From e35b1c9376872278d838e4140fa0941555a59b83 Mon Sep 17 00:00:00 2001
From: Daniel Weindl <dweindl@users.noreply.github.com>
Date: Fri, 15 Oct 2021 07:15:56 +0200
Subject: [PATCH 01/17] Update Valgrind suppressions (#1569)

* Ignore pandas extension leaks
* Ignore PyTuple_New
---
 .github/workflows/test_valgrind.yml |  2 +-
 python/tests/valgrind-python.supp   | 14 ++++++++++++--
 2 files changed, 13 insertions(+), 3 deletions(-)

diff --git a/.github/workflows/test_valgrind.yml b/.github/workflows/test_valgrind.yml
index cd47d30757..3a0f3a1eed 100644
--- a/.github/workflows/test_valgrind.yml
+++ b/.github/workflows/test_valgrind.yml
@@ -3,7 +3,7 @@ on:
   push:
     branches:
       - master
-      - feature_cpp_hierarchical_derivatives
+      - update_valgrind_supp
   pull_request:
     branches:
       - master
diff --git a/python/tests/valgrind-python.supp b/python/tests/valgrind-python.supp
index 10e33a4de1..fc4fdfdeba 100644
--- a/python/tests/valgrind-python.supp
+++ b/python/tests/valgrind-python.supp
@@ -391,9 +391,9 @@
    match-leak-kinds: definite
    fun:malloc
    obj:/usr/bin/python3.?
+   ...
    fun:PyTuple_New
-   fun:_PyEval_EvalCodeWithName
-   fun:_PyFunction_Vectorcall
+   ...
 }
 
 {
@@ -440,3 +440,13 @@
    fun:dlopen_doit
    fun:_dl_catch_exception
 }
+
+{
+   Pandas
+   Memcheck:Leak
+   match-leak-kinds: definite
+   fun:malloc
+   ...
+   obj:*site-packages/pandas/_libs/*.cpython-3*-x86_64-linux-gnu.so
+   ...
+}

From c3fa68b37a79977f7a9f18484f8b2ff76d9c812a Mon Sep 17 00:00:00 2001
From: Daniel Weindl <dweindl@users.noreply.github.com>
Date: Fri, 15 Oct 2021 19:52:56 +0200
Subject: [PATCH 02/17] Update documentation stack (#1527)

* RTD with Ubuntu20.04
* Recent doxygen with various bugfixed
* Updates sphinx, breathe, ...
* Stick to Python 3.8 on RTD, because with 3.9:
```
Traceback (most recent call last):
  File "/home/docs/checkouts/readthedocs.org/user_builds/amici/envs/1527/lib/python3.9/site-packages/sphinx/cmd/build.py", line 276, in build_main
    app = Sphinx(args.sourcedir, args.confdir, args.outputdir,
  File "/home/docs/checkouts/readthedocs.org/user_builds/amici/envs/1527/lib/python3.9/site-packages/sphinx/application.py", line 237, in __init__
    self.setup_extension(extension)
  File "/home/docs/checkouts/readthedocs.org/user_builds/amici/envs/1527/lib/python3.9/site-packages/sphinx/application.py", line 393, in setup_extension
    self.registry.load_extension(self, extname)
  File "/home/docs/checkouts/readthedocs.org/user_builds/amici/envs/1527/lib/python3.9/site-packages/sphinx/registry.py", line 442, in load_extension
    metadata = setup(app)
  File "/home/docs/checkouts/readthedocs.org/user_builds/amici/envs/1527/lib/python3.9/site-packages/recommonmark/__init__.py", line 9, in setup
    from .parser import CommonMarkParser
  File "/home/docs/checkouts/readthedocs.org/user_builds/amici/envs/1527/lib/python3.9/site-packages/recommonmark/parser.py", line 9, in <module>
    from commonmark import Parser
  File "/home/docs/checkouts/readthedocs.org/user_builds/amici/envs/1527/lib/python3.9/site-packages/commonmark/__init__.py", line 4, in <module>
    from commonmark.main import commonmark
  File "/home/docs/checkouts/readthedocs.org/user_builds/amici/envs/1527/lib/python3.9/site-packages/commonmark/main.py", line 14, in <module>
    from commonmark.blocks import Parser
  File "/home/docs/checkouts/readthedocs.org/user_builds/amici/envs/1527/lib/python3.9/site-packages/commonmark/blocks.py", line 5, in <module>
    from commonmark import common
  File "/home/docs/checkouts/readthedocs.org/user_builds/amici/envs/1527/lib/python3.9/site-packages/commonmark/common.py", line 14, in <module>
    HTMLunescape = html.parser.HTMLParser().unescape
AttributeError: 'HTMLParser' object has no attribute 'unescape'

Exception occurred:
  File "/home/docs/checkouts/readthedocs.org/user_builds/amici/envs/1527/lib/python3.9/site-packages/commonmark/common.py", line 14, in <module>
    HTMLunescape = html.parser.HTMLParser().unescape
AttributeError: 'HTMLParser' object has no attribute 'unescape'
```
---
 .readthedocs.yml                   | 15 ++++++-------
 documentation/conf.py              | 35 ++++++++++++++++++++++++++++--
 documentation/rtd_requirements.txt | 21 +++++++++---------
 3 files changed, 50 insertions(+), 21 deletions(-)

diff --git a/.readthedocs.yml b/.readthedocs.yml
index ef19ad6d86..3e75f7dc84 100644
--- a/.readthedocs.yml
+++ b/.readthedocs.yml
@@ -11,19 +11,18 @@ sphinx:
   configuration: documentation/conf.py
   fail_on_warning: True
 
-# Build documentation with MkDocs
-#mkdocs:
-#  configuration: mkdocs.yml
-
-# Optionally build your docs in additional formats such as PDF and ePub
 formats:
   - pdf
 
-# Optionally set the version of Python and requirements required to build your docs
 python:
-  version: 3.8
   install:
     - requirements: documentation/rtd_requirements.txt
 
 build:
-  image: latest
+  os: "ubuntu-20.04"
+  apt_packages:
+    # for custom doxygen
+    - libclang-cpp9
+    - libclang1-9
+  tools:
+    python: "3.8"
diff --git a/documentation/conf.py b/documentation/conf.py
index 90c8c17cb7..de30887b3a 100644
--- a/documentation/conf.py
+++ b/documentation/conf.py
@@ -94,7 +94,7 @@ def install_amici_deps_rtd():
     cmd = (f"cd '{os.path.join(amici_dir, 'ThirdParty')}' "
            "&& apt download libatlas-base-dev && mkdir libatlas-base-dev "
            "&& cd libatlas-base-dev "
-           "&& ar x ../libatlas-base-dev_3.10.3-5_amd64.deb "
+           "&& ar x ../libatlas-base-dev_3.10.3-8ubuntu7_amd64.deb "
            "&& tar -xJf data.tar.xz "
            f"&& ln -s {cblas_inc_dir}/cblas-atlas.h {cblas_inc_dir}/cblas.h "
            )
@@ -113,6 +113,28 @@ def install_amici_deps_rtd():
     os.environ['SWIG'] = os.path.join(swig_dir, 'swig')
 
 
+def install_doxygen():
+    """Get a more recent doxygen"""
+    version = '1.9.1'
+    doxygen_exe = os.path.join(amici_dir, 'ThirdParty',
+                               f'doxygen-{version}', 'bin', 'doxygen')
+    # to create a symlink to doxygen in a location that is already on PATH
+    some_dir_on_path = os.environ['PATH'].split(os.pathsep)[0]
+    cmd = (
+        f"cd '{os.path.join(amici_dir, 'ThirdParty')}' "
+        f"&& wget 'https://doxygen.nl/files/"
+        f"doxygen-{version}.linux.bin.tar.gz' "
+        f"&& tar -xzf doxygen-{version}.linux.bin.tar.gz "
+        f"&& ln -s '{doxygen_exe}' '{some_dir_on_path}'"
+    )
+    subprocess.run(cmd, shell=True, check=True)
+    assert os.path.islink(os.path.join(some_dir_on_path, 'doxygen'))
+    # verify it's available
+    res = subprocess.run(['doxygen', '--version'],
+                         check=False, capture_output=True)
+    print(res.stdout.decode(), res.stderr.decode())
+    assert version in res.stdout.decode()
+
 # -- Path setup --------------------------------------------------------------
 
 # If extensions (or modules to document with autodoc) are in another directory,
@@ -127,6 +149,7 @@ def install_amici_deps_rtd():
 # only execute those commands when running from RTD
 if 'READTHEDOCS' in os.environ and os.environ['READTHEDOCS']:
     install_amici_deps_rtd()
+    install_doxygen()
 
 # Required for matlab doxygen processing
 install_mtocpp()
@@ -298,7 +321,15 @@ def install_amici_deps_rtd():
         "exhaleDoxygenStdin": "\n".join([
             "INPUT = ../include",
             "BUILTIN_STL_SUPPORT    = YES",
-            "PREDEFINED            += EXHALE_DOXYGEN_SHOULD_SKIP_THIS"
+            "PREDEFINED            += EXHALE_DOXYGEN_SHOULD_SKIP_THIS",
+            "EXCLUDE += ../include/amici/interface_matlab.h",
+            "EXCLUDE += ../include/amici/returndata_matlab.h",
+            "EXCLUDE += ../include/amici/spline.h",
+            # amici::log collides with amici::${some_enum}::log
+            #  potentially fixed in
+            #  https://github.com/svenevs/exhale/commit/c924df2e139a09fbacd07587779c55fd0ee4e00b
+            #  and can be un-excluded after the next exhale release
+            "EXCLUDE += ../include/amici/symbolic_functions.h",
         ]),
         "containmentFolder": "_exhale_cpp_api",
         "rootFileTitle": "AMICI C++ API",
diff --git a/documentation/rtd_requirements.txt b/documentation/rtd_requirements.txt
index 154f12a9dc..a97d743172 100644
--- a/documentation/rtd_requirements.txt
+++ b/documentation/rtd_requirements.txt
@@ -1,24 +1,23 @@
-sphinx==3.2.1
+sphinx==4.2.0
 mock>=4.0.1
 setuptools>=45.2.0
 pysb>=1.11.0
-matplotlib>=3.1.3
-pkgconfig>=1.5.1
-nbsphinx>=0.5.1
+matplotlib>=3.4.3
+pkgconfig>=1.5.5
+nbsphinx>=0.8.7
 recommonmark>=0.6.0
-sphinx_rtd_theme>=0.4.3
-petab>=0.1.5
+sphinx_rtd_theme>=1.0.0
+petab>=0.1.20
 sphinx-autodoc-typehints>=1.10.3
 git+https://github.com/readthedocs/sphinx-hoverxref@master
-prompt-toolkit<=3.0.0
-ipython>=7.17.0
-breathe==4.25.1
+ipython>=7.28.0
+breathe==4.31.0
 #exhale>=0.2.3
 git+https://github.com/dweindl/exhale@ea77a313777c1382a7830ce9ee6c405ce47f5f3b#egg=exhale
 # Newer versions cause trouble with including notebooks:
 # sphinx.errors.SphinxParallelError: ImportError: cannot import name 'Application' from partially initialized module 'prompt_toolkit.application.application' (most likely due to a circular import)
 # https://github.com/svenevs/exhale/issues/27 https://github.com/mithro/sphinx-contrib-mithro/tree/master/sphinx-contrib-exhale-multiproject
 -e git+https://github.com/mithro/sphinx-contrib-mithro#egg=sphinx-contrib-exhale-multiproject&subdirectory=sphinx-contrib-exhale-multiproject
-sphinxcontrib-matlabdomain
+sphinxcontrib-matlabdomain>=0.12.0
 sphinxcontrib-napoleon
-pygments==2.7.4
+pygments==2.10.0

From 28e8fab31adfac9e77d0dbcefebcdf169b4252a2 Mon Sep 17 00:00:00 2001
From: Daniel Weindl <dweindl@users.noreply.github.com>
Date: Fri, 15 Oct 2021 23:42:55 +0200
Subject: [PATCH 03/17] Remove matlab reports (#1572)

... which were probably inadvertently included a long time ago...
---
 .../example_adjoint/html/example_adjoint.html | 316 -------------
 .../example_adjoint/html/example_adjoint.png  | Bin 652 -> 0 bytes
 .../example_adjoint/html/example_adjoint.tex  | 169 -------
 .../html/example_adjoint_01.png               | Bin 19635 -> 0 bytes
 .../html/example_adjoint_02.png               | Bin 18080 -> 0 bytes
 .../html/model_adjoint_syms.html              | 156 -------
 .../html/model_adjoint_syms.tex               |  84 ----
 .../example_dirac/html/example_dirac.html     | 396 ----------------
 .../example_dirac/html/example_dirac.png      | Bin 1985 -> 0 bytes
 .../example_dirac/html/example_dirac.tex      | 226 ---------
 .../example_dirac/html/example_dirac_01.png   | Bin 32827 -> 0 bytes
 .../example_dirac/html/example_dirac_02.png   | Bin 44488 -> 0 bytes
 .../example_dirac/html/example_dirac_03.png   | Bin 37451 -> 0 bytes
 .../example_dirac/html/model_dirac_syms.html  | 159 -------
 .../example_dirac/html/model_dirac_syms.tex   |  86 ----
 .../html/example_dirac_adjoint.html           | 232 ---------
 .../html/example_dirac_adjoint.png            | Bin 659 -> 0 bytes
 .../html/example_dirac_adjoint.tex            | 126 -----
 .../html/example_dirac_adjoint_01.png         | Bin 18743 -> 0 bytes
 .../html/example_dirac_adjoint_02.png         | Bin 16955 -> 0 bytes
 .../html/model_dirac_adjoint_syms.html        | 161 -------
 .../html/model_dirac_adjoint_syms.tex         |  86 ----
 .../html/example_dirac_secondorder.html       | 242 ----------
 .../html/example_dirac_secondorder.png        | Bin 2493 -> 0 bytes
 .../html/example_dirac_secondorder.tex        | 140 ------
 .../html/example_dirac_secondorder_01.png     | Bin 36896 -> 0 bytes
 .../html/example_dirac_secondorder_02.png     | Bin 34408 -> 0 bytes
 .../html/model_dirac_secondorder_syms.html    | 159 -------
 .../html/model_dirac_secondorder_syms.tex     |  86 ----
 .../example_dirac_secondorder_vectmult.html   | 288 ------------
 .../example_dirac_secondorder_vectmult.png    | Bin 1945 -> 0 bytes
 .../example_dirac_secondorder_vectmult.tex    | 163 -------
 .../example_dirac_secondorder_vectmult_01.png | Bin 43461 -> 0 bytes
 .../example_dirac_secondorder_vectmult_02.png | Bin 36542 -> 0 bytes
 ...model_dirac_secondorder_vectmult_syms.html | 159 -------
 .../model_dirac_secondorder_vectmult_syms.tex |  86 ----
 .../example_events/html/example_events.html   | 441 ------------------
 .../example_events/html/example_events.png    | Bin 1842 -> 0 bytes
 .../example_events/html/example_events.tex    | 251 ----------
 .../example_events/html/example_events_01.png | Bin 39236 -> 0 bytes
 .../example_events/html/example_events_02.png | Bin 66469 -> 0 bytes
 .../example_events/html/example_events_03.png | Bin 47809 -> 0 bytes
 .../example_events/html/example_events_04.png | Bin 33765 -> 0 bytes
 .../html/model_events_syms.html               | 207 --------
 .../example_events/html/model_events_syms.tex | 116 -----
 .../html/example_jakstat_adjoint.html         | 259 ----------
 .../html/example_jakstat_adjoint.png          | Bin 686 -> 0 bytes
 .../html/example_jakstat_adjoint.tex          | 127 -----
 .../html/example_jakstat_adjoint_01.png       | Bin 22090 -> 0 bytes
 .../html/example_jakstat_adjoint_02.png       | Bin 17784 -> 0 bytes
 .../html/model_jakstat_adjoint_syms.html      | 186 --------
 .../html/model_jakstat_adjoint_syms.tex       | 109 -----
 .../html/example_steadystate.html             | 391 ----------------
 .../html/example_steadystate.png              | Bin 754 -> 0 bytes
 .../html/example_steadystate.tex              | 230 ---------
 .../html/example_steadystate_01.png           | Bin 26877 -> 0 bytes
 .../html/example_steadystate_02.png           | Bin 55522 -> 0 bytes
 .../html/example_steadystate_03.png           | Bin 61349 -> 0 bytes
 .../html/example_steadystate_04.png           | Bin 18751 -> 0 bytes
 .../html/model_steadystate_syms.html          | 180 -------
 .../html/model_steadystate_syms.tex           |  98 ----
 61 files changed, 6115 deletions(-)
 delete mode 100644 matlab/examples/example_adjoint/html/example_adjoint.html
 delete mode 100644 matlab/examples/example_adjoint/html/example_adjoint.png
 delete mode 100644 matlab/examples/example_adjoint/html/example_adjoint.tex
 delete mode 100644 matlab/examples/example_adjoint/html/example_adjoint_01.png
 delete mode 100644 matlab/examples/example_adjoint/html/example_adjoint_02.png
 delete mode 100644 matlab/examples/example_adjoint/html/model_adjoint_syms.html
 delete mode 100644 matlab/examples/example_adjoint/html/model_adjoint_syms.tex
 delete mode 100644 matlab/examples/example_dirac/html/example_dirac.html
 delete mode 100644 matlab/examples/example_dirac/html/example_dirac.png
 delete mode 100644 matlab/examples/example_dirac/html/example_dirac.tex
 delete mode 100644 matlab/examples/example_dirac/html/example_dirac_01.png
 delete mode 100644 matlab/examples/example_dirac/html/example_dirac_02.png
 delete mode 100644 matlab/examples/example_dirac/html/example_dirac_03.png
 delete mode 100644 matlab/examples/example_dirac/html/model_dirac_syms.html
 delete mode 100644 matlab/examples/example_dirac/html/model_dirac_syms.tex
 delete mode 100644 matlab/examples/example_dirac_adjoint/html/example_dirac_adjoint.html
 delete mode 100644 matlab/examples/example_dirac_adjoint/html/example_dirac_adjoint.png
 delete mode 100644 matlab/examples/example_dirac_adjoint/html/example_dirac_adjoint.tex
 delete mode 100644 matlab/examples/example_dirac_adjoint/html/example_dirac_adjoint_01.png
 delete mode 100644 matlab/examples/example_dirac_adjoint/html/example_dirac_adjoint_02.png
 delete mode 100644 matlab/examples/example_dirac_adjoint/html/model_dirac_adjoint_syms.html
 delete mode 100644 matlab/examples/example_dirac_adjoint/html/model_dirac_adjoint_syms.tex
 delete mode 100644 matlab/examples/example_dirac_secondorder/html/example_dirac_secondorder.html
 delete mode 100644 matlab/examples/example_dirac_secondorder/html/example_dirac_secondorder.png
 delete mode 100644 matlab/examples/example_dirac_secondorder/html/example_dirac_secondorder.tex
 delete mode 100644 matlab/examples/example_dirac_secondorder/html/example_dirac_secondorder_01.png
 delete mode 100644 matlab/examples/example_dirac_secondorder/html/example_dirac_secondorder_02.png
 delete mode 100644 matlab/examples/example_dirac_secondorder/html/model_dirac_secondorder_syms.html
 delete mode 100644 matlab/examples/example_dirac_secondorder/html/model_dirac_secondorder_syms.tex
 delete mode 100644 matlab/examples/example_dirac_secondorder_vectmult/html/example_dirac_secondorder_vectmult.html
 delete mode 100644 matlab/examples/example_dirac_secondorder_vectmult/html/example_dirac_secondorder_vectmult.png
 delete mode 100644 matlab/examples/example_dirac_secondorder_vectmult/html/example_dirac_secondorder_vectmult.tex
 delete mode 100644 matlab/examples/example_dirac_secondorder_vectmult/html/example_dirac_secondorder_vectmult_01.png
 delete mode 100644 matlab/examples/example_dirac_secondorder_vectmult/html/example_dirac_secondorder_vectmult_02.png
 delete mode 100644 matlab/examples/example_dirac_secondorder_vectmult/html/model_dirac_secondorder_vectmult_syms.html
 delete mode 100644 matlab/examples/example_dirac_secondorder_vectmult/html/model_dirac_secondorder_vectmult_syms.tex
 delete mode 100644 matlab/examples/example_events/html/example_events.html
 delete mode 100644 matlab/examples/example_events/html/example_events.png
 delete mode 100644 matlab/examples/example_events/html/example_events.tex
 delete mode 100644 matlab/examples/example_events/html/example_events_01.png
 delete mode 100644 matlab/examples/example_events/html/example_events_02.png
 delete mode 100644 matlab/examples/example_events/html/example_events_03.png
 delete mode 100644 matlab/examples/example_events/html/example_events_04.png
 delete mode 100644 matlab/examples/example_events/html/model_events_syms.html
 delete mode 100644 matlab/examples/example_events/html/model_events_syms.tex
 delete mode 100644 matlab/examples/example_jakstat_adjoint/html/example_jakstat_adjoint.html
 delete mode 100644 matlab/examples/example_jakstat_adjoint/html/example_jakstat_adjoint.png
 delete mode 100644 matlab/examples/example_jakstat_adjoint/html/example_jakstat_adjoint.tex
 delete mode 100644 matlab/examples/example_jakstat_adjoint/html/example_jakstat_adjoint_01.png
 delete mode 100644 matlab/examples/example_jakstat_adjoint/html/example_jakstat_adjoint_02.png
 delete mode 100644 matlab/examples/example_jakstat_adjoint/html/model_jakstat_adjoint_syms.html
 delete mode 100644 matlab/examples/example_jakstat_adjoint/html/model_jakstat_adjoint_syms.tex
 delete mode 100644 matlab/examples/example_steadystate/html/example_steadystate.html
 delete mode 100644 matlab/examples/example_steadystate/html/example_steadystate.png
 delete mode 100644 matlab/examples/example_steadystate/html/example_steadystate.tex
 delete mode 100644 matlab/examples/example_steadystate/html/example_steadystate_01.png
 delete mode 100644 matlab/examples/example_steadystate/html/example_steadystate_02.png
 delete mode 100644 matlab/examples/example_steadystate/html/example_steadystate_03.png
 delete mode 100644 matlab/examples/example_steadystate/html/example_steadystate_04.png
 delete mode 100644 matlab/examples/example_steadystate/html/model_steadystate_syms.html
 delete mode 100644 matlab/examples/example_steadystate/html/model_steadystate_syms.tex

diff --git a/matlab/examples/example_adjoint/html/example_adjoint.html b/matlab/examples/example_adjoint/html/example_adjoint.html
deleted file mode 100644
index 24fe24b409..0000000000
--- a/matlab/examples/example_adjoint/html/example_adjoint.html
+++ /dev/null
@@ -1,316 +0,0 @@
-
-<!DOCTYPE html
-  PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN">
-<html><head>
-      <meta http-equiv="Content-Type" content="text/html; charset=utf-8">
-   <!--
-This HTML was auto-generated from MATLAB code.
-To make changes, update the MATLAB code and republish this document.
-      --><title>example_adjoint</title><meta name="generator" content="MATLAB 9.0"><link rel="schema.DC" href="http://purl.org/dc/elements/1.1/"><meta name="DC.date" content="2016-05-04"><meta name="DC.source" content="example_adjoint.m"><style type="text/css">
-html,body,div,span,applet,object,iframe,h1,h2,h3,h4,h5,h6,p,blockquote,pre,a,abbr,acronym,address,big,cite,code,del,dfn,em,font,img,ins,kbd,q,s,samp,small,strike,strong,sub,sup,tt,var,b,u,i,center,dl,dt,dd,ol,ul,li,fieldset,form,label,legend,table,caption,tbody,tfoot,thead,tr,th,td{margin:0;padding:0;border:0;outline:0;font-size:100%;vertical-align:baseline;background:transparent}body{line-height:1}ol,ul{list-style:none}blockquote,q{quotes:none}blockquote:before,blockquote:after,q:before,q:after{content:'';content:none}:focus{outine:0}ins{text-decoration:none}del{text-decoration:line-through}table{border-collapse:collapse;border-spacing:0}
-
-html { min-height:100%; margin-bottom:1px; }
-html body { height:100%; margin:0px; font-family:Arial, Helvetica, sans-serif; font-size:10px; color:#000; line-height:140%; background:#fff none; overflow-y:scroll; }
-html body td { vertical-align:top; text-align:left; }
-
-h1 { padding:0px; margin:0px 0px 25px; font-family:Arial, Helvetica, sans-serif; font-size:1.5em; color:#d55000; line-height:100%; font-weight:normal; }
-h2 { padding:0px; margin:0px 0px 8px; font-family:Arial, Helvetica, sans-serif; font-size:1.2em; color:#000; font-weight:bold; line-height:140%; border-bottom:1px solid #d6d4d4; display:block; }
-h3 { padding:0px; margin:0px 0px 5px; font-family:Arial, Helvetica, sans-serif; font-size:1.1em; color:#000; font-weight:bold; line-height:140%; }
-
-a { color:#005fce; text-decoration:none; }
-a:hover { color:#005fce; text-decoration:underline; }
-a:visited { color:#004aa0; text-decoration:none; }
-
-p { padding:0px; margin:0px 0px 20px; }
-img { padding:0px; margin:0px 0px 20px; border:none; }
-p img, pre img, tt img, li img, h1 img, h2 img { margin-bottom:0px; } 
-
-ul { padding:0px; margin:0px 0px 20px 23px; list-style:square; }
-ul li { padding:0px; margin:0px 0px 7px 0px; }
-ul li ul { padding:5px 0px 0px; margin:0px 0px 7px 23px; }
-ul li ol li { list-style:decimal; }
-ol { padding:0px; margin:0px 0px 20px 0px; list-style:decimal; }
-ol li { padding:0px; margin:0px 0px 7px 23px; list-style-type:decimal; }
-ol li ol { padding:5px 0px 0px; margin:0px 0px 7px 0px; }
-ol li ol li { list-style-type:lower-alpha; }
-ol li ul { padding-top:7px; }
-ol li ul li { list-style:square; }
-
-.content { font-size:1.2em; line-height:140%; padding: 20px; }
-
-pre, code { font-size:12px; }
-tt { font-size: 1.2em; }
-pre { margin:0px 0px 20px; }
-pre.codeinput { padding:10px; border:1px solid #d3d3d3; background:#f7f7f7; }
-pre.codeoutput { padding:10px 11px; margin:0px 0px 20px; color:#4c4c4c; }
-pre.error { color:red; }
-
-@media print { pre.codeinput, pre.codeoutput { word-wrap:break-word; width:100%; } }
-
-span.keyword { color:#0000FF }
-span.comment { color:#228B22 }
-span.string { color:#A020F0 }
-span.untermstring { color:#B20000 }
-span.syscmd { color:#B28C00 }
-
-.footer { width:auto; padding:10px 0px; margin:25px 0px 0px; border-top:1px dotted #878787; font-size:0.8em; line-height:140%; font-style:italic; color:#878787; text-align:left; float:none; }
-.footer p { margin:0px; }
-.footer a { color:#878787; }
-.footer a:hover { color:#878787; text-decoration:underline; }
-.footer a:visited { color:#878787; }
-
-table th { padding:7px 5px; text-align:left; vertical-align:middle; border: 1px solid #d6d4d4; font-weight:bold; }
-table td { padding:7px 5px; text-align:left; vertical-align:top; border:1px solid #d6d4d4; }
-
-
-
-
-
-  </style></head><body><div class="content"><pre class="codeinput"><span class="keyword">function</span> example_adjoint()
-</pre><p>COMPILATION</p><pre class="codeinput">    [exdir,~,~]=fileparts(which(<span class="string">'example_adjoint.m'</span>));
-    <span class="comment">% compile the model</span>
-    amiwrap(<span class="string">'model_adjoint'</span>,<span class="string">'model_adjoint_syms'</span>,exdir)
-</pre><pre class="codeoutput">Generating model struct ...
-Parsing model struct ...
-Generating C code ...
-headers | wrapfunctions | Compiling mex file ...
-amici | Building with 'Xcode with Clang'.
-MEX completed successfully.
-Building with 'Xcode with Clang'.
-MEX completed successfully.
-</pre><p>SIMULATION</p><pre class="codeinput">    <span class="comment">% time vector</span>
-    t = [linspace(0,4,5)];
-    p = [1.1,0.3,1];
-    k = [];
-
-    D.Y = [     1.0171
-        1.3423
-        1.6585
-        0.9814
-        0.3288];
-
-    D.Sigma_Y = 0.1*ones(size(D.Y));
-
-
-    options.sensi = 1;
-    options.sensi_meth = <span class="string">'adjoint'</span>;
-    options.maxsteps = 1e4;
-    options.rtol = 1e-12;
-    options.atol = 1e-12;
-    <span class="comment">% load mex into memory</span>
-    [~] = which(<span class="string">'simulate_model_adjoint'</span>); <span class="comment">% fix for inaccessability problems</span>
-    sol = simulate_model_adjoint(t,log10(p),k,D,options);
-</pre><p>Plot</p><pre class="codeinput">    figure
-    subplot(3,1,1)
-    errorbar(t,D.Y,D.Sigma_Y)
-    hold <span class="string">on</span>
-    <span class="comment">% plot(t,sol.y)</span>
-
-    xlabel(<span class="string">'time t'</span>)
-    ylabel(<span class="string">'observable'</span>)
-    title([<span class="string">'log-likelihood: '</span> num2str(sol.llh) ])
-
-    y = (p(2)*t + p(3)).*(t&lt;2) + ( (2*p(2)+p(3)-p(2)/p(1))*exp(-p(1)*(t-2))+p(2)/p(1) ).*(t&gt;=2);
-
-
-    tfine = linspace(0,4,100001);
-    xfine = (p(2)*tfine + 1).*(tfine&lt;2) + ( (2*p(2)+p(3)-p(2)/p(1))*exp(-p(1)*(tfine-2))+p(2)/p(1) ).*(tfine&gt;=2);
-
-    mu = zeros(1,length(tfine));
-    <span class="keyword">for</span> it = 1:length(t)
-        <span class="keyword">if</span>(t(it)&lt;=2)
-            mu = mu + ((y(it)-D.Y(it))/(D.Sigma_Y(it)^2))*(tfine&lt;=t(it));
-        <span class="keyword">else</span>
-            mu = mu + ((y(it)-D.Y(it))/(D.Sigma_Y(it)^2))*exp(p(1)*(tfine-t(it))).*(tfine&lt;=t(it)).*(tfine&gt;2) + ((y(it)-D.Y(it))/(D.Sigma_Y(it)^2))*exp(p(1)*(2-t(it))).*(tfine&lt;t(it)).*(tfine&lt;=2);
-        <span class="keyword">end</span>
-    <span class="keyword">end</span>
-    plot(tfine,xfine)
-    legend(<span class="string">'data'</span>,<span class="string">'simulation'</span>)
-    xlim([min(t)-0.5,max(t)+0.5])
-    subplot(3,1,2)
-    plot(tfine,mu)
-    ylabel(<span class="string">'adjoint'</span>)
-    xlabel(<span class="string">'time t'</span>)
-    xlim([min(t)-0.5,max(t)+0.5])
-
-    subplot(3,1,3)
-
-    plot(fliplr(tfine),-cumsum(fliplr(-mu.*xfine.*(tfine&gt;2)))*p(1)*log(10)*(t(end)/numel(tfine)))
-    hold <span class="string">on</span>
-    plot(fliplr(tfine),-cumsum(fliplr(mu))*p(2)*log(10)*(t(end)/numel(tfine)))
-    plot(tfine,-mu(1)*p(3)*log(10)*(tfine&lt;2))
-    xlim([min(t)-0.5,max(t)+0.5])
-    ylabel(<span class="string">'integral'</span>)
-    xlabel(<span class="string">'time t'</span>)
-
-    legend(<span class="string">'p1'</span>,<span class="string">'p2'</span>,<span class="string">'p3'</span>)
-
-    grad(1,1) = -trapz(tfine,-mu.*xfine.*(tfine&gt;2))*p(1)*log(10);
-    grad(2,1) = -trapz(tfine,mu)*p(2)*log(10);
-    grad(3,1) = -mu(1)*p(3)*log(10);
-
-    plot(zeros(3,1),grad,<span class="string">'ko'</span>)
-</pre><img vspace="5" hspace="5" src="../examples/example_adjoint/html/example_adjoint_01.png" alt=""> <p>FD</p><pre class="codeinput">    eps = 1e-5;
-    xi = log10(p);
-    grad_fd_f = NaN(3,1);
-    grad_fd_b = NaN(3,1);
-    <span class="keyword">for</span> ip = 1:3;
-        options.sensi = 0;
-        xip = xi;
-        xip(ip) = xip(ip) + eps;
-        solp = simulate_model_adjoint(t,xip,k,D,options);
-        grad_fd_f(ip,1) = (solp.llh-sol.llh)/eps;
-        xip = xi;
-        xip(ip) = xip(ip) - eps;
-        solp = simulate_model_adjoint(t,xip,k,D,options);
-        grad_fd_b(ip,1) = -(solp.llh-sol.llh)/eps;
-    <span class="keyword">end</span>
-
-    figure
-    plot(abs(grad),abs(grad_fd_f),<span class="string">'o'</span>)
-    hold <span class="string">on</span>
-    plot(abs(grad),abs(grad_fd_b),<span class="string">'o'</span>)
-    plot(abs(grad),mean([abs(grad_fd_b),abs(grad_fd_f)],2),<span class="string">'o'</span>)
-    plot(abs(grad),abs(sol.sllh),<span class="string">'o'</span>)
-    plot([1e1,1e2],[1e1,1e2],<span class="string">'k:'</span>)
-    set(gca,<span class="string">'XScale'</span>,<span class="string">'log'</span>)
-    set(gca,<span class="string">'YScale'</span>,<span class="string">'log'</span>)
-    axis <span class="string">square</span>
-    legend(<span class="string">'forward FD'</span>,<span class="string">'backward FD'</span>,<span class="string">'central FD'</span>,<span class="string">'adjoint sensintivity analysis'</span>,<span class="string">'Location'</span>,<span class="string">'SouthEast'</span>)
-    xlabel(<span class="string">'analytic absolute value of gradient element'</span>)
-    ylabel(<span class="string">'computed absolute value of gradient element'</span>)
-    set(gcf,<span class="string">'Position'</span>,[100 300 1200 500])
-
-    drawnow
-</pre><img vspace="5" hspace="5" src="../examples/example_adjoint/html/example_adjoint_02.png" alt=""> <pre class="codeinput"><span class="keyword">end</span>
-</pre><p class="footer"><br><a href="http://www.mathworks.com/products/matlab/">Published with MATLAB&reg; R2016a</a><br></p></div><!--
-##### SOURCE BEGIN #####
-function example_adjoint()
-    
-    %%
-    % COMPILATION
-    
-    [exdir,~,~]=fileparts(which('example_adjoint.m'));
-    % compile the model
-    amiwrap('model_adjoint','model_adjoint_syms',exdir)
-    
-    %%
-    % SIMULATION
-    
-    % time vector
-    t = [linspace(0,4,5)];
-    p = [1.1,0.3,1];
-    k = [];
-    
-    D.Y = [     1.0171
-        1.3423
-        1.6585
-        0.9814
-        0.3288];
-    
-    D.Sigma_Y = 0.1*ones(size(D.Y));
-    
-    
-    options.sensi = 1;
-    options.sensi_meth = 'adjoint';
-    options.maxsteps = 1e4;
-    options.rtol = 1e-12;
-    options.atol = 1e-12;
-    % load mex into memory
-    [~] = which('simulate_model_adjoint'); % fix for inaccessability problems
-    sol = simulate_model_adjoint(t,log10(p),k,D,options);
-    
-    %%
-    % Plot
-    
-    figure
-    subplot(3,1,1)
-    errorbar(t,D.Y,D.Sigma_Y)
-    hold on
-    % plot(t,sol.y)
-    
-    xlabel('time t')
-    ylabel('observable')
-    title(['log-likelihood: ' num2str(sol.llh) ])
-    
-    y = (p(2)*t + p(3)).*(t<2) + ( (2*p(2)+p(3)-p(2)/p(1))*exp(-p(1)*(t-2))+p(2)/p(1) ).*(t>=2);
-    
-    
-    tfine = linspace(0,4,100001);
-    xfine = (p(2)*tfine + 1).*(tfine<2) + ( (2*p(2)+p(3)-p(2)/p(1))*exp(-p(1)*(tfine-2))+p(2)/p(1) ).*(tfine>=2);
-    
-    mu = zeros(1,length(tfine));
-    for it = 1:length(t)
-        if(t(it)<=2)
-            mu = mu + ((y(it)-D.Y(it))/(D.Sigma_Y(it)^2))*(tfine<=t(it));
-        else
-            mu = mu + ((y(it)-D.Y(it))/(D.Sigma_Y(it)^2))*exp(p(1)*(tfine-t(it))).*(tfine<=t(it)).*(tfine>2) + ((y(it)-D.Y(it))/(D.Sigma_Y(it)^2))*exp(p(1)*(2-t(it))).*(tfine<t(it)).*(tfine<=2);
-        end
-    end
-    plot(tfine,xfine)
-    legend('data','simulation')
-    xlim([min(t)-0.5,max(t)+0.5])
-    subplot(3,1,2)
-    plot(tfine,mu)
-    ylabel('adjoint')
-    xlabel('time t')
-    xlim([min(t)-0.5,max(t)+0.5])
-    
-    subplot(3,1,3)
-    
-    plot(fliplr(tfine),-cumsum(fliplr(-mu.*xfine.*(tfine>2)))*p(1)*log(10)*(t(end)/numel(tfine)))
-    hold on
-    plot(fliplr(tfine),-cumsum(fliplr(mu))*p(2)*log(10)*(t(end)/numel(tfine)))
-    plot(tfine,-mu(1)*p(3)*log(10)*(tfine<2))
-    xlim([min(t)-0.5,max(t)+0.5])
-    ylabel('integral')
-    xlabel('time t')
-    
-    legend('p1','p2','p3')
-    
-    grad(1,1) = -trapz(tfine,-mu.*xfine.*(tfine>2))*p(1)*log(10);
-    grad(2,1) = -trapz(tfine,mu)*p(2)*log(10);
-    grad(3,1) = -mu(1)*p(3)*log(10);
-    
-    plot(zeros(3,1),grad,'ko')
-    
-    %%
-    % FD
-    
-    eps = 1e-5;
-    xi = log10(p);
-    grad_fd_f = NaN(3,1);
-    grad_fd_b = NaN(3,1);
-    for ip = 1:3;
-        options.sensi = 0;
-        xip = xi;
-        xip(ip) = xip(ip) + eps;
-        solp = simulate_model_adjoint(t,xip,k,D,options);
-        grad_fd_f(ip,1) = (solp.llh-sol.llh)/eps;
-        xip = xi;
-        xip(ip) = xip(ip) - eps;
-        solp = simulate_model_adjoint(t,xip,k,D,options);
-        grad_fd_b(ip,1) = -(solp.llh-sol.llh)/eps;
-    end
-    
-    figure
-    plot(abs(grad),abs(grad_fd_f),'o')
-    hold on
-    plot(abs(grad),abs(grad_fd_b),'o')
-    plot(abs(grad),mean([abs(grad_fd_b),abs(grad_fd_f)],2),'o')
-    plot(abs(grad),abs(sol.sllh),'o')
-    plot([1e1,1e2],[1e1,1e2],'k:')
-    set(gca,'XScale','log')
-    set(gca,'YScale','log')
-    axis square
-    legend('forward FD','backward FD','central FD','adjoint sensintivity analysis','Location','SouthEast')
-    xlabel('analytic absolute value of gradient element')
-    ylabel('computed absolute value of gradient element')
-    set(gcf,'Position',[100 300 1200 500])
-    
-    drawnow
-    
-end
-
-##### SOURCE END #####
---></body></html>
\ No newline at end of file
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diff --git a/matlab/examples/example_adjoint/html/example_adjoint.tex b/matlab/examples/example_adjoint/html/example_adjoint.tex
deleted file mode 100644
index 02eeb858ac..0000000000
--- a/matlab/examples/example_adjoint/html/example_adjoint.tex
+++ /dev/null
@@ -1,169 +0,0 @@
-
-% This LaTeX was auto-generated from MATLAB code.
-% To make changes, update the MATLAB code and republish this document.
-
-
-
-
-
-
-
-
-
-
-
-    
-    \begin{DoxyCode}
-function example_adjoint()
-\end{DoxyCode}
-\begin{par}
-COMPILATION
-\end{par} \vspace{1em}
-\begin{DoxyCode}
-    [exdir,~,~]=fileparts(which('example_adjoint.m'));
-    % compile the model
-    amiwrap('model_adjoint','model_adjoint_syms',exdir)
-\end{DoxyCode}
-
-         \begin{DoxyCode}Generating model struct ...
-Parsing model struct ...
-
-Generating C code ...
-headers | wrapfunctions | 
-Compiling mex file ...
-amici | Building with 'Xcode with Clang'.
-MEX completed successfully.
-Building with 'Xcode with Clang'.
-MEX completed successfully.
-\end{DoxyCode} 
-    \begin{par}
-SIMULATION
-\end{par} \vspace{1em}
-\begin{DoxyCode}
-    % time vector
-    t = [linspace(0,4,5)];
-    p = [1.1,0.3,1];
-    k = [];
-
-    D.Y = [     1.0171
-        1.3423
-        1.6585
-        0.9814
-        0.3288];
-
-    D.Sigma_Y = 0.1*ones(size(D.Y));
-
-
-    options.sensi = 1;
-    options.sensi_meth = 'adjoint';
-    options.maxsteps = 1e4;
-    options.rtol = 1e-12;
-    options.atol = 1e-12;
-    % load mex into memory
-    [~] = which('simulate_model_adjoint'); % fix for inaccessability problems
-    sol = simulate_model_adjoint(t,log10(p),k,D,options);
-\end{DoxyCode}
-\begin{par}
-Plot
-\end{par} \vspace{1em}
-\begin{DoxyCode}
-    figure
-    subplot(3,1,1)
-    errorbar(t,D.Y,D.Sigma_Y)
-    hold on
-    % plot(t,sol.y)
-
-    xlabel('time t')
-    ylabel('observable')
-    title(['log-likelihood: ' num2str(sol.llh) ])
-
-    y = (p(2)*t + p(3)).*(t<2) + ( (2*p(2)+p(3)-p(2)/p(1))*exp(-p(1)*(t-2))+p(2)/p(1) ).*(t>=2);
-
-
-    tfine = linspace(0,4,100001);
-    xfine = (p(2)*tfine + 1).*(tfine<2) + ( (2*p(2)+p(3)-p(2)/p(1))*exp(-p(1)*(tfine-2))+p(2)/p(1) ).*(tfine>=2);
-
-    mu = zeros(1,length(tfine));
-    for it = 1:length(t)
-        if(t(it)<=2)
-            mu = mu + ((y(it)-D.Y(it))/(D.Sigma_Y(it)^2))*(tfine<=t(it));
-        else
-            mu = mu + ((y(it)-D.Y(it))/(D.Sigma_Y(it)^2))*exp(p(1)*(tfine-t(it))).*(tfine<=t(it)).*(tfine>2) + ((y(it)-D.Y(it))/(D.Sigma_Y(it)^2))*exp(p(1)*(2-t(it))).*(tfine<t(it)).*(tfine<=2);
-        end
-    end
-    plot(tfine,xfine)
-    legend('data','simulation')
-    xlim([min(t)-0.5,max(t)+0.5])
-    subplot(3,1,2)
-    plot(tfine,mu)
-    ylabel('adjoint')
-    xlabel('time t')
-    xlim([min(t)-0.5,max(t)+0.5])
-
-    subplot(3,1,3)
-
-    plot(fliplr(tfine),-cumsum(fliplr(-mu.*xfine.*(tfine>2)))*p(1)*log(10)*(t(end)/numel(tfine)))
-    hold on
-    plot(fliplr(tfine),-cumsum(fliplr(mu))*p(2)*log(10)*(t(end)/numel(tfine)))
-    plot(tfine,-mu(1)*p(3)*log(10)*(tfine<2))
-    xlim([min(t)-0.5,max(t)+0.5])
-    ylabel('integral')
-    xlabel('time t')
-
-    legend('p1','p2','p3')
-
-    grad(1,1) = -trapz(tfine,-mu.*xfine.*(tfine>2))*p(1)*log(10);
-    grad(2,1) = -trapz(tfine,mu)*p(2)*log(10);
-    grad(3,1) = -mu(1)*p(3)*log(10);
-
-    plot(zeros(3,1),grad,'ko')
-\end{DoxyCode}
-
-\includegraphics[width=\textwidth]{../../examples/example_adjoint/html/example_adjoint_01.png}
-\begin{par}
-FD
-\end{par} \vspace{1em}
-\begin{DoxyCode}
-    eps = 1e-5;
-    xi = log10(p);
-    grad_fd_f = NaN(3,1);
-    grad_fd_b = NaN(3,1);
-    for ip = 1:3;
-        options.sensi = 0;
-        xip = xi;
-        xip(ip) = xip(ip) + eps;
-        solp = simulate_model_adjoint(t,xip,k,D,options);
-        grad_fd_f(ip,1) = (solp.llh-sol.llh)/eps;
-        xip = xi;
-        xip(ip) = xip(ip) - eps;
-        solp = simulate_model_adjoint(t,xip,k,D,options);
-        grad_fd_b(ip,1) = -(solp.llh-sol.llh)/eps;
-    end
-
-    figure
-    plot(abs(grad),abs(grad_fd_f),'o')
-    hold on
-    plot(abs(grad),abs(grad_fd_b),'o')
-    plot(abs(grad),mean([abs(grad_fd_b),abs(grad_fd_f)],2),'o')
-    plot(abs(grad),abs(sol.sllh),'o')
-    plot([1e1,1e2],[1e1,1e2],'k:')
-    set(gca,'XScale','log')
-    set(gca,'YScale','log')
-    axis square
-    legend('forward FD','backward FD','central FD','adjoint sensintivity analysis','Location','SouthEast')
-    xlabel('analytic absolute value of gradient element')
-    ylabel('computed absolute value of gradient element')
-    set(gcf,'Position',[100 300 1200 500])
-
-    drawnow
-\end{DoxyCode}
-
-\includegraphics[width=\textwidth]{../../examples/example_adjoint/html/example_adjoint_02.png}
-\begin{DoxyCode}
-end
-\end{DoxyCode}
-
-
-
-
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\ No newline at end of file
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-
-
-
-
-
-  </style></head><body><div class="content"><pre class="codeinput"><span class="keyword">function</span> [model] = model_adjoint_syms()
-</pre><p>STATES</p><pre class="codeinput"><span class="comment">% create state syms</span>
-syms <span class="string">x1</span>
-
-<span class="comment">% create state vector</span>
-model.sym.x = [x1];
-</pre><p>PARAMETERS ( for these sensitivities will be computed )</p><pre class="codeinput"><span class="comment">% create parameter syms</span>
-syms <span class="string">p1</span> <span class="string">p2</span> <span class="string">p3</span>
-
-<span class="comment">% create parameter vector</span>
-model.sym.p = [p1 p2 p3];
-
-
-<span class="comment">% set the parametrisation of the problem options are 'log', 'log10' and</span>
-<span class="comment">% 'lin' (default).</span>
-model.param = <span class="string">'log10'</span>;
-</pre><p>SYSTEM EQUATIONS</p><pre class="codeinput"><span class="comment">% create symbolic variable for time</span>
-syms <span class="string">t</span>
-
-model.sym.xdot = sym(zeros(size(model.sym.x)));
-
-<span class="comment">% piecewise defined function</span>
-model.sym.xdot(1) = -p1*x1*heaviside(t-2) + p2;
-</pre><p>INITIAL CONDITIONS</p><pre class="codeinput">model.sym.x0 = sym(zeros(size(model.sym.x)));
-
-model.sym.x0(1) = p3;
-</pre><p>OBSERVALES</p><pre class="codeinput">model.sym.y = sym(zeros(1,1));
-
-model.sym.y(1) = x1;
-</pre><pre class="codeinput"><span class="keyword">end</span>
-</pre><pre class="codeoutput">ans = 
-      sym: [1x1 struct]
-    param: 'log10'
-</pre><p class="footer"><br><a href="http://www.mathworks.com/products/matlab/">Published with MATLAB&reg; R2016a</a><br></p></div><!--
-##### SOURCE BEGIN #####
-function [model] = model_adjoint_syms()
-
-%%
-% STATES
-
-% create state syms
-syms x1
-
-% create state vector
-model.sym.x = [x1];
-
-%%
-% PARAMETERS ( for these sensitivities will be computed )
-
-% create parameter syms
-syms p1 p2 p3 
-
-% create parameter vector 
-model.sym.p = [p1 p2 p3];
-
-
-% set the parametrisation of the problem options are 'log', 'log10' and
-% 'lin' (default).
-model.param = 'log10';
-
-%%
-% SYSTEM EQUATIONS
-
-% create symbolic variable for time
-syms t
-
-model.sym.xdot = sym(zeros(size(model.sym.x)));
-
-% piecewise defined function
-model.sym.xdot(1) = -p1*x1*heaviside(t-2) + p2;
-
-%%
-% INITIAL CONDITIONS
-
-model.sym.x0 = sym(zeros(size(model.sym.x)));
-
-model.sym.x0(1) = p3;
-
-%%
-% OBSERVALES
-
-model.sym.y = sym(zeros(1,1));
-
-model.sym.y(1) = x1;
-
-end
-##### SOURCE END #####
---></body></html>
\ No newline at end of file
diff --git a/matlab/examples/example_adjoint/html/model_adjoint_syms.tex b/matlab/examples/example_adjoint/html/model_adjoint_syms.tex
deleted file mode 100644
index 93fd135d16..0000000000
--- a/matlab/examples/example_adjoint/html/model_adjoint_syms.tex
+++ /dev/null
@@ -1,84 +0,0 @@
-
-% This LaTeX was auto-generated from MATLAB code.
-% To make changes, update the MATLAB code and republish this document.
-
-
-
-
-
-
-
-
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-
-
-    
-    \begin{DoxyCode}
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-\end{par} \vspace{1em}
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-% create state syms
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-
-% create state vector
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-PARAMETERS ( for these sensitivities will be computed )
-\end{par} \vspace{1em}
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-% create parameter syms
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-
-% create parameter vector
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-
-
-% set the parametrisation of the problem options are 'log', 'log10' and
-% 'lin' (default).
-model.param = 'log10';
-\end{DoxyCode}
-\begin{par}
-SYSTEM EQUATIONS
-\end{par} \vspace{1em}
-\begin{DoxyCode}
-% create symbolic variable for time
-syms t
-
-model.sym.xdot = sym(zeros(size(model.sym.x)));
-
-% piecewise defined function
-model.sym.xdot(1) = -p1*x1*heaviside(t-2) + p2;
-\end{DoxyCode}
-\begin{par}
-INITIAL CONDITIONS
-\end{par} \vspace{1em}
-\begin{DoxyCode}
-model.sym.x0 = sym(zeros(size(model.sym.x)));
-
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-\begin{DoxyCode}
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-      sym: [1x1 struct]
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\ No newline at end of file
diff --git a/matlab/examples/example_dirac/html/example_dirac.html b/matlab/examples/example_dirac/html/example_dirac.html
deleted file mode 100644
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--- a/matlab/examples/example_dirac/html/example_dirac.html
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-.footer { width:auto; padding:10px 0px; margin:25px 0px 0px; border-top:1px dotted #878787; font-size:0.8em; line-height:140%; font-style:italic; color:#878787; text-align:left; float:none; }
-.footer p { margin:0px; }
-.footer a { color:#878787; }
-.footer a:hover { color:#878787; text-decoration:underline; }
-.footer a:visited { color:#878787; }
-
-table th { padding:7px 5px; text-align:left; vertical-align:middle; border: 1px solid #d6d4d4; font-weight:bold; }
-table td { padding:7px 5px; text-align:left; vertical-align:top; border:1px solid #d6d4d4; }
-
-
-
-
-
-  </style></head><body><div class="content"><pre class="codeinput"><span class="keyword">function</span> example_dirac()
-</pre><p>COMPILATION</p><pre class="codeinput">    [exdir,~,~]=fileparts(which(<span class="string">'example_dirac.m'</span>));
-    <span class="comment">% compile the model</span>
-    amiwrap(<span class="string">'model_dirac'</span>,<span class="string">'model_dirac_syms'</span>,exdir)
-</pre><pre class="codeoutput">Generating model struct ...
-Parsing model struct ...
-Generating C code ...
-headers | wrapfunctions | Compiling mex file ...
-amici | Building with 'Xcode with Clang'.
-MEX completed successfully.
-Building with 'Xcode with Clang'.
-MEX completed successfully.
-</pre><p>SIMULATION</p><pre class="codeinput">    <span class="comment">% time vector</span>
-    t = linspace(0,3,1001);
-    p = [1;0.5;2;3];
-    k = [];
-
-    options = amioption(<span class="string">'sensi'</span>,0,<span class="keyword">...</span>
-        <span class="string">'maxsteps'</span>,1e4);
-
-    <span class="comment">% load mex into memory</span>
-    [msg] = which(<span class="string">'simulate_model_dirac'</span>); <span class="comment">% fix for inaccessability problems</span>
-    sol = simulate_model_dirac(t,log10(p),k,[],options);
-
-    tic
-    sol = simulate_model_dirac(t,log10(p),k,[],options);
-    disp([<span class="string">'Time elapsed with amiwrap: '</span> num2str(toc) ])
-</pre><pre class="codeoutput">Time elapsed with amiwrap: 0.0049341
-</pre><p>ODE15S</p><pre class="codeinput">    sig = 1e-2;
-    delta_num = @(tau) exp(-1/2*(tau/sig).^2)/(sqrt(2*pi)*sig);
-
-    ode_system = @(t,x,p,k) [-p(1)*x(1)+delta_num(t-p(2));
-        +p(3)*x(1) - p(4)*x(2)];
-
-    options_ode45 = odeset(<span class="string">'RelTol'</span>,options.rtol,<span class="string">'AbsTol'</span>,options.atol,<span class="string">'MaxStep'</span>,options.maxsteps);
-
-    tic
-    [~, X_ode45] = ode45(@(t,x) ode_system(t,x,p,k),t,[0;0],options_ode45);
-    disp([<span class="string">'Time elapsed with ode45: '</span> num2str(toc) ])
-</pre><pre class="codeoutput">Time elapsed with ode45: 0.097728
-</pre><p>PLOTTING</p><pre class="codeinput">    figure
-    c_x = get(gca,<span class="string">'ColorOrder'</span>);
-    subplot(2,2,1)
-    <span class="keyword">for</span> ix = 1:size(sol.x,2)
-        plot(t,sol.x(:,ix),<span class="string">'.-'</span>,<span class="string">'Color'</span>,c_x(ix,:))
-        hold <span class="string">on</span>
-        plot(t,X_ode45(:,ix),<span class="string">'--'</span>,<span class="string">'Color'</span>,c_x(ix,:))
-    <span class="keyword">end</span>
-
-    legend(<span class="string">'x1'</span>,<span class="string">'x1_{ode45}'</span>,<span class="string">'x2'</span>,<span class="string">'x2_{ode15s}'</span>,<span class="string">'Location'</span>,<span class="string">'NorthEastOutside'</span>)
-    legend <span class="string">boxoff</span>
-    xlabel(<span class="string">'time t'</span>)
-    ylabel(<span class="string">'x'</span>)
-    box <span class="string">on</span>
-    subplot(2,2,2)
-    plot(t,abs(sol.x-X_ode45),<span class="string">'--'</span>)
-    set(gca,<span class="string">'YScale'</span>,<span class="string">'log'</span>)
-    ylim([1e-10,1e0])
-    legend(<span class="string">'error x1'</span>,<span class="string">'error x2'</span>,<span class="string">'Location'</span>,<span class="string">'NorthEastOutside'</span>)
-    legend <span class="string">boxoff</span>
-
-    subplot(2,2,3)
-    plot(t,sol.y,<span class="string">'.-'</span>,<span class="string">'Color'</span>,c_x(1,:))
-    hold <span class="string">on</span>
-    plot(t,X_ode45(:,2),<span class="string">'--'</span>,<span class="string">'Color'</span>,c_x(1,:))
-    legend(<span class="string">'y1'</span>,<span class="string">'y1_{ode45}'</span>,<span class="string">'Location'</span>,<span class="string">'NorthEastOutside'</span>)
-    legend <span class="string">boxoff</span>
-    xlabel(<span class="string">'time t'</span>)
-    ylabel(<span class="string">'y'</span>)
-    box <span class="string">on</span>
-
-    subplot(2,2,4)
-    plot(t,abs(sol.y-X_ode45(:,2)),<span class="string">'--'</span>)
-    set(gca,<span class="string">'YScale'</span>,<span class="string">'log'</span>)
-    ylim([1e-10,1e0])
-    legend(<span class="string">'error y1'</span>,<span class="string">'Location'</span>,<span class="string">'NorthEastOutside'</span>)
-    legend <span class="string">boxoff</span>
-    xlabel(<span class="string">'time t'</span>)
-    ylabel(<span class="string">'y'</span>)
-    box <span class="string">on</span>
-    set(gcf,<span class="string">'Position'</span>,[100 300 1200 500])
-</pre><img vspace="5" hspace="5" src="../examples/example_dirac/html/example_dirac_01.png" alt=""> <p>FORWARD SENSITIVITY ANALYSIS</p><pre class="codeinput">    options.sensi = 1;
-
-    sol = simulate_model_dirac(t,log10(p),k,[],options);
-</pre><p>FINITE DIFFERENCES</p><pre class="codeinput">    eps = 1e-4;
-    xi = log10(p);
-    <span class="keyword">for</span> ip = 1:4;
-        xip = xi;
-        xip(ip) = xip(ip) + eps;
-        solp = simulate_model_dirac(t,xip,k,[],options);
-        sx_fd(:,:,ip) = (solp.x - sol.x)/eps;
-        sy_fd(:,:,ip) = (solp.y - sol.y)/eps;
-    <span class="keyword">end</span>
-</pre><p>PLOTTING</p><pre class="codeinput">    figure
-    <span class="keyword">for</span> ip = 1:4
-        subplot(4,2,ip*2-1)
-        hold <span class="string">on</span>
-        <span class="keyword">for</span> ix = 1:size(sol.x,2)
-            plot(t,sol.sx(:,ix,ip),<span class="string">'.-'</span>,<span class="string">'Color'</span>,c_x(ix,:))
-            plot(t,sx_fd(:,ix,ip),<span class="string">'--'</span>,<span class="string">'Color'</span>,c_x(ix,:))
-        <span class="keyword">end</span>
-        ylim([-2,2])
-        legend(<span class="string">'x1'</span>,<span class="string">'x1_{fd}'</span>,<span class="string">'x2'</span>,<span class="string">'x2_{fd}'</span>,<span class="string">'Location'</span>,<span class="string">'NorthEastOutside'</span>)
-        legend <span class="string">boxoff</span>
-        title([<span class="string">'state sensitivity for p'</span> num2str(ip)])
-        xlabel(<span class="string">'time t'</span>)
-        ylabel(<span class="string">'x'</span>)
-        box <span class="string">on</span>
-
-        subplot(4,2,ip*2)
-        plot(t,abs(sol.sx(:,:,ip)-sx_fd(:,:,ip)),<span class="string">'r--'</span>)
-        legend(<span class="string">'error x1'</span>,<span class="string">'error x2'</span>,<span class="string">'Location'</span>,<span class="string">'NorthEastOutside'</span>)
-        legend <span class="string">boxoff</span>
-        title([<span class="string">'state sensitivity for p'</span> num2str(ip)])
-        xlabel(<span class="string">'time t'</span>)
-        ylabel(<span class="string">'error'</span>)
-        ylim([1e-12,1e0])
-        set(gca,<span class="string">'YScale'</span>,<span class="string">'log'</span>)
-        box <span class="string">on</span>
-    <span class="keyword">end</span>
-    set(gcf,<span class="string">'Position'</span>,[100 300 1200 500])
-
-    figure
-    <span class="keyword">for</span> ip = 1:4
-        subplot(4,2,ip*2-1)
-        hold <span class="string">on</span>
-        <span class="keyword">for</span> iy = 1:size(sol.y,2)
-            plot(t,sol.sy(:,iy,ip),<span class="string">'.-'</span>,<span class="string">'Color'</span>,c_x(iy,:))
-            plot(t,sy_fd(:,iy,ip),<span class="string">'--'</span>,<span class="string">'Color'</span>,c_x(iy,:))
-        <span class="keyword">end</span>
-        ylim([-2,2])
-        legend(<span class="string">'y1'</span>,<span class="string">'y1_{fd}'</span>,<span class="string">'Location'</span>,<span class="string">'NorthEastOutside'</span>)
-        legend <span class="string">boxoff</span>
-        title([<span class="string">'observable sensitivity for p'</span> num2str(ip)])
-        xlabel(<span class="string">'time t'</span>)
-        ylabel(<span class="string">'y'</span>)
-        box <span class="string">on</span>
-
-        subplot(4,2,ip*2)
-        plot(t,abs(sol.sy(:,:,ip)-sy_fd(:,:,ip)),<span class="string">'r--'</span>)
-        legend(<span class="string">'error y1'</span>,<span class="string">'Location'</span>,<span class="string">'NorthEastOutside'</span>)
-        legend <span class="string">boxoff</span>
-        title([<span class="string">'observable sensitivity for p'</span> num2str(ip)])
-        xlabel(<span class="string">'time t'</span>)
-        ylabel(<span class="string">'error'</span>)
-        ylim([1e-12,1e0])
-        set(gca,<span class="string">'YScale'</span>,<span class="string">'log'</span>)
-        box <span class="string">on</span>
-    <span class="keyword">end</span>
-    set(gcf,<span class="string">'Position'</span>,[100 300 1200 500])
-
-    drawnow
-</pre><img vspace="5" hspace="5" src="../examples/example_dirac/html/example_dirac_02.png" alt=""> <img vspace="5" hspace="5" src="../examples/example_dirac/html/example_dirac_03.png" alt=""> <pre class="codeinput"><span class="keyword">end</span>
-</pre><p class="footer"><br><a href="http://www.mathworks.com/products/matlab/">Published with MATLAB&reg; R2016a</a><br></p></div><!--
-##### SOURCE BEGIN #####
-function example_dirac()
-    %%
-    % COMPILATION
-    
-    [exdir,~,~]=fileparts(which('example_dirac.m'));
-    % compile the model
-    amiwrap('model_dirac','model_dirac_syms',exdir)
-    
-    %%
-    % SIMULATION
-    
-    % time vector
-    t = linspace(0,3,1001);
-    p = [1;0.5;2;3];
-    k = [];
-    
-    options = amioption('sensi',0,...
-        'maxsteps',1e4);
-    
-    % load mex into memory
-    [msg] = which('simulate_model_dirac'); % fix for inaccessability problems
-    sol = simulate_model_dirac(t,log10(p),k,[],options);
-    
-    tic
-    sol = simulate_model_dirac(t,log10(p),k,[],options);
-    disp(['Time elapsed with amiwrap: ' num2str(toc) ])
-    
-    %%
-    % ODE15S
-    
-    sig = 1e-2;
-    delta_num = @(tau) exp(-1/2*(tau/sig).^2)/(sqrt(2*pi)*sig);
-    
-    ode_system = @(t,x,p,k) [-p(1)*x(1)+delta_num(t-p(2));
-        +p(3)*x(1) - p(4)*x(2)];
-    
-    options_ode45 = odeset('RelTol',options.rtol,'AbsTol',options.atol,'MaxStep',options.maxsteps);
-    
-    tic
-    [~, X_ode45] = ode45(@(t,x) ode_system(t,x,p,k),t,[0;0],options_ode45);
-    disp(['Time elapsed with ode45: ' num2str(toc) ])
-    
-    %%
-    % PLOTTING
-    
-    figure
-    c_x = get(gca,'ColorOrder');
-    subplot(2,2,1)
-    for ix = 1:size(sol.x,2)
-        plot(t,sol.x(:,ix),'.-','Color',c_x(ix,:))
-        hold on
-        plot(t,X_ode45(:,ix),'REPLACE_WITH_DASH_DASH','Color',c_x(ix,:))
-    end
-    
-    legend('x1','x1_{ode45}','x2','x2_{ode15s}','Location','NorthEastOutside')
-    legend boxoff
-    xlabel('time t')
-    ylabel('x')
-    box on
-    subplot(2,2,2)
-    plot(t,abs(sol.x-X_ode45),'REPLACE_WITH_DASH_DASH')
-    set(gca,'YScale','log')
-    ylim([1e-10,1e0])
-    legend('error x1','error x2','Location','NorthEastOutside')
-    legend boxoff
-    
-    subplot(2,2,3)
-    plot(t,sol.y,'.-','Color',c_x(1,:))
-    hold on
-    plot(t,X_ode45(:,2),'REPLACE_WITH_DASH_DASH','Color',c_x(1,:))
-    legend('y1','y1_{ode45}','Location','NorthEastOutside')
-    legend boxoff
-    xlabel('time t')
-    ylabel('y')
-    box on
-    
-    subplot(2,2,4)
-    plot(t,abs(sol.y-X_ode45(:,2)),'REPLACE_WITH_DASH_DASH')
-    set(gca,'YScale','log')
-    ylim([1e-10,1e0])
-    legend('error y1','Location','NorthEastOutside')
-    legend boxoff
-    xlabel('time t')
-    ylabel('y')
-    box on
-    set(gcf,'Position',[100 300 1200 500])
-    
-    
-    %%
-    % FORWARD SENSITIVITY ANALYSIS
-    
-    options.sensi = 1;
-    
-    sol = simulate_model_dirac(t,log10(p),k,[],options);
-    
-    %%
-    % FINITE DIFFERENCES
-    
-    eps = 1e-4;
-    xi = log10(p);
-    for ip = 1:4;
-        xip = xi;
-        xip(ip) = xip(ip) + eps;
-        solp = simulate_model_dirac(t,xip,k,[],options);
-        sx_fd(:,:,ip) = (solp.x - sol.x)/eps;
-        sy_fd(:,:,ip) = (solp.y - sol.y)/eps;
-    end
-    
-    %%
-    % PLOTTING
-    figure
-    for ip = 1:4
-        subplot(4,2,ip*2-1)
-        hold on
-        for ix = 1:size(sol.x,2)
-            plot(t,sol.sx(:,ix,ip),'.-','Color',c_x(ix,:))
-            plot(t,sx_fd(:,ix,ip),'REPLACE_WITH_DASH_DASH','Color',c_x(ix,:))
-        end
-        ylim([-2,2])
-        legend('x1','x1_{fd}','x2','x2_{fd}','Location','NorthEastOutside')
-        legend boxoff
-        title(['state sensitivity for p' num2str(ip)])
-        xlabel('time t')
-        ylabel('x')
-        box on
-        
-        subplot(4,2,ip*2)
-        plot(t,abs(sol.sx(:,:,ip)-sx_fd(:,:,ip)),'rREPLACE_WITH_DASH_DASH')
-        legend('error x1','error x2','Location','NorthEastOutside')
-        legend boxoff
-        title(['state sensitivity for p' num2str(ip)])
-        xlabel('time t')
-        ylabel('error')
-        ylim([1e-12,1e0])
-        set(gca,'YScale','log')
-        box on
-    end
-    set(gcf,'Position',[100 300 1200 500])
-    
-    figure
-    for ip = 1:4
-        subplot(4,2,ip*2-1)
-        hold on
-        for iy = 1:size(sol.y,2)
-            plot(t,sol.sy(:,iy,ip),'.-','Color',c_x(iy,:))
-            plot(t,sy_fd(:,iy,ip),'REPLACE_WITH_DASH_DASH','Color',c_x(iy,:))
-        end
-        ylim([-2,2])
-        legend('y1','y1_{fd}','Location','NorthEastOutside')
-        legend boxoff
-        title(['observable sensitivity for p' num2str(ip)])
-        xlabel('time t')
-        ylabel('y')
-        box on
-        
-        subplot(4,2,ip*2)
-        plot(t,abs(sol.sy(:,:,ip)-sy_fd(:,:,ip)),'rREPLACE_WITH_DASH_DASH')
-        legend('error y1','Location','NorthEastOutside')
-        legend boxoff
-        title(['observable sensitivity for p' num2str(ip)])
-        xlabel('time t')
-        ylabel('error')
-        ylim([1e-12,1e0])
-        set(gca,'YScale','log')
-        box on
-    end
-    set(gcf,'Position',[100 300 1200 500])
-    
-    drawnow
-    
-end
-##### SOURCE END #####
---></body></html>
\ No newline at end of file
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diff --git a/matlab/examples/example_dirac/html/example_dirac.tex b/matlab/examples/example_dirac/html/example_dirac.tex
deleted file mode 100644
index 5f520666a3..0000000000
--- a/matlab/examples/example_dirac/html/example_dirac.tex
+++ /dev/null
@@ -1,226 +0,0 @@
-
-% This LaTeX was auto-generated from MATLAB code.
-% To make changes, update the MATLAB code and republish this document.
-
-
-
-
-
-
-
-
-
-
-
-    
-    \begin{DoxyCode}
-function example_dirac()
-\end{DoxyCode}
-\begin{par}
-COMPILATION
-\end{par} \vspace{1em}
-\begin{DoxyCode}
-    [exdir,~,~]=fileparts(which('example_dirac.m'));
-    % compile the model
-    amiwrap('model_dirac','model_dirac_syms',exdir)
-\end{DoxyCode}
-
-         \begin{DoxyCode}Generating model struct ...
-Parsing model struct ...
-
-Generating C code ...
-headers | wrapfunctions | 
-Compiling mex file ...
-amici | Building with 'Xcode with Clang'.
-MEX completed successfully.
-Building with 'Xcode with Clang'.
-MEX completed successfully.
-\end{DoxyCode} 
-    \begin{par}
-SIMULATION
-\end{par} \vspace{1em}
-\begin{DoxyCode}
-    % time vector
-    t = linspace(0,3,1001);
-    p = [1;0.5;2;3];
-    k = [];
-
-    options = amioption('sensi',0,...
-        'maxsteps',1e4);
-
-    % load mex into memory
-    [msg] = which('simulate_model_dirac'); % fix for inaccessability problems
-    sol = simulate_model_dirac(t,log10(p),k,[],options);
-
-    tic
-    sol = simulate_model_dirac(t,log10(p),k,[],options);
-    disp(['Time elapsed with amiwrap: ' num2str(toc) ])
-\end{DoxyCode}
-
-         \begin{DoxyCode}Time elapsed with amiwrap: 0.0045507
-\end{DoxyCode} 
-    \begin{par}
-ODE15S
-\end{par} \vspace{1em}
-\begin{DoxyCode}
-    sig = 1e-2;
-    delta_num = @(tau) exp(-1/2*(tau/sig).^2)/(sqrt(2*pi)*sig);
-
-    ode_system = @(t,x,p,k) [-p(1)*x(1)+delta_num(t-p(2));
-        +p(3)*x(1) - p(4)*x(2)];
-
-    options_ode45 = odeset('RelTol',options.rtol,'AbsTol',options.atol,'MaxStep',options.maxsteps);
-
-    tic
-    [~, X_ode45] = ode45(@(t,x) ode_system(t,x,p,k),t,[0;0],options_ode45);
-    disp(['Time elapsed with ode45: ' num2str(toc) ])
-\end{DoxyCode}
-
-         \begin{DoxyCode}Time elapsed with ode45: 0.080371
-\end{DoxyCode} 
-    \begin{par}
-PLOTTING
-\end{par} \vspace{1em}
-\begin{DoxyCode}
-    figure
-    c_x = get(gca,'ColorOrder');
-    subplot(2,2,1)
-    for ix = 1:size(sol.x,2)
-        plot(t,sol.x(:,ix),'.-','Color',c_x(ix,:))
-        hold on
-        plot(t,X_ode45(:,ix),'--','Color',c_x(ix,:))
-    end
-
-    legend('x1','x1_{ode45}','x2','x2_{ode15s}','Location','NorthEastOutside')
-    legend boxoff
-    xlabel('time t')
-    ylabel('x')
-    box on
-    subplot(2,2,2)
-    plot(t,abs(sol.x-X_ode45),'--')
-    set(gca,'YScale','log')
-    ylim([1e-10,1e0])
-    legend('error x1','error x2','Location','NorthEastOutside')
-    legend boxoff
-
-    subplot(2,2,3)
-    plot(t,sol.y,'.-','Color',c_x(1,:))
-    hold on
-    plot(t,X_ode45(:,2),'--','Color',c_x(1,:))
-    legend('y1','y1_{ode45}','Location','NorthEastOutside')
-    legend boxoff
-    xlabel('time t')
-    ylabel('y')
-    box on
-
-    subplot(2,2,4)
-    plot(t,abs(sol.y-X_ode45(:,2)),'--')
-    set(gca,'YScale','log')
-    ylim([1e-10,1e0])
-    legend('error y1','Location','NorthEastOutside')
-    legend boxoff
-    xlabel('time t')
-    ylabel('y')
-    box on
-    set(gcf,'Position',[100 300 1200 500])
-\end{DoxyCode}
-
-\includegraphics[width=\textwidth]{../../examples/example_dirac/html/example_dirac_01.png}
-\begin{par}
-FORWARD SENSITIVITY ANALYSIS
-\end{par} \vspace{1em}
-\begin{DoxyCode}
-    options.sensi = 1;
-
-    sol = simulate_model_dirac(t,log10(p),k,[],options);
-\end{DoxyCode}
-\begin{par}
-FINITE DIFFERENCES
-\end{par} \vspace{1em}
-\begin{DoxyCode}
-    eps = 1e-4;
-    xi = log10(p);
-    for ip = 1:4;
-        xip = xi;
-        xip(ip) = xip(ip) + eps;
-        solp = simulate_model_dirac(t,xip,k,[],options);
-        sx_fd(:,:,ip) = (solp.x - sol.x)/eps;
-        sy_fd(:,:,ip) = (solp.y - sol.y)/eps;
-    end
-\end{DoxyCode}
-\begin{par}
-PLOTTING
-\end{par} \vspace{1em}
-\begin{DoxyCode}
-    figure
-    for ip = 1:4
-        subplot(4,2,ip*2-1)
-        hold on
-        for ix = 1:size(sol.x,2)
-            plot(t,sol.sx(:,ix,ip),'.-','Color',c_x(ix,:))
-            plot(t,sx_fd(:,ix,ip),'--','Color',c_x(ix,:))
-        end
-        ylim([-2,2])
-        legend('x1','x1_{fd}','x2','x2_{fd}','Location','NorthEastOutside')
-        legend boxoff
-        title(['state sensitivity for p' num2str(ip)])
-        xlabel('time t')
-        ylabel('x')
-        box on
-
-        subplot(4,2,ip*2)
-        plot(t,abs(sol.sx(:,:,ip)-sx_fd(:,:,ip)),'r--')
-        legend('error x1','error x2','Location','NorthEastOutside')
-        legend boxoff
-        title(['state sensitivity for p' num2str(ip)])
-        xlabel('time t')
-        ylabel('error')
-        ylim([1e-12,1e0])
-        set(gca,'YScale','log')
-        box on
-    end
-    set(gcf,'Position',[100 300 1200 500])
-
-    figure
-    for ip = 1:4
-        subplot(4,2,ip*2-1)
-        hold on
-        for iy = 1:size(sol.y,2)
-            plot(t,sol.sy(:,iy,ip),'.-','Color',c_x(iy,:))
-            plot(t,sy_fd(:,iy,ip),'--','Color',c_x(iy,:))
-        end
-        ylim([-2,2])
-        legend('y1','y1_{fd}','Location','NorthEastOutside')
-        legend boxoff
-        title(['observable sensitivity for p' num2str(ip)])
-        xlabel('time t')
-        ylabel('y')
-        box on
-
-        subplot(4,2,ip*2)
-        plot(t,abs(sol.sy(:,:,ip)-sy_fd(:,:,ip)),'r--')
-        legend('error y1','Location','NorthEastOutside')
-        legend boxoff
-        title(['observable sensitivity for p' num2str(ip)])
-        xlabel('time t')
-        ylabel('error')
-        ylim([1e-12,1e0])
-        set(gca,'YScale','log')
-        box on
-    end
-    set(gcf,'Position',[100 300 1200 500])
-
-    drawnow
-\end{DoxyCode}
-
-\includegraphics[width=\textwidth]{../../examples/example_dirac/html/example_dirac_02.png}
-
-\includegraphics[width=\textwidth]{../../examples/example_dirac/html/example_dirac_03.png}
-\begin{DoxyCode}
-end
-\end{DoxyCode}
-
-
-
-
-    
\ No newline at end of file
diff --git a/matlab/examples/example_dirac/html/example_dirac_01.png b/matlab/examples/example_dirac/html/example_dirac_01.png
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deleted file mode 100644
index 2ab780a122..0000000000
--- a/matlab/examples/example_dirac/html/model_dirac_syms.html
+++ /dev/null
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-To make changes, update the MATLAB code and republish this document.
-      --><title>model_dirac_syms</title><meta name="generator" content="MATLAB 9.0"><link rel="schema.DC" href="http://purl.org/dc/elements/1.1/"><meta name="DC.date" content="2016-05-04"><meta name="DC.source" content="model_dirac_syms.m"><style type="text/css">
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-
-
-
-
-
-  </style></head><body><div class="content"><pre class="codeinput"><span class="keyword">function</span> [model] = model_dirac_syms()
-</pre><p>STATES</p><pre class="codeinput"><span class="comment">% create state syms</span>
-syms <span class="string">x1</span> <span class="string">x2</span>
-
-<span class="comment">% create state vector</span>
-model.sym.x = [ x1 x2 ];
-</pre><p>PARAMETERS ( for these sensitivities will be computed )</p><pre class="codeinput"><span class="comment">% create parameter syms</span>
-syms <span class="string">p1</span> <span class="string">p2</span> <span class="string">p3</span> <span class="string">p4</span>
-
-<span class="comment">% create parameter vector</span>
-model.sym.p = [p1,p2,p3,p4];
-
-<span class="comment">% set the parametrisation of the problem options are 'log', 'log10' and</span>
-<span class="comment">% 'lin' (default).</span>
-model.param = <span class="string">'log10'</span>;
-</pre><p>SYSTEM EQUATIONS</p><pre class="codeinput"><span class="comment">% create symbolic variable for time</span>
-syms <span class="string">t</span>
-
-model.sym.xdot = sym(zeros(size(model.sym.x)));
-
-<span class="comment">% piecewise defined function</span>
-model.sym.xdot(1) = -p1*x1 + dirac(t-p2);
-<span class="comment">% inhomogeneous</span>
-model.sym.xdot(2) = p3*x1 - p4*x2 ;
-</pre><p>INITIAL CONDITIONS</p><pre class="codeinput">model.sym.x0 = sym(zeros(size(model.sym.x)));
-
-model.sym.x0(1) = 0;
-model.sym.x0(2) = 0;
-</pre><p>OBSERVALES</p><pre class="codeinput">model.sym.y = sym(zeros(1,1));
-
-model.sym.y(1) = x2;
-</pre><pre class="codeinput"><span class="keyword">end</span>
-</pre><pre class="codeoutput">ans = 
-      sym: [1x1 struct]
-    param: 'log10'
-</pre><p class="footer"><br><a href="http://www.mathworks.com/products/matlab/">Published with MATLAB&reg; R2016a</a><br></p></div><!--
-##### SOURCE BEGIN #####
-function [model] = model_dirac_syms()
-
-%%
-% STATES
-
-% create state syms
-syms x1 x2
-
-% create state vector
-model.sym.x = [ x1 x2 ];
-
-%%
-% PARAMETERS ( for these sensitivities will be computed )
-
-% create parameter syms
-syms p1 p2 p3 p4
-
-% create parameter vector 
-model.sym.p = [p1,p2,p3,p4];
-
-% set the parametrisation of the problem options are 'log', 'log10' and
-% 'lin' (default).
-model.param = 'log10'; 
-
-%%
-% SYSTEM EQUATIONS
-
-% create symbolic variable for time
-syms t
-
-model.sym.xdot = sym(zeros(size(model.sym.x)));
-
-% piecewise defined function
-model.sym.xdot(1) = -p1*x1 + dirac(t-p2);
-% inhomogeneous
-model.sym.xdot(2) = p3*x1 - p4*x2 ;
-
-%%
-% INITIAL CONDITIONS
-
-model.sym.x0 = sym(zeros(size(model.sym.x)));
-
-model.sym.x0(1) = 0;
-model.sym.x0(2) = 0;
-
-%%
-% OBSERVALES
-
-model.sym.y = sym(zeros(1,1));
-
-model.sym.y(1) = x2;
-end
-##### SOURCE END #####
---></body></html>
\ No newline at end of file
diff --git a/matlab/examples/example_dirac/html/model_dirac_syms.tex b/matlab/examples/example_dirac/html/model_dirac_syms.tex
deleted file mode 100644
index 2a8bd67c0f..0000000000
--- a/matlab/examples/example_dirac/html/model_dirac_syms.tex
+++ /dev/null
@@ -1,86 +0,0 @@
-
-% This LaTeX was auto-generated from MATLAB code.
-% To make changes, update the MATLAB code and republish this document.
-
-
-
-
-
-
-
-
-
-
-
-    
-    \begin{DoxyCode}
-function [model] = model_dirac_syms()
-\end{DoxyCode}
-\begin{par}
-STATES
-\end{par} \vspace{1em}
-\begin{DoxyCode}
-% create state syms
-syms x1 x2
-
-% create state vector
-model.sym.x = [ x1 x2 ];
-\end{DoxyCode}
-\begin{par}
-PARAMETERS ( for these sensitivities will be computed )
-\end{par} \vspace{1em}
-\begin{DoxyCode}
-% create parameter syms
-syms p1 p2 p3 p4
-
-% create parameter vector
-model.sym.p = [p1,p2,p3,p4];
-
-% set the parametrisation of the problem options are 'log', 'log10' and
-% 'lin' (default).
-model.param = 'log10';
-\end{DoxyCode}
-\begin{par}
-SYSTEM EQUATIONS
-\end{par} \vspace{1em}
-\begin{DoxyCode}
-% create symbolic variable for time
-syms t
-
-model.sym.xdot = sym(zeros(size(model.sym.x)));
-
-% piecewise defined function
-model.sym.xdot(1) = -p1*x1 + dirac(t-p2);
-% inhomogeneous
-model.sym.xdot(2) = p3*x1 - p4*x2 ;
-\end{DoxyCode}
-\begin{par}
-INITIAL CONDITIONS
-\end{par} \vspace{1em}
-\begin{DoxyCode}
-model.sym.x0 = sym(zeros(size(model.sym.x)));
-
-model.sym.x0(1) = 0;
-model.sym.x0(2) = 0;
-\end{DoxyCode}
-\begin{par}
-OBSERVALES
-\end{par} \vspace{1em}
-\begin{DoxyCode}
-model.sym.y = sym(zeros(1,1));
-
-model.sym.y(1) = x2;
-\end{DoxyCode}
-\begin{DoxyCode}
-end
-\end{DoxyCode}
-
-         \begin{DoxyCode}ans = 
-      sym: [1x1 struct]
-    param: 'log10'
-\end{DoxyCode} 
-    
-
-
-
-    
\ No newline at end of file
diff --git a/matlab/examples/example_dirac_adjoint/html/example_dirac_adjoint.html b/matlab/examples/example_dirac_adjoint/html/example_dirac_adjoint.html
deleted file mode 100644
index 28ebfd2511..0000000000
--- a/matlab/examples/example_dirac_adjoint/html/example_dirac_adjoint.html
+++ /dev/null
@@ -1,232 +0,0 @@
-
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-  PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN">
-<html><head>
-      <meta http-equiv="Content-Type" content="text/html; charset=utf-8">
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-To make changes, update the MATLAB code and republish this document.
-      --><title>example_dirac_adjoint</title><meta name="generator" content="MATLAB 9.0"><link rel="schema.DC" href="http://purl.org/dc/elements/1.1/"><meta name="DC.date" content="2016-05-04"><meta name="DC.source" content="example_dirac_adjoint.m"><style type="text/css">
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-</pre><p>COMPILATION</p><pre class="codeinput">    [exdir,~,~]=fileparts(which(<span class="string">'example_dirac_adjoint.m'</span>));
-    <span class="comment">% compile the model</span>
-    amiwrap(<span class="string">'model_dirac_adjoint'</span>,<span class="string">'model_dirac_adjoint_syms'</span>,exdir)
-</pre><pre class="codeoutput">Generating model struct ...
-Parsing model struct ...
-Generating C code ...
-headers | wrapfunctions | Compiling mex file ...
-amici | Building with 'Xcode with Clang'.
-MEX completed successfully.
-Building with 'Xcode with Clang'.
-MEX completed successfully.
-</pre><p>SIMULATION</p><pre class="codeinput">    <span class="comment">% time vector</span>
-    tout = linspace(0,4,9);
-    tfine = linspace(0,4,10001);
-    p = [1;0.4;2;3];
-    k = [];
-
-    D.Y = [  0.00714742903826096
-        -0.00204966058299775
-        0.382159034587845
-        0.33298932672138
-        0.226111476113441
-        0.147028440865854
-        0.0882468698791813
-        0.0375887796628869
-        0.0373422340295005];
-
-    D.Sigma_Y = 0.01*ones(size(D.Y));
-
-
-    options.sensi = 1;
-    options.sensi_meth = <span class="string">'adjoint'</span>;
-    options.maxsteps = 1e5;
-    sol = simulate_model_dirac_adjoint(tout,log10(p),k,D,options);
-    options.sensi = 0;
-    solfine = simulate_model_dirac_adjoint(tfine,log10(p),k,[],options);
-    figure
-    errorbar(tout,D.Y,D.Sigma_Y)
-    hold <span class="string">on</span>
-    plot(tfine,solfine.y)
-    legend(<span class="string">'data'</span>,<span class="string">'simulation'</span>)
-    xlabel(<span class="string">'time t'</span>)
-    ylabel(<span class="string">'observable'</span>)
-    title([<span class="string">'log-likelihood: '</span> num2str(sol.llh) ])
-</pre><img vspace="5" hspace="5" src="../examples/example_dirac_adjoint/html/example_dirac_adjoint_01.png" alt=""> <p>FD</p><pre class="codeinput">    eps = 1e-4;
-    xi = log10(p);
-    grad_fd_f = NaN(4,1);
-    grad_fd_b = NaN(4,1);
-    <span class="keyword">for</span> ip = 1:4;
-        options.sensi = 0;
-        xip = xi;
-        xip(ip) = xip(ip) + eps;
-        solpf = simulate_model_dirac_adjoint(tout,xip,k,D,options);
-        grad_fd_f(ip,1) = (solpf.llh-sol.llh)/eps;
-        xip = xi;
-        xip(ip) = xip(ip) - eps;
-        solpb = simulate_model_dirac_adjoint(tout,xip,k,D,options);
-        grad_fd_b(ip,1) = -(solpb.llh-sol.llh)/eps;
-    <span class="keyword">end</span>
-
-    figure
-    plot(abs(grad_fd_f),abs(sol.sllh),<span class="string">'o'</span>)
-    hold <span class="string">on</span>
-    plot(abs(grad_fd_b),abs(sol.sllh),<span class="string">'o'</span>)
-    set(gca,<span class="string">'XScale'</span>,<span class="string">'log'</span>)
-    set(gca,<span class="string">'YScale'</span>,<span class="string">'log'</span>)
-    hold <span class="string">on</span>
-    axis <span class="string">square</span>
-    plot([1e2,1e4],[1e2,1e4],<span class="string">'k:'</span>)
-    xlim([1e2,1e4])
-    ylim([1e2,1e4])
-    legend(<span class="string">'forward FD'</span>,<span class="string">'backward FD'</span>,<span class="string">'Location'</span>,<span class="string">'SouthEast'</span>)
-    xlabel(<span class="string">'adjoint sensitivity absolute value of gradient element'</span>)
-    ylabel(<span class="string">'computed absolute value of gradient element'</span>)
-    set(gcf,<span class="string">'Position'</span>,[100 300 1200 500])
-
-    drawnow
-</pre><img vspace="5" hspace="5" src="../examples/example_dirac_adjoint/html/example_dirac_adjoint_02.png" alt=""> <pre class="codeinput"><span class="keyword">end</span>
-</pre><p class="footer"><br><a href="http://www.mathworks.com/products/matlab/">Published with MATLAB&reg; R2016a</a><br></p></div><!--
-##### SOURCE BEGIN #####
-function example_dirac_adjoint()
-    %%
-    % COMPILATION
-    [exdir,~,~]=fileparts(which('example_dirac_adjoint.m'));
-    % compile the model
-    amiwrap('model_dirac_adjoint','model_dirac_adjoint_syms',exdir)
-    
-    %%
-    % SIMULATION
-    
-    % time vector
-    tout = linspace(0,4,9);
-    tfine = linspace(0,4,10001);
-    p = [1;0.4;2;3];
-    k = [];
-    
-    D.Y = [  0.00714742903826096
-        -0.00204966058299775
-        0.382159034587845
-        0.33298932672138
-        0.226111476113441
-        0.147028440865854
-        0.0882468698791813
-        0.0375887796628869
-        0.0373422340295005];
-    
-    D.Sigma_Y = 0.01*ones(size(D.Y));
-    
-    
-    options.sensi = 1;
-    options.sensi_meth = 'adjoint';
-    options.maxsteps = 1e5;
-    sol = simulate_model_dirac_adjoint(tout,log10(p),k,D,options);
-    options.sensi = 0;
-    solfine = simulate_model_dirac_adjoint(tfine,log10(p),k,[],options);
-    figure
-    errorbar(tout,D.Y,D.Sigma_Y)
-    hold on
-    plot(tfine,solfine.y)
-    legend('data','simulation')
-    xlabel('time t')
-    ylabel('observable')
-    title(['log-likelihood: ' num2str(sol.llh) ])
-    
-    %%
-    % FD
-    
-    eps = 1e-4;
-    xi = log10(p);
-    grad_fd_f = NaN(4,1);
-    grad_fd_b = NaN(4,1);
-    for ip = 1:4;
-        options.sensi = 0;
-        xip = xi;
-        xip(ip) = xip(ip) + eps;
-        solpf = simulate_model_dirac_adjoint(tout,xip,k,D,options);
-        grad_fd_f(ip,1) = (solpf.llh-sol.llh)/eps;
-        xip = xi;
-        xip(ip) = xip(ip) - eps;
-        solpb = simulate_model_dirac_adjoint(tout,xip,k,D,options);
-        grad_fd_b(ip,1) = -(solpb.llh-sol.llh)/eps;
-    end
-    
-    figure
-    plot(abs(grad_fd_f),abs(sol.sllh),'o')
-    hold on
-    plot(abs(grad_fd_b),abs(sol.sllh),'o')
-    set(gca,'XScale','log')
-    set(gca,'YScale','log')
-    hold on
-    axis square
-    plot([1e2,1e4],[1e2,1e4],'k:')
-    xlim([1e2,1e4])
-    ylim([1e2,1e4])
-    legend('forward FD','backward FD','Location','SouthEast')
-    xlabel('adjoint sensitivity absolute value of gradient element')
-    ylabel('computed absolute value of gradient element')
-    set(gcf,'Position',[100 300 1200 500])
-    
-    drawnow
-end
-##### SOURCE END #####
---></body></html>
\ No newline at end of file
diff --git a/matlab/examples/example_dirac_adjoint/html/example_dirac_adjoint.png b/matlab/examples/example_dirac_adjoint/html/example_dirac_adjoint.png
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diff --git a/matlab/examples/example_dirac_adjoint/html/example_dirac_adjoint.tex b/matlab/examples/example_dirac_adjoint/html/example_dirac_adjoint.tex
deleted file mode 100644
index c112059a4c..0000000000
--- a/matlab/examples/example_dirac_adjoint/html/example_dirac_adjoint.tex
+++ /dev/null
@@ -1,126 +0,0 @@
-
-% This LaTeX was auto-generated from MATLAB code.
-% To make changes, update the MATLAB code and republish this document.
-
-
-
-
-
-
-
-
-
-
-
-    
-    \begin{DoxyCode}
-function example_dirac_adjoint()
-\end{DoxyCode}
-\begin{par}
-COMPILATION
-\end{par} \vspace{1em}
-\begin{DoxyCode}
-    [exdir,~,~]=fileparts(which('example_dirac_adjoint.m'));
-    % compile the model
-    amiwrap('model_dirac_adjoint','model_dirac_adjoint_syms',exdir)
-\end{DoxyCode}
-
-         \begin{DoxyCode}Generating model struct ...
-Parsing model struct ...
-
-Generating C code ...
-headers | wrapfunctions | 
-Compiling mex file ...
-amici | Building with 'Xcode with Clang'.
-MEX completed successfully.
-Building with 'Xcode with Clang'.
-MEX completed successfully.
-\end{DoxyCode} 
-    \begin{par}
-SIMULATION
-\end{par} \vspace{1em}
-\begin{DoxyCode}
-    % time vector
-    tout = linspace(0,4,9);
-    tfine = linspace(0,4,10001);
-    p = [1;0.4;2;3];
-    k = [];
-
-    D.Y = [  0.00714742903826096
-        -0.00204966058299775
-        0.382159034587845
-        0.33298932672138
-        0.226111476113441
-        0.147028440865854
-        0.0882468698791813
-        0.0375887796628869
-        0.0373422340295005];
-
-    D.Sigma_Y = 0.01*ones(size(D.Y));
-
-
-    options.sensi = 1;
-    options.sensi_meth = 'adjoint';
-    options.maxsteps = 1e5;
-    sol = simulate_model_dirac_adjoint(tout,log10(p),k,D,options);
-    options.sensi = 0;
-    solfine = simulate_model_dirac_adjoint(tfine,log10(p),k,[],options);
-    figure
-    errorbar(tout,D.Y,D.Sigma_Y)
-    hold on
-    plot(tfine,solfine.y)
-    legend('data','simulation')
-    xlabel('time t')
-    ylabel('observable')
-    title(['log-likelihood: ' num2str(sol.llh) ])
-\end{DoxyCode}
-
-\includegraphics[width=\textwidth]{../../examples/example_dirac_adjoint/html/example_dirac_adjoint_01.png}
-\begin{par}
-FD
-\end{par} \vspace{1em}
-\begin{DoxyCode}
-    eps = 1e-4;
-    xi = log10(p);
-    grad_fd_f = NaN(4,1);
-    grad_fd_b = NaN(4,1);
-    for ip = 1:4;
-        options.sensi = 0;
-        xip = xi;
-        xip(ip) = xip(ip) + eps;
-        solpf = simulate_model_dirac_adjoint(tout,xip,k,D,options);
-        grad_fd_f(ip,1) = (solpf.llh-sol.llh)/eps;
-        xip = xi;
-        xip(ip) = xip(ip) - eps;
-        solpb = simulate_model_dirac_adjoint(tout,xip,k,D,options);
-        grad_fd_b(ip,1) = -(solpb.llh-sol.llh)/eps;
-    end
-
-    figure
-    plot(abs(grad_fd_f),abs(sol.sllh),'o')
-    hold on
-    plot(abs(grad_fd_b),abs(sol.sllh),'o')
-    set(gca,'XScale','log')
-    set(gca,'YScale','log')
-    hold on
-    axis square
-    plot([1e2,1e4],[1e2,1e4],'k:')
-    xlim([1e2,1e4])
-    ylim([1e2,1e4])
-    legend('forward FD','backward FD','Location','SouthEast')
-    xlabel('adjoint sensitivity absolute value of gradient element')
-    ylabel('computed absolute value of gradient element')
-    set(gcf,'Position',[100 300 1200 500])
-
-    drawnow
-\end{DoxyCode}
-
-\includegraphics[width=\textwidth]{../../examples/example_dirac_adjoint/html/example_dirac_adjoint_02.png}
-\begin{DoxyCode}
-end
-\end{DoxyCode}
-
-
-
-
-    
\ No newline at end of file
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-table td { padding:7px 5px; text-align:left; vertical-align:top; border:1px solid #d6d4d4; }
-
-
-
-
-
-  </style></head><body><div class="content"><pre class="codeinput"><span class="keyword">function</span> [model] = model_dirac_adjoint_syms()
-</pre><p>STATES</p><pre class="codeinput"><span class="comment">% create state syms</span>
-syms <span class="string">x1</span> <span class="string">x2</span>
-
-<span class="comment">% create state vector</span>
-model.sym.x = [ x1 x2 ];
-</pre><p>PARAMETERS ( for these sensitivities will be computed )</p><pre class="codeinput"><span class="comment">% create parameter syms</span>
-syms <span class="string">p1</span> <span class="string">p2</span> <span class="string">p3</span> <span class="string">p4</span>
-
-<span class="comment">% create parameter vector</span>
-model.sym.p = [p1,p2,p3,p4];
-
-<span class="comment">% set the parametrisation of the problem options are 'log', 'log10' and</span>
-<span class="comment">% 'lin' (default).</span>
-model.param = <span class="string">'log10'</span>;
-</pre><p>SYSTEM EQUATIONS</p><pre class="codeinput"><span class="comment">% create symbolic variable for time</span>
-syms <span class="string">t</span>
-
-model.sym.xdot = sym(zeros(size(model.sym.x)));
-
-<span class="comment">% piecewise defined function</span>
-model.sym.xdot(1) = -p1*x1 + dirac(t-p2);
-<span class="comment">% inhomogeneous</span>
-model.sym.xdot(2) = p3*x1 - p4*x2 ;
-</pre><p>INITIAL CONDITIONS</p><pre class="codeinput">model.sym.x0 = sym(zeros(size(model.sym.x)));
-
-model.sym.x0(1) = 0;
-model.sym.x0(2) = 0;
-</pre><p>OBSERVALES</p><pre class="codeinput">model.sym.y = sym(zeros(1,1));
-
-model.sym.y(1) = x2;
-</pre><pre class="codeinput"><span class="keyword">end</span>
-</pre><pre class="codeoutput">ans = 
-      sym: [1x1 struct]
-    param: 'log10'
-</pre><p class="footer"><br><a href="http://www.mathworks.com/products/matlab/">Published with MATLAB&reg; R2016a</a><br></p></div><!--
-##### SOURCE BEGIN #####
-function [model] = model_dirac_adjoint_syms()
-
-
-%%
-% STATES
-
-% create state syms
-syms x1 x2
-
-% create state vector
-model.sym.x = [ x1 x2 ];
-
-%%
-% PARAMETERS ( for these sensitivities will be computed )
-
-% create parameter syms
-syms p1 p2 p3 p4
-
-% create parameter vector 
-model.sym.p = [p1,p2,p3,p4];
-
-% set the parametrisation of the problem options are 'log', 'log10' and
-% 'lin' (default).
-model.param = 'log10';
-
-%%
-% SYSTEM EQUATIONS
-
-% create symbolic variable for time
-syms t
-
-model.sym.xdot = sym(zeros(size(model.sym.x)));
-
-% piecewise defined function
-model.sym.xdot(1) = -p1*x1 + dirac(t-p2);
-% inhomogeneous
-model.sym.xdot(2) = p3*x1 - p4*x2 ;
-
-%%
-% INITIAL CONDITIONS
-
-model.sym.x0 = sym(zeros(size(model.sym.x)));
-
-model.sym.x0(1) = 0;
-model.sym.x0(2) = 0;
-
-%%
-% OBSERVALES
-
-model.sym.y = sym(zeros(1,1));
-
-model.sym.y(1) = x2;
-
-end
-##### SOURCE END #####
---></body></html>
\ No newline at end of file
diff --git a/matlab/examples/example_dirac_adjoint/html/model_dirac_adjoint_syms.tex b/matlab/examples/example_dirac_adjoint/html/model_dirac_adjoint_syms.tex
deleted file mode 100644
index a7a9033e5f..0000000000
--- a/matlab/examples/example_dirac_adjoint/html/model_dirac_adjoint_syms.tex
+++ /dev/null
@@ -1,86 +0,0 @@
-
-% This LaTeX was auto-generated from MATLAB code.
-% To make changes, update the MATLAB code and republish this document.
-
-
-
-
-
-
-
-
-
-
-
-    
-    \begin{DoxyCode}
-function [model] = model_dirac_adjoint_syms()
-\end{DoxyCode}
-\begin{par}
-STATES
-\end{par} \vspace{1em}
-\begin{DoxyCode}
-% create state syms
-syms x1 x2
-
-% create state vector
-model.sym.x = [ x1 x2 ];
-\end{DoxyCode}
-\begin{par}
-PARAMETERS ( for these sensitivities will be computed )
-\end{par} \vspace{1em}
-\begin{DoxyCode}
-% create parameter syms
-syms p1 p2 p3 p4
-
-% create parameter vector
-model.sym.p = [p1,p2,p3,p4];
-
-% set the parametrisation of the problem options are 'log', 'log10' and
-% 'lin' (default).
-model.param = 'log10';
-\end{DoxyCode}
-\begin{par}
-SYSTEM EQUATIONS
-\end{par} \vspace{1em}
-\begin{DoxyCode}
-% create symbolic variable for time
-syms t
-
-model.sym.xdot = sym(zeros(size(model.sym.x)));
-
-% piecewise defined function
-model.sym.xdot(1) = -p1*x1 + dirac(t-p2);
-% inhomogeneous
-model.sym.xdot(2) = p3*x1 - p4*x2 ;
-\end{DoxyCode}
-\begin{par}
-INITIAL CONDITIONS
-\end{par} \vspace{1em}
-\begin{DoxyCode}
-model.sym.x0 = sym(zeros(size(model.sym.x)));
-
-model.sym.x0(1) = 0;
-model.sym.x0(2) = 0;
-\end{DoxyCode}
-\begin{par}
-OBSERVALES
-\end{par} \vspace{1em}
-\begin{DoxyCode}
-model.sym.y = sym(zeros(1,1));
-
-model.sym.y(1) = x2;
-\end{DoxyCode}
-\begin{DoxyCode}
-end
-\end{DoxyCode}
-
-         \begin{DoxyCode}ans = 
-      sym: [1x1 struct]
-    param: 'log10'
-\end{DoxyCode} 
-    
-
-
-
-    
\ No newline at end of file
diff --git a/matlab/examples/example_dirac_secondorder/html/example_dirac_secondorder.html b/matlab/examples/example_dirac_secondorder/html/example_dirac_secondorder.html
deleted file mode 100644
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--- a/matlab/examples/example_dirac_secondorder/html/example_dirac_secondorder.html
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-<html><head>
-      <meta http-equiv="Content-Type" content="text/html; charset=utf-8">
-   <!--
-This HTML was auto-generated from MATLAB code.
-To make changes, update the MATLAB code and republish this document.
-      --><title>example_dirac_secondorder</title><meta name="generator" content="MATLAB 9.0"><link rel="schema.DC" href="http://purl.org/dc/elements/1.1/"><meta name="DC.date" content="2016-05-04"><meta name="DC.source" content="example_dirac_secondorder.m"><style type="text/css">
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-
-
-
-
-
-  </style></head><body><div class="content"><pre class="codeinput"><span class="keyword">function</span> example_dirac_secondorder()
-</pre><p>COMPILATION</p><pre class="codeinput">    [exdir,~,~]=fileparts(which(<span class="string">'example_dirac_secondorder.m'</span>));
-    <span class="comment">% compile the model</span>
-    amiwrap(<span class="string">'model_dirac_secondorder'</span>,<span class="string">'model_dirac_secondorder_syms'</span>,exdir,1)
-</pre><pre class="codeoutput">Generating model struct ...
-x | k | p | deltax | xdot | deltaxdot | ddeltaxdx | ddeltaxdp | ddeltaxdt | root | drootdx | sx | drootdp | drootdt | dtaudp | sroot | stau | deltasx | sigma_y | dsigma_ydp | y | dydp | sigma_z | dsigma_zdp | z | dzdp | Parsing model struct ...
-z | Generating C code ...
-deltasx | deltax | dsigma_ydp | dsigma_zdp | dydp | dzdp | root | sigma_y | sigma_z | stau | xdot | y | z | headers | wrapfunctions | headers | wrapfunctions | Compiling mex file ...
-amici | Building with 'Xcode with Clang'.
-MEX completed successfully.
-Building with 'Xcode with Clang'.
-MEX completed successfully.
-amici | Building with 'Xcode with Clang'.
-MEX completed successfully.
-Building with 'Xcode with Clang'.
-MEX completed successfully.
-</pre><p>SIMULATION</p><pre class="codeinput">    <span class="comment">% time vector</span>
-    t = linspace(0,3,1001);
-    p = [1;0.5;2;3];
-    k = [];
-
-    options = amioption(<span class="string">'sensi'</span>,0,<span class="keyword">...</span>
-        <span class="string">'maxsteps'</span>,1e4);
-
-    <span class="comment">% load mex into memory</span>
-    [msg] = which(<span class="string">'simulate_model_secondorder_dirac'</span>); <span class="comment">% fix for inaccessability problems</span>
-    options.sensi = 2;
-    sol = simulate_model_dirac_secondorder(t,log10(p),k,[],options);
-</pre><p>FORWARD SENSITIVITY ANALYSIS</p><pre class="codeinput">    options.sensi = 2;
-
-    sol = simulate_model_dirac_secondorder(t,log10(p),k,[],options);
-</pre><p>FINITE DIFFERENCES</p><pre class="codeinput">    options.sensi = 1;
-
-    eps = 1e-4;
-    xi = log10(p);
-    <span class="keyword">for</span> ip = 1:4;
-        xip = xi;
-        xip(ip) = xip(ip) + eps;
-        solp = simulate_model_dirac_secondorder(t,xip,k,[],options);
-        s2x_fd(:,:,:,ip) = (solp.sx - sol.sx)/eps;
-        s2y_fd(:,:,:,ip) = (solp.sy - sol.sy)/eps;
-    <span class="keyword">end</span>
-</pre><p>PLOTTING</p><pre class="codeinput">    figure
-    c_x = get(gca,<span class="string">'ColorOrder'</span>);
-    <span class="keyword">for</span> ip = 1:4
-        <span class="keyword">for</span> jp = 1:4
-            subplot(4,4,(ip-1)*4+jp)
-            hold <span class="string">on</span>
-            <span class="keyword">for</span> ix = 1:size(sol.x,2)
-                plot(t,sol.s2x(:,ix,ip,jp),<span class="string">'.-'</span>,<span class="string">'Color'</span>,c_x(ix,:))
-                plot(t,s2x_fd(:,ix,ip,jp),<span class="string">'--'</span>,<span class="string">'Color'</span>,c_x(ix,:))
-            <span class="keyword">end</span>
-            ylim([-10,10])
-            legend(<span class="string">'x1'</span>,<span class="string">'x1_{fd}'</span>,<span class="string">'x2'</span>,<span class="string">'x2_{fd}'</span>,<span class="string">'Location'</span>,<span class="string">'NorthEastOutside'</span>)
-            legend <span class="string">boxoff</span>
-            title([<span class="string">'state sensitivity for p'</span> num2str(ip) <span class="string">'/p'</span> num2str(jp)])
-            xlabel(<span class="string">'time t'</span>)
-            ylabel(<span class="string">'x'</span>)
-            box <span class="string">on</span>
-        <span class="keyword">end</span>
-    <span class="keyword">end</span>
-    set(gcf,<span class="string">'Position'</span>,[100 300 1200 500])
-    figure
-    <span class="keyword">for</span> ip = 1:4
-        <span class="keyword">for</span> jp = 1:4
-            subplot(4,4,(ip-1)*4+jp)
-            plot(t,abs(sol.s2x(:,:,ip,jp)-s2x_fd(:,:,ip,jp)),<span class="string">'r--'</span>)
-            legend(<span class="string">'error x1'</span>,<span class="string">'error x2'</span>,<span class="string">'Location'</span>,<span class="string">'NorthEastOutside'</span>)
-            legend <span class="string">boxoff</span>
-            title([<span class="string">'state sensitivity for p'</span> num2str(ip) <span class="string">'/p'</span> num2str(jp)])
-            xlabel(<span class="string">'time t'</span>)
-            ylabel(<span class="string">'error'</span>)
-            ylim([1e-12,1e0])
-            set(gca,<span class="string">'YScale'</span>,<span class="string">'log'</span>)
-            box <span class="string">on</span>
-        <span class="keyword">end</span>
-    <span class="keyword">end</span>
-    set(gcf,<span class="string">'Position'</span>,[100 300 1200 500])
-
-    drawnow
-</pre><img vspace="5" hspace="5" src="../examples/example_dirac_secondorder/html/example_dirac_secondorder_01.png" alt=""> <img vspace="5" hspace="5" src="../examples/example_dirac_secondorder/html/example_dirac_secondorder_02.png" alt=""> <pre class="codeinput"><span class="keyword">end</span>
-</pre><p class="footer"><br><a href="http://www.mathworks.com/products/matlab/">Published with MATLAB&reg; R2016a</a><br></p></div><!--
-##### SOURCE BEGIN #####
-function example_dirac_secondorder()
-    %%
-    % COMPILATION
-    
-    [exdir,~,~]=fileparts(which('example_dirac_secondorder.m'));
-    % compile the model
-    amiwrap('model_dirac_secondorder','model_dirac_secondorder_syms',exdir,1)
-    
-    %%
-    % SIMULATION
-    
-    % time vector
-    t = linspace(0,3,1001);
-    p = [1;0.5;2;3];
-    k = [];
-    
-    options = amioption('sensi',0,...
-        'maxsteps',1e4);
-    
-    % load mex into memory
-    [msg] = which('simulate_model_secondorder_dirac'); % fix for inaccessability problems
-    options.sensi = 2;
-    sol = simulate_model_dirac_secondorder(t,log10(p),k,[],options);
-    
-    %%
-    % FORWARD SENSITIVITY ANALYSIS
-    
-    options.sensi = 2;
-    
-    sol = simulate_model_dirac_secondorder(t,log10(p),k,[],options);
-    
-    %%
-    % FINITE DIFFERENCES
-    
-    options.sensi = 1;
-    
-    eps = 1e-4;
-    xi = log10(p);
-    for ip = 1:4;
-        xip = xi;
-        xip(ip) = xip(ip) + eps;
-        solp = simulate_model_dirac_secondorder(t,xip,k,[],options);
-        s2x_fd(:,:,:,ip) = (solp.sx - sol.sx)/eps;
-        s2y_fd(:,:,:,ip) = (solp.sy - sol.sy)/eps;
-    end
-    
-    %%
-    % PLOTTING
-    figure
-    c_x = get(gca,'ColorOrder');
-    for ip = 1:4
-        for jp = 1:4
-            subplot(4,4,(ip-1)*4+jp)
-            hold on
-            for ix = 1:size(sol.x,2)
-                plot(t,sol.s2x(:,ix,ip,jp),'.-','Color',c_x(ix,:))
-                plot(t,s2x_fd(:,ix,ip,jp),'REPLACE_WITH_DASH_DASH','Color',c_x(ix,:))
-            end
-            ylim([-10,10])
-            legend('x1','x1_{fd}','x2','x2_{fd}','Location','NorthEastOutside')
-            legend boxoff
-            title(['state sensitivity for p' num2str(ip) '/p' num2str(jp)])
-            xlabel('time t')
-            ylabel('x')
-            box on
-        end
-    end
-    set(gcf,'Position',[100 300 1200 500])
-    figure
-    for ip = 1:4
-        for jp = 1:4
-            subplot(4,4,(ip-1)*4+jp)
-            plot(t,abs(sol.s2x(:,:,ip,jp)-s2x_fd(:,:,ip,jp)),'rREPLACE_WITH_DASH_DASH')
-            legend('error x1','error x2','Location','NorthEastOutside')
-            legend boxoff
-            title(['state sensitivity for p' num2str(ip) '/p' num2str(jp)])
-            xlabel('time t')
-            ylabel('error')
-            ylim([1e-12,1e0])
-            set(gca,'YScale','log')
-            box on
-        end
-    end
-    set(gcf,'Position',[100 300 1200 500])
-    
-    drawnow
-    
-end
-
-##### SOURCE END #####
---></body></html>
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diff --git a/matlab/examples/example_dirac_secondorder/html/example_dirac_secondorder.tex b/matlab/examples/example_dirac_secondorder/html/example_dirac_secondorder.tex
deleted file mode 100644
index 2bfcf40493..0000000000
--- a/matlab/examples/example_dirac_secondorder/html/example_dirac_secondorder.tex
+++ /dev/null
@@ -1,140 +0,0 @@
-
-% This LaTeX was auto-generated from MATLAB code.
-% To make changes, update the MATLAB code and republish this document.
-
-
-
-
-
-
-
-
-
-
-
-    
-    \begin{DoxyCode}
-function example_dirac_secondorder()
-\end{DoxyCode}
-\begin{par}
-COMPILATION
-\end{par} \vspace{1em}
-\begin{DoxyCode}
-    [exdir,~,~]=fileparts(which('example_dirac_secondorder.m'));
-    % compile the model
-    amiwrap('model_dirac_secondorder','model_dirac_secondorder_syms',exdir,1)
-\end{DoxyCode}
-
-         \begin{DoxyCode}Generating model struct ...
-x | k | p | deltax | xdot | deltaxdot | ddeltaxdx | ddeltaxdp | ddeltaxdt | root | drootdx | sx | drootdp | drootdt | dtaudp | sroot | stau | deltasx | sigma_y | dsigma_ydp | y | dydp | sigma_z | dsigma_zdp | z | dzdp | Parsing model struct ...
-z | 
-
-Generating C code ...
-deltasx | deltax | dsigma_ydp | dsigma_zdp | dydp | dzdp | root | sigma_y | sigma_z | stau | xdot | y | z | headers | wrapfunctions | 
-headers | wrapfunctions | 
-Compiling mex file ...
-amici | Building with 'Xcode with Clang'.
-MEX completed successfully.
-Building with 'Xcode with Clang'.
-MEX completed successfully.
-amici | Building with 'Xcode with Clang'.
-MEX completed successfully.
-Building with 'Xcode with Clang'.
-MEX completed successfully.
-\end{DoxyCode} 
-    \begin{par}
-SIMULATION
-\end{par} \vspace{1em}
-\begin{DoxyCode}
-    % time vector
-    t = linspace(0,3,1001);
-    p = [1;0.5;2;3];
-    k = [];
-
-    options = amioption('sensi',0,...
-        'maxsteps',1e4);
-
-    % load mex into memory
-    [msg] = which('simulate_model_secondorder_dirac'); % fix for inaccessability problems
-    options.sensi = 2;
-    sol = simulate_model_dirac_secondorder(t,log10(p),k,[],options);
-\end{DoxyCode}
-\begin{par}
-FORWARD SENSITIVITY ANALYSIS
-\end{par} \vspace{1em}
-\begin{DoxyCode}
-    options.sensi = 2;
-
-    sol = simulate_model_dirac_secondorder(t,log10(p),k,[],options);
-\end{DoxyCode}
-\begin{par}
-FINITE DIFFERENCES
-\end{par} \vspace{1em}
-\begin{DoxyCode}
-    options.sensi = 1;
-
-    eps = 1e-4;
-    xi = log10(p);
-    for ip = 1:4;
-        xip = xi;
-        xip(ip) = xip(ip) + eps;
-        solp = simulate_model_dirac_secondorder(t,xip,k,[],options);
-        s2x_fd(:,:,:,ip) = (solp.sx - sol.sx)/eps;
-        s2y_fd(:,:,:,ip) = (solp.sy - sol.sy)/eps;
-    end
-\end{DoxyCode}
-\begin{par}
-PLOTTING
-\end{par} \vspace{1em}
-\begin{DoxyCode}
-    figure
-    c_x = get(gca,'ColorOrder');
-    for ip = 1:4
-        for jp = 1:4
-            subplot(4,4,(ip-1)*4+jp)
-            hold on
-            for ix = 1:size(sol.x,2)
-                plot(t,sol.s2x(:,ix,ip,jp),'.-','Color',c_x(ix,:))
-                plot(t,s2x_fd(:,ix,ip,jp),'--','Color',c_x(ix,:))
-            end
-            ylim([-10,10])
-            legend('x1','x1_{fd}','x2','x2_{fd}','Location','NorthEastOutside')
-            legend boxoff
-            title(['state sensitivity for p' num2str(ip) '/p' num2str(jp)])
-            xlabel('time t')
-            ylabel('x')
-            box on
-        end
-    end
-    set(gcf,'Position',[100 300 1200 500])
-    figure
-    for ip = 1:4
-        for jp = 1:4
-            subplot(4,4,(ip-1)*4+jp)
-            plot(t,abs(sol.s2x(:,:,ip,jp)-s2x_fd(:,:,ip,jp)),'r--')
-            legend('error x1','error x2','Location','NorthEastOutside')
-            legend boxoff
-            title(['state sensitivity for p' num2str(ip) '/p' num2str(jp)])
-            xlabel('time t')
-            ylabel('error')
-            ylim([1e-12,1e0])
-            set(gca,'YScale','log')
-            box on
-        end
-    end
-    set(gcf,'Position',[100 300 1200 500])
-
-    drawnow
-\end{DoxyCode}
-
-\includegraphics[width=\textwidth]{../../examples/example_dirac_secondorder/html/example_dirac_secondorder_01.png}
-
-\includegraphics[width=\textwidth]{../../examples/example_dirac_secondorder/html/example_dirac_secondorder_02.png}
-\begin{DoxyCode}
-end
-\end{DoxyCode}
-
-
-
-
-    
\ No newline at end of file
diff --git a/matlab/examples/example_dirac_secondorder/html/example_dirac_secondorder_01.png b/matlab/examples/example_dirac_secondorder/html/example_dirac_secondorder_01.png
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-      --><title>model_dirac_secondorder_syms</title><meta name="generator" content="MATLAB 9.0"><link rel="schema.DC" href="http://purl.org/dc/elements/1.1/"><meta name="DC.date" content="2016-05-04"><meta name="DC.source" content="model_dirac_secondorder_syms.m"><style type="text/css">
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-
-  </style></head><body><div class="content"><pre class="codeinput"><span class="keyword">function</span> [model] = model_dirac_secondorder_syms()
-</pre><p>STATES</p><pre class="codeinput"><span class="comment">% create state syms</span>
-syms <span class="string">x1</span> <span class="string">x2</span>
-
-<span class="comment">% create state vector</span>
-model.sym.x = [ x1 x2 ];
-</pre><p>PARAMETERS ( for these sensitivities will be computed )</p><pre class="codeinput"><span class="comment">% create parameter syms</span>
-syms <span class="string">p1</span> <span class="string">p2</span> <span class="string">p3</span> <span class="string">p4</span>
-
-<span class="comment">% create parameter vector</span>
-model.sym.p = [p1,p2,p3,p4];
-
-<span class="comment">% set the parametrisation of the problem options are 'log', 'log10' and</span>
-<span class="comment">% 'lin' (default).</span>
-model.param = <span class="string">'log10'</span>;
-</pre><p>SYSTEM EQUATIONS</p><pre class="codeinput"><span class="comment">% create symbolic variable for time</span>
-syms <span class="string">t</span>
-
-model.sym.xdot = sym(zeros(size(model.sym.x)));
-
-<span class="comment">% piecewise defined function</span>
-model.sym.xdot(1) = -p1*x1 + dirac(t-p2);
-<span class="comment">% inhomogeneous</span>
-model.sym.xdot(2) = p3*x1 - p4*x2 ;
-</pre><p>INITIAL CONDITIONS</p><pre class="codeinput">model.sym.x0 = sym(zeros(size(model.sym.x)));
-
-model.sym.x0(1) = 0;
-model.sym.x0(2) = 0;
-</pre><p>OBSERVALES</p><pre class="codeinput">model.sym.y = sym(zeros(1,1));
-
-model.sym.y(1) = x2;
-</pre><pre class="codeinput"><span class="keyword">end</span>
-</pre><pre class="codeoutput">ans = 
-      sym: [1x1 struct]
-    param: 'log10'
-</pre><p class="footer"><br><a href="http://www.mathworks.com/products/matlab/">Published with MATLAB&reg; R2016a</a><br></p></div><!--
-##### SOURCE BEGIN #####
-function [model] = model_dirac_secondorder_syms()
-    
-%%
-% STATES
-
-% create state syms
-syms x1 x2
-
-% create state vector
-model.sym.x = [ x1 x2 ];
-
-%%
-% PARAMETERS ( for these sensitivities will be computed )
-
-% create parameter syms
-syms p1 p2 p3 p4
-
-% create parameter vector 
-model.sym.p = [p1,p2,p3,p4];
-
-% set the parametrisation of the problem options are 'log', 'log10' and
-% 'lin' (default).
-model.param = 'log10'; 
-
-%%
-% SYSTEM EQUATIONS
-
-% create symbolic variable for time
-syms t
-
-model.sym.xdot = sym(zeros(size(model.sym.x)));
-
-% piecewise defined function
-model.sym.xdot(1) = -p1*x1 + dirac(t-p2);
-% inhomogeneous
-model.sym.xdot(2) = p3*x1 - p4*x2 ;
-
-%%
-% INITIAL CONDITIONS
-
-model.sym.x0 = sym(zeros(size(model.sym.x)));
-
-model.sym.x0(1) = 0;
-model.sym.x0(2) = 0;
-
-%%
-% OBSERVALES
-
-model.sym.y = sym(zeros(1,1));
-
-model.sym.y(1) = x2;
-end
-##### SOURCE END #####
---></body></html>
\ No newline at end of file
diff --git a/matlab/examples/example_dirac_secondorder/html/model_dirac_secondorder_syms.tex b/matlab/examples/example_dirac_secondorder/html/model_dirac_secondorder_syms.tex
deleted file mode 100644
index fd51e9978f..0000000000
--- a/matlab/examples/example_dirac_secondorder/html/model_dirac_secondorder_syms.tex
+++ /dev/null
@@ -1,86 +0,0 @@
-
-% This LaTeX was auto-generated from MATLAB code.
-% To make changes, update the MATLAB code and republish this document.
-
-
-
-
-
-
-
-
-
-
-
-    
-    \begin{DoxyCode}
-function [model] = model_dirac_secondorder_syms()
-\end{DoxyCode}
-\begin{par}
-STATES
-\end{par} \vspace{1em}
-\begin{DoxyCode}
-% create state syms
-syms x1 x2
-
-% create state vector
-model.sym.x = [ x1 x2 ];
-\end{DoxyCode}
-\begin{par}
-PARAMETERS ( for these sensitivities will be computed )
-\end{par} \vspace{1em}
-\begin{DoxyCode}
-% create parameter syms
-syms p1 p2 p3 p4
-
-% create parameter vector
-model.sym.p = [p1,p2,p3,p4];
-
-% set the parametrisation of the problem options are 'log', 'log10' and
-% 'lin' (default).
-model.param = 'log10';
-\end{DoxyCode}
-\begin{par}
-SYSTEM EQUATIONS
-\end{par} \vspace{1em}
-\begin{DoxyCode}
-% create symbolic variable for time
-syms t
-
-model.sym.xdot = sym(zeros(size(model.sym.x)));
-
-% piecewise defined function
-model.sym.xdot(1) = -p1*x1 + dirac(t-p2);
-% inhomogeneous
-model.sym.xdot(2) = p3*x1 - p4*x2 ;
-\end{DoxyCode}
-\begin{par}
-INITIAL CONDITIONS
-\end{par} \vspace{1em}
-\begin{DoxyCode}
-model.sym.x0 = sym(zeros(size(model.sym.x)));
-
-model.sym.x0(1) = 0;
-model.sym.x0(2) = 0;
-\end{DoxyCode}
-\begin{par}
-OBSERVALES
-\end{par} \vspace{1em}
-\begin{DoxyCode}
-model.sym.y = sym(zeros(1,1));
-
-model.sym.y(1) = x2;
-\end{DoxyCode}
-\begin{DoxyCode}
-end
-\end{DoxyCode}
-
-         \begin{DoxyCode}ans = 
-      sym: [1x1 struct]
-    param: 'log10'
-\end{DoxyCode} 
-    
-
-
-
-    
\ No newline at end of file
diff --git a/matlab/examples/example_dirac_secondorder_vectmult/html/example_dirac_secondorder_vectmult.html b/matlab/examples/example_dirac_secondorder_vectmult/html/example_dirac_secondorder_vectmult.html
deleted file mode 100644
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-pre.error { color:red; }
-
-@media print { pre.codeinput, pre.codeoutput { word-wrap:break-word; width:100%; } }
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-.footer { width:auto; padding:10px 0px; margin:25px 0px 0px; border-top:1px dotted #878787; font-size:0.8em; line-height:140%; font-style:italic; color:#878787; text-align:left; float:none; }
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-
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-
-
-  </style></head><body><div class="content"><pre class="codeinput"><span class="keyword">function</span> example_dirac_secondorder_vectmult()
-</pre><p>COMPILATION</p><pre class="codeinput">    [exdir,~,~]=fileparts(which(<span class="string">'example_dirac_secondorder_vectmult.m'</span>));
-    <span class="comment">% compile the model</span>
-    amiwrap(<span class="string">'model_dirac_secondorder_vectmult'</span>,<span class="string">'model_dirac_secondorder_vectmult_syms'</span>,exdir,2)
-</pre><pre class="codeoutput">Generating model struct ...
-x | k | p | deltax | xdot | deltaxdot | ddeltaxdx | ddeltaxdp | ddeltaxdt | root | drootdx | sx | drootdp | drootdt | dtaudp | sroot | stau | deltasx | sigma_y | dsigma_ydp | y | dydp | sigma_z | dsigma_zdp | z | dzdp | Parsing model struct ...
-z | Generating C code ...
-deltasx | deltax | dsigma_ydp | dsigma_zdp | dydp | dzdp | root | sigma_y | sigma_z | stau | xdot | y | z | headers | wrapfunctions | headers | wrapfunctions | Compiling mex file ...
-amici | Building with 'Xcode with Clang'.
-MEX completed successfully.
-Building with 'Xcode with Clang'.
-MEX completed successfully.
-amici | Building with 'Xcode with Clang'.
-MEX completed successfully.
-Building with 'Xcode with Clang'.
-MEX completed successfully.
-</pre><p>SIMULATION</p><pre class="codeinput">    <span class="comment">% time vector</span>
-    t = linspace(0,3,1001);
-    p = [1;0.5;2;3];
-    k = [];
-    v = [0.7;0.3;1.4;0.1];
-
-    options = amioption(<span class="string">'sensi'</span>,0,<span class="keyword">...</span>
-        <span class="string">'maxsteps'</span>,1e4);
-
-    <span class="comment">% load mex into memory</span>
-    [msg] = which(<span class="string">'model_dirac_secondorder_vectmult'</span>); <span class="comment">% fix for inaccessability problems</span>
-    options.sensi = 2;
-    sol = simulate_model_dirac_secondorder_vectmult(t,log10(p),k,[],options,v);
-</pre><p>FORWARD SENSITIVITY ANALYSIS</p><pre class="codeinput">    options.sensi = 2;
-
-    sol = simulate_model_dirac_secondorder_vectmult(t,log10(p),k,[],options,v);
-</pre><p>FINITE DIFFERENCES</p><pre class="codeinput">    options.sensi = 1;
-
-    eps = 1e-4;
-    xi = log10(p);
-    <span class="keyword">for</span> ip = 1:4;
-        xip = xi;
-        xip(ip) = xip(ip) + eps;
-        solp = simulate_model_dirac_secondorder_vectmult(t,xip,k,[],options);
-        s2x_fd(:,:,ip) = sum(bsxfun(@times,(solp.sx - sol.sx)/eps,permute(v,[3,2,1])),3);
-        s2y_fd(:,:,ip) = sum(bsxfun(@times,(solp.sy - sol.sy)/eps,permute(v,[3,2,1])),3);
-    <span class="keyword">end</span>
-</pre><p>PLOTTING</p><pre class="codeinput">    figure
-    c_x = get(gca,<span class="string">'ColorOrder'</span>);
-    <span class="keyword">for</span> ip = 1:4
-        subplot(4,2,ip*2-1)
-        hold <span class="string">on</span>
-        <span class="keyword">for</span> ix = 1:size(sol.x,2)
-            plot(t,sol.s2x(:,ix,ip),<span class="string">'.-'</span>,<span class="string">'Color'</span>,c_x(ix,:))
-            plot(t,s2x_fd(:,ix,ip),<span class="string">'--'</span>,<span class="string">'Color'</span>,c_x(ix,:))
-        <span class="keyword">end</span>
-        ylim([-10,10])
-        legend(<span class="string">'x1'</span>,<span class="string">'x1_{fd}'</span>,<span class="string">'x2'</span>,<span class="string">'x2_{fd}'</span>,<span class="string">'Location'</span>,<span class="string">'NorthEastOutside'</span>)
-        legend <span class="string">boxoff</span>
-        title([<span class="string">'state sensitivity for p'</span> num2str(ip)])
-        xlabel(<span class="string">'time t'</span>)
-        ylabel(<span class="string">'x'</span>)
-        box <span class="string">on</span>
-
-        subplot(4,2,ip*2)
-        plot(t,abs(sol.s2x(:,:,ip)-s2x_fd(:,:,ip)),<span class="string">'r--'</span>)
-        legend(<span class="string">'error x1'</span>,<span class="string">'error x2'</span>,<span class="string">'Location'</span>,<span class="string">'NorthEastOutside'</span>)
-        legend <span class="string">boxoff</span>
-        title([<span class="string">'state sensitivity for p'</span> num2str(ip)])
-        xlabel(<span class="string">'time t'</span>)
-        ylabel(<span class="string">'error'</span>)
-        ylim([1e-12,1e0])
-        set(gca,<span class="string">'YScale'</span>,<span class="string">'log'</span>)
-        box <span class="string">on</span>
-    <span class="keyword">end</span>
-    set(gcf,<span class="string">'Position'</span>,[100 300 1200 500])
-
-    figure
-    <span class="keyword">for</span> ip = 1:4
-        subplot(4,2,ip*2-1)
-        hold <span class="string">on</span>
-        <span class="keyword">for</span> iy = 1:size(sol.y,2)
-            plot(t,sol.s2y(:,iy,ip),<span class="string">'.-'</span>,<span class="string">'Color'</span>,c_x(iy,:))
-            plot(t,s2y_fd(:,iy,ip),<span class="string">'--'</span>,<span class="string">'Color'</span>,c_x(iy,:))
-        <span class="keyword">end</span>
-        ylim([-10,10])
-        legend(<span class="string">'y1'</span>,<span class="string">'y1_{fd}'</span>,<span class="string">'Location'</span>,<span class="string">'NorthEastOutside'</span>)
-        legend <span class="string">boxoff</span>
-        title([<span class="string">'observable sensitivity for p'</span> num2str(ip)])
-        xlabel(<span class="string">'time t'</span>)
-        ylabel(<span class="string">'y'</span>)
-        box <span class="string">on</span>
-
-        subplot(4,2,ip*2)
-        plot(t,abs(sol.s2y(:,:,ip)-s2y_fd(:,:,ip)),<span class="string">'r--'</span>)
-        legend(<span class="string">'error y1'</span>,<span class="string">'Location'</span>,<span class="string">'NorthEastOutside'</span>)
-        legend <span class="string">boxoff</span>
-        title([<span class="string">'observable sensitivity for p'</span> num2str(ip)])
-        xlabel(<span class="string">'time t'</span>)
-        ylabel(<span class="string">'error'</span>)
-        ylim([1e-12,1e0])
-        set(gca,<span class="string">'YScale'</span>,<span class="string">'log'</span>)
-        box <span class="string">on</span>
-    <span class="keyword">end</span>
-    set(gcf,<span class="string">'Position'</span>,[100 300 1200 500])
-
-    drawnow
-</pre><img vspace="5" hspace="5" src="../examples/example_dirac_secondorder_vectmult/html/example_dirac_secondorder_vectmult_01.png" alt=""> <img vspace="5" hspace="5" src="../examples/example_dirac_secondorder_vectmult/html/example_dirac_secondorder_vectmult_02.png" alt=""> <pre class="codeinput"><span class="keyword">end</span>
-</pre><p class="footer"><br><a href="http://www.mathworks.com/products/matlab/">Published with MATLAB&reg; R2016a</a><br></p></div><!--
-##### SOURCE BEGIN #####
-function example_dirac_secondorder_vectmult()
-    %%
-    % COMPILATION
-    
-    [exdir,~,~]=fileparts(which('example_dirac_secondorder_vectmult.m'));
-    % compile the model
-    amiwrap('model_dirac_secondorder_vectmult','model_dirac_secondorder_vectmult_syms',exdir,2)
-    
-    %%
-    % SIMULATION
-    
-    % time vector
-    t = linspace(0,3,1001);
-    p = [1;0.5;2;3];
-    k = [];
-    v = [0.7;0.3;1.4;0.1];
-    
-    options = amioption('sensi',0,...
-        'maxsteps',1e4);
-    
-    % load mex into memory
-    [msg] = which('model_dirac_secondorder_vectmult'); % fix for inaccessability problems
-    options.sensi = 2;
-    sol = simulate_model_dirac_secondorder_vectmult(t,log10(p),k,[],options,v);
-    
-    %%
-    % FORWARD SENSITIVITY ANALYSIS
-    
-    options.sensi = 2;
-    
-    sol = simulate_model_dirac_secondorder_vectmult(t,log10(p),k,[],options,v);
-    
-    %%
-    % FINITE DIFFERENCES
-    
-    options.sensi = 1;
-    
-    eps = 1e-4;
-    xi = log10(p);
-    for ip = 1:4;
-        xip = xi;
-        xip(ip) = xip(ip) + eps;
-        solp = simulate_model_dirac_secondorder_vectmult(t,xip,k,[],options);
-        s2x_fd(:,:,ip) = sum(bsxfun(@times,(solp.sx - sol.sx)/eps,permute(v,[3,2,1])),3);
-        s2y_fd(:,:,ip) = sum(bsxfun(@times,(solp.sy - sol.sy)/eps,permute(v,[3,2,1])),3);
-    end
-    
-    %%
-    % PLOTTING
-    
-    figure
-    c_x = get(gca,'ColorOrder');
-    for ip = 1:4
-        subplot(4,2,ip*2-1)
-        hold on
-        for ix = 1:size(sol.x,2)
-            plot(t,sol.s2x(:,ix,ip),'.-','Color',c_x(ix,:))
-            plot(t,s2x_fd(:,ix,ip),'REPLACE_WITH_DASH_DASH','Color',c_x(ix,:))
-        end
-        ylim([-10,10])
-        legend('x1','x1_{fd}','x2','x2_{fd}','Location','NorthEastOutside')
-        legend boxoff
-        title(['state sensitivity for p' num2str(ip)])
-        xlabel('time t')
-        ylabel('x')
-        box on
-        
-        subplot(4,2,ip*2)
-        plot(t,abs(sol.s2x(:,:,ip)-s2x_fd(:,:,ip)),'rREPLACE_WITH_DASH_DASH')
-        legend('error x1','error x2','Location','NorthEastOutside')
-        legend boxoff
-        title(['state sensitivity for p' num2str(ip)])
-        xlabel('time t')
-        ylabel('error')
-        ylim([1e-12,1e0])
-        set(gca,'YScale','log')
-        box on
-    end
-    set(gcf,'Position',[100 300 1200 500])
-    
-    figure
-    for ip = 1:4
-        subplot(4,2,ip*2-1)
-        hold on
-        for iy = 1:size(sol.y,2)
-            plot(t,sol.s2y(:,iy,ip),'.-','Color',c_x(iy,:))
-            plot(t,s2y_fd(:,iy,ip),'REPLACE_WITH_DASH_DASH','Color',c_x(iy,:))
-        end
-        ylim([-10,10])
-        legend('y1','y1_{fd}','Location','NorthEastOutside')
-        legend boxoff
-        title(['observable sensitivity for p' num2str(ip)])
-        xlabel('time t')
-        ylabel('y')
-        box on
-        
-        subplot(4,2,ip*2)
-        plot(t,abs(sol.s2y(:,:,ip)-s2y_fd(:,:,ip)),'rREPLACE_WITH_DASH_DASH')
-        legend('error y1','Location','NorthEastOutside')
-        legend boxoff
-        title(['observable sensitivity for p' num2str(ip)])
-        xlabel('time t')
-        ylabel('error')
-        ylim([1e-12,1e0])
-        set(gca,'YScale','log')
-        box on
-    end
-    set(gcf,'Position',[100 300 1200 500])
-    
-    drawnow
-    
-end
-##### SOURCE END #####
---></body></html>
\ No newline at end of file
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diff --git a/matlab/examples/example_dirac_secondorder_vectmult/html/example_dirac_secondorder_vectmult.tex b/matlab/examples/example_dirac_secondorder_vectmult/html/example_dirac_secondorder_vectmult.tex
deleted file mode 100644
index 588100d553..0000000000
--- a/matlab/examples/example_dirac_secondorder_vectmult/html/example_dirac_secondorder_vectmult.tex
+++ /dev/null
@@ -1,163 +0,0 @@
-
-% This LaTeX was auto-generated from MATLAB code.
-% To make changes, update the MATLAB code and republish this document.
-
-
-
-
-
-
-
-
-
-
-
-    
-    \begin{DoxyCode}
-function example_dirac_secondorder_vectmult()
-\end{DoxