i64 0))
%93 = tail call i32 @puts(i8* dereferenceable(1) getelementptr inbounds ([123 x i8], [123 x i8]* @str.312, i64 0, i64 0))
%94 = tail call i32 @puts(i8* dereferenceable(1) getelementptr inbounds ([79 x i8], [79 x i8]* @str.313, i64 0, i64 0))
%95 = tail call i32 @puts(i8* dereferenceable(1) getelementptr inbounds ([107 x i8], [107 x i8]* @str.314, i64 0, i64 0))
%96 = tail call i32 @puts(i8* dereferenceable(1) getelementptr inbounds ([116 x i8], [116 x i8]* @str.315, i64 0, i64 0))
%97 = tail call i32 @puts(i8* dereferenceable(1) getelementptr inbounds ([96 x i8], [96 x i8]* @str.316, i64 0, i64 0))
%98 = tail call i32 @puts(i8* dereferenceable(1) getelementptr inbounds ([116 x i8], [116 x i8]* @str.317, i64 0, i64 0))
%99 = tail call i32 @puts(i8* dereferenceable(1) getelementptr inbounds ([170 x i8], [170 x i8]* @str.318, i64 0, i64 0))
%100 = tail call i32 @puts(i8* dereferenceable(1) getelementptr inbounds ([69 x i8], [69 x i8]* @str.319, i64 0, i64 0))
%101 = tail call i32 @puts(i8* dereferenceable(1) getelementptr inbounds ([63 x i8], [63 x i8]* @str.320, i64 0, i64 0))
%102 = tail call i32 @puts(i8* dereferenceable(1) getelementptr inbounds ([102 x i8], [102 x i8]* @str.321, i64 0, i64 0))
%103 = tail call i32 @puts(i8* dereferenceable(1) getelementptr inbounds ([103 x i8], [103 x i8]* @str.322, i64 0, i64 0))
%104 = tail call i32 @puts(i8* dereferenceable(1) getelementptr inbounds ([93 x i8], [93 x i8]* @str.323, i64 0, i64 0))
%105 = tail call i32 @puts(i8* dereferenceable(1) getelementptr inbounds ([77 x i8], [77 x i8]* @str.324, i64 0, i64 0))
%106 = tail call i32 @puts(i8* dereferenceable(1) getelementptr inbounds ([140 x i8], [140 x i8]* @str.325, i64 0, i64 0))
%107 = tail call i32 @puts(i8* dereferenceable(1) getelementptr inbounds ([120 x i8], [120 x i8]* @str.326, i64 0, i64 0))
%108 = tail call i32 @puts(i8* dereferenceable(1) getelementptr inbounds ([121 x i8], [121 x i8]* @str.327, i64 0, i64 0))
%109 = tail call i32 @puts(i8* dereferenceable(1) getelementptr inbounds ([133 x i8], [133 x i8]* @str.328, i64 0, i64 0))
%110 = tail call i32 @puts(i8* dereferenceable(1) getelementptr inbounds ([92 x i8], [92 x i8]* @str.329, i64 0, i64 0))
%111 = tail call i32 @puts(i8* dereferenceable(1) getelementptr inbounds ([134 x i8], [134 x i8]* @str.330, i64 0, i64 0))
%112 = tail call i32 @puts(i8* dereferenceable(1) getelementptr inbounds ([73 x i8], [73 x i8]* @str.331, i64 0, i64 0))
%113 = tail call i32 @puts(i8* dereferenceable(1) getelementptr inbounds ([102 x i8], [102 x i8]* @str.332, i64 0, i64 0))
%114 = tail call i32 @puts(i8* dereferenceable(1) getelementptr inbounds ([76 x i8], [76 x i8]* @str.333, i64 0, i64 0))
%115 = tail call i32 @puts(i8* dereferenceable(1) getelementptr inbounds ([48 x i8], [48 x i8]* @str.334, i64 0, i64 0))
%116 = tail call i32 @puts(i8* dereferenceable(1) getelementptr inbounds ([67 x i8], [67 x i8]* @str.335, i64 0, i64 0))
%117 = tail call i32 @puts(i8* dereferenceable(1) getelementptr inbounds ([67 x i8], [67 x i8]* @str.336, i64 0, i64 0))
%118 = tail call i32 @puts(i8* dereferenceable(1) getelementptr inbounds ([67 x i8], [67 x i8]* @str.337, i64 0, i64 0))
%119 = tail call i32 @puts(i8* dereferenceable(1) getelementptr inbounds ([128 x i8], [128 x i8]* @str.338, i64 0, i64 0))
%120 = tail call i32 @puts(i8* dereferenceable(1) getelementptr inbounds ([118 x i8], [118 x i8]* @str.339, i64 0, i64 0))
%121 = tail call i32 @puts(i8* dereferenceable(1) getelementptr inbounds ([85 x i8], [85 x i8]* @str.340, i64 0, i64 0))
%122 = tail call i32 @puts(i8* dereferenceable(1) getelementptr inbounds ([106 x i8], [106 x i8]* @str.341, i64 0, i64 0))
%123 = tail call i32 @puts(i8* dereferenceable(1) getelementptr inbounds ([125 x i8], [125 x i8]* @str.342, i64 0, i64 0))
%124 = tail call i32 @puts(i8* dereferenceable(1) getelementptr inbounds ([121 x i8], [121 x i8]* @str.343, i64 0, i64 0))
%125 = tail call i32 @puts(i8* dereferenceable(1) getelementptr inbounds ([111 x i8], [111 x i8]* @str.344, i64 0, i64 0))
%126 = tail call i32 @puts(i8* dereferenceable(1) getelementptr inbounds ([109 x i8], [109 x i8]* @str.345, i64 0, i64 0))
%127 = tail call i32 @puts(i8* dereferenceable(1) getelementptr inbounds ([53 x i8], [53 x i8]* @str.346, i64 0, i64 0))
%128 = tail call i32 @puts(i8* dereferenceable(1) getelementptr inbounds ([48 x i8], [48 x i8]* @str.347, i64 0, i64 0))
%129 = tail call i32 @puts(i8* dereferenceable(1) getelementptr inbounds ([39 x i8], [39 x i8]* @str.348, i64 0, i64 0))
%130 = tail call i32 @puts(i8* dereferenceable(1) getelementptr inbounds ([41 x i8], [41 x i8]* @str.349, i64 0, i64 0))
%131 = tail call i32 @puts(i8* dereferenceable(1) getelementptr inbounds ([52 x i8], [52 x i8]* @str.350, i64 0, i64 0))
%132 = tail call i32 @puts(i8* dereferenceable(1) getelementptr inbounds ([35 x i8], [35 x i8]* @str.351, i64 0, i64 0))
%133 = tail call i32 @puts(i8* dereferenceable(1) getelementptr inbounds ([68 x i8], [68 x i8]* @str.352, i64 0, i64 0))
%134 = tail call i32 @puts(i8* dereferenceable(1) getelementptr inbounds ([40 x i8], [40 x i8]* @str.353, i64 0, i64 0))
%135 = tail call i32 @puts(i8* dereferenceable(1) getelementptr inbounds ([44 x i8], [44 x i8]* @str.354, i64 0, i64 0))
%136 = tail call i32 @puts(i8* dereferenceable(1) getelementptr inbounds ([49 x i8], [49 x i8]* @str.355, i64 0, i64 0))
%137 = tail call i32 @puts(i8* dereferenceable(1) getelementptr inbounds ([51 x i8], [51 x i8]* @str.356, i64 0, i64 0))
%138 = tail call i32 @puts(i8* dereferenceable(1) getelementptr inbounds ([51 x i8], [51 x i8]* @str.357, i64 0, i64 0))
%139 = tail call i32 @puts(i8* dereferenceable(1) getelementptr inbounds ([52 x i8], [52 x i8]* @str.358, i64 0, i64 0))
%140 = tail call i32 @puts(i8* dereferenceable(1) getelementptr inbounds ([86 x i8], [86 x i8]* @str.359, i64 0, i64 0))
%141 = tail call i32 @puts(i8* dereferenceable(1) getelementptr inbounds ([71 x i8], [71 x i8]* @str.360, i64 0, i64 0))
%142 = tail call i32 @puts(i8* dereferenceable(1) getelementptr inbounds ([59 x i8], [59 x i8]* @str.361, i64 0, i64 0))
%143 = tail call i32 @puts(i8* dereferenceable(1) getelementptr inbounds ([61 x i8], [61 x i8]* @str.362, i64 0, i64 0))
%144 = tail call i32 @puts(i8* dereferenceable(1) getelementptr inbounds ([69 x i8], [69 x i8]* @str.363, i64 0, i64 0))
%145 = tail call i32 @puts(i8* dereferenceable(1) getelementptr inbounds ([53 x i8], [53 x i8]* @str.364, i64 0, i64 0))
%146 = tail call i32 @puts(i8* dereferenceable(1) getelementptr inbounds ([80 x i8], [80 x i8]* @str.365, i64 0, i64 0))
%147 = tail call i32 @puts(i8* dereferenceable(1) getelementptr inbounds ([49 x i8], [49 x i8]* @str.366, i64 0, i64 0))
%148 = tail call i32 @puts(i8* dereferenceable(1) getelementptr inbounds ([36 x i8], [36 x i8]* @str.367, i64 0, i64 0))
%149 = tail call i32 @puts(i8* dereferenceable(1) getelementptr inbounds ([36 x i8], [36 x i8]* @str.368, i64 0, i64 0))
%150 = tail call i32 @puts(i8* dereferenceable(1) getelementptr inbounds ([42 x i8], [42 x i8]* @str.369, i64 0, i64 0))
%151 = tail call i32 @puts(i8* dereferenceable(1) getelementptr inbounds ([56 x i8], [56 x i8]* @str.370, i64 0, i64 0))
%152 = tail call i32 @puts(i8* dereferenceable(1) getelementptr inbounds ([67 x i8], [67 x i8]* @str.371, i64 0, i64 0))
%153 = tail call i32 @puts(i8* dereferenceable(1) getelementptr inbounds ([67 x i8], [67 x i8]* @str.372, i64 0, i64 0))
%154 = tail call i32 @puts(i8* dereferenceable(1) getelementptr inbounds ([79 x i8], [79 x i8]* @str.373, i64 0, i64 0))
%155 = tail call i32 @puts(i8* dereferenceable(1) getelementptr inbounds ([72 x i8], [72 x i8]* @str.374, i64 0, i64 0))
%156 = tail call i32 @puts(i8* dereferenceable(1) getelementptr inbounds ([74 x i8], [74 x i8]* @str.375, i64 0, i64 0))
%157 = tail call i32 @puts(i8* dereferenceable(1) getelementptr inbounds ([124 x i8], [124 x i8]* @str.376, i64 0, i64 0))
%158 = tail call i32 @puts(i8* dereferenceable(1) getelementptr inbounds ([117 x i8], [117 x i8]* @str.377, i64 0, i64 0))
%159 = tail call i32 @puts(i8* dereferenceable(1) getelementptr inbounds ([113 x i8], [113 x i8]* @str.378, i64 0, i64 0))
%160 = tail call i32 @puts(i8* dereferenceable(1) getelementptr inbounds ([76 x i8], [76 x i8]* @str.379, i64 0, i64 0))
%161 = tail call i32 @puts(i8* dereferenceable(1) getelementptr inbounds ([29 x i8], [29 x i8]* @str.380, i64 0, i64 0))
%162 = tail call i32 @puts(i8* dereferenceable(1) getelementptr inbounds ([130 x i8], [130 x i8]* @str.381, i64 0, i64 0))
%163 = tail call i32 @puts(i8* dereferenceable(1) getelementptr inbounds ([110 x i8], [110 x i8]* @str.382, i64 0, i64 0))
%164 = tail call i32 @puts(i8* dereferenceable(1) getelementptr inbounds ([60 x i8], [60 x i8]* @str.383, i64 0, i64 0))
%165 = tail call i32 @puts(i8* dereferenceable(1) getelementptr inbounds ([70 x i8], [70 x i8]* @str.384, i64 0, i64 0))
%166 = tail call i32 @puts(i8* dereferenceable(1) getelementptr inbounds ([86 x i8], [86 x i8]* @str.385, i64 0, i64 0))
%167 = tail call i32 @puts(i8* dereferenceable(1) getelementptr inbounds ([81 x i8], [81 x i8]* @str.386, i64 0, i64 0))
%168 = tail call i32 @puts(i8* dereferenceable(1) getelementptr inbounds ([69 x i8], [69 x i8]* @str.387, i64 0, i64 0))
%169 = tail call i32 @puts(i8* dereferenceable(1) getelementptr inbounds ([109 x i8], [109 x i8]* @str.388, i64 0, i64 0))
%170 = tail call i32 @puts(i8* dereferenceable(1) getelementptr inbounds ([82 x i8], [82 x i8]* @str.389, i64 0, i64 0))
%171 = tail call i32 @puts(i8* dereferenceable(1) getelementptr inbounds ([81 x i8], [81 x i8]* @str.390, i64 0, i64 0))
%172 = tail call i32 @puts(i8* dereferenceable(1) getelementptr inbounds ([81 x i8], [81 x i8]* @str.391, i64 0, i64 0))
%173 = tail call i32 @puts(i8* dereferenceable(1) getelementptr inbounds ([74 x i8], [74 x i8]* @str.392, i64 0, i64 0))
%174 = tail call i32 @puts(i8* dereferenceable(1) getelementptr inbounds ([23 x i8], [23 x i8]* @str.393, i64 0, i64 0))
%175 = tail call i32 @puts(i8* dereferenceable(1) getelementptr inbounds ([72 x i8], [72 x i8]* @str.394, i64 0, i64 0))
%176 = tail call i32 @puts(i8* dereferenceable(1) getelementptr inbounds ([71 x i8], [71 x i8]* @str.395, i64 0, i64 0))
%177 = tail call i32 @puts(i8* dereferenceable(1) getelementptr inbounds ([119 x i8], [119 x i8]* @str.396, i64 0, i64 0))
%178 = tail call i32 @puts(i8* dereferenceable(1) getelementptr inbounds ([121 x i8], [121 x i8]* @str.397, i64 0, i64 0))
%179 = tail call i32 @puts(i8* dereferenceable(1) getelementptr inbounds ([115 x i8], [115 x i8]* @str.398, i64 0, i64 0))
%180 = tail call i32 @puts(i8* dereferenceable(1) getelementptr inbounds ([128 x i8], [128 x i8]* @str.399, i64 0, i64 0))
%181 = tail call i32 @puts(i8* dereferenceable(1) getelementptr inbounds ([106 x i8], [106 x i8]* @str.400, i64 0, i64 0))
%182 = tail call i32 @puts(i8* dereferenceable(1) getelementptr inbounds ([100 x i8], [100 x i8]* @str.401, i64 0, i64 0))
%183 = tail call i32 @puts(i8* dereferenceable(1) getelementptr inbounds ([11 x i8], [11 x i8]* @str.402, i64 0, i64 0))
%184 = tail call i32 @puts(i8* dereferenceable(1) getelementptr inbounds ([87 x i8], [87 x i8]* @str.403, i64 0, i64 0))
%185 = tail call i32 @puts(i8* dereferenceable(1) getelementptr inbounds ([43 x i8], [43 x i8]* @str.404, i64 0, i64 0))
%186 = tail call i32 @puts(i8* dereferenceable(1) getelementptr inbounds ([107 x i8], [107 x i8]* @str.405, i64 0, i64 0))
%187 = tail call i32 @puts(i8* dereferenceable(1) getelementptr inbounds ([109 x i8], [109 x i8]* @str.406, i64 0, i64 0))
%188 = tail call i32 @puts(i8* dereferenceable(1) getelementptr inbounds ([103 x i8], [103 x i8]* @str.407, i64 0, i64 0))
%189 = tail call i32 @puts(i8* dereferenceable(1) getelementptr inbounds ([63 x i8], [63 x i8]* @str.408, i64 0, i64 0))
%190 = tail call i32 @puts(i8* dereferenceable(1) getelementptr inbounds ([73 x i8], [73 x i8]* @str.409, i64 0, i64 0))
%191 = tail call i32 @puts(i8* dereferenceable(1) getelementptr inbounds ([97 x i8], [97 x i8]* @str.410, i64 0, i64 0))
%192 = tail call i32 @puts(i8* dereferenceable(1) getelementptr inbounds ([87 x i8], [87 x i8]* @str.411, i64 0, i64 0))
%193 = tail call i32 @puts(i8* dereferenceable(1) getelementptr inbounds ([89 x i8], [89 x i8]* @str.412, i64 0, i64 0))
%194 = tail call i32 @puts(i8* dereferenceable(1) getelementptr inbounds ([115 x i8], [115 x i8]* @str.413, i64 0, i64 0))
%195 = tail call i32 @puts(i8* dereferenceable(1) getelementptr inbounds ([90 x i8], [90 x i8]* @str.414, i64 0, i64 0))
%196 = tail call i32 @puts(i8* dereferenceable(1) getelementptr inbounds ([107 x i8], [107 x i8]* @str.415, i64 0, i64 0))
%197 = tail call i32 @puts(i8* dereferenceable(1) getelementptr inbounds ([72 x i8], [72 x i8]* @str.416, i64 0, i64 0))
%198 = tail call i32 @puts(i8* dereferenceable(1) getelementptr inbounds ([70 x i8], [70 x i8]* @str.417, i64 0, i64 0))
%199 = tail call i32 @puts(i8* dereferenceable(1) getelementptr inbounds ([44 x i8], [44 x i8]* @str.418, i64 0, i64 0))
%200 = tail call i32 @puts(i8* dereferenceable(1) getelementptr inbounds ([27 x i8], [27 x i8]* @str.419, i64 0, i64 0))
%201 = tail call i32 @puts(i8* dereferenceable(1) getelementptr inbounds ([101 x i8], [101 x i8]* @str.420, i64 0, i64 0))
%202 = tail call i32 @puts(i8* dereferenceable(1) getelementptr inbounds ([53 x i8], [53 x i8]* @str.421, i64 0, i64 0))
%203 = tail call i32 @puts(i8* dereferenceable(1) getelementptr inbounds ([154 x i8], [154 x i8]* @str.422, i64 0, i64 0))
%204 = tail call i32 @puts(i8* dereferenceable(1) getelementptr inbounds ([47 x i8], [47 x i8]* @str.423, i64 0, i64 0))
%205 = tail call i32 @puts(i8* dereferenceable(1) getelementptr inbounds ([93 x i8], [93 x i8]* @str.424, i64 0, i64 0))
%206 = tail call i32 @puts(i8* dereferenceable(1) getelementptr inbounds ([105 x i8], [105 x i8]* @str.425, i64 0, i64 0))
%207 = tail call i32 @puts(i8* dereferenceable(1) getelementptr inbounds ([101 x i8], [101 x i8]* @str.426, i64 0, i64 0))
%208 = tail call i32 @puts(i8* dereferenceable(1) getelementptr inbounds ([97 x i8], [97 x i8]* @str.427, i64 0, i64 0))
%209 = tail call i32 @puts(i8* dereferenceable(1) getelementptr inbounds ([96 x i8], [96 x i8]* @str.428, i64 0, i64 0))
%210 = tail call i32 @puts(i8* dereferenceable(1) getelementptr inbounds ([52 x i8], [52 x i8]* @str.429, i64 0, i64 0))
%211 = tail call i32 @puts(i8* dereferenceable(1) getelementptr inbounds ([29 x i8], [29 x i8]* @str.430, i64 0, i64 0))
%212 = tail call i32 @puts(i8* dereferenceable(1) getelementptr inbounds ([90 x i8], [90 x i8]* @str.431, i64 0, i64 0))
%213 = tail call i32 @puts(i8* dereferenceable(1) getelementptr inbounds ([90 x i8], [90 x i8]* @str.432, i64 0, i64 0))
%214 = tail call i32 @puts(i8* dereferenceable(1) getelementptr inbounds ([90 x i8], [90 x i8]* @str.433, i64 0, i64 0))
%215 = tail call i32 @puts(i8* dereferenceable(1) getelementptr inbounds ([90 x i8], [90 x i8]* @str.434, i64 0, i64 0))
%216 = tail call i32 @puts(i8* dereferenceable(1) getelementptr inbounds ([90 x i8], [90 x i8]* @str.435, i64 0, i64 0))
%217 = tail call i32 @puts(i8* dereferenceable(1) getelementptr inbounds ([29 x i8], [29 x i8]* @str.436, i64 0, i64 0))
%218 = tail call i32 @puts(i8* dereferenceable(1) getelementptr inbounds ([82 x i8], [82 x i8]* @str.437, i64 0, i64 0))
%219 = tail call i32 @puts(i8* dereferenceable(1) getelementptr inbounds ([39 x i8], [39 x i8]* @str.438, i64 0, i64 0))
%220 = tail call i32 @puts(i8* dereferenceable(1) getelementptr inbounds ([50 x i8], [50 x i8]* @str.439, i64 0, i64 0))
%221 = tail call i32 @puts(i8* dereferenceable(1) getelementptr inbounds ([85 x i8], [85 x i8]* @str.440, i64 0, i64 0))
ret void
}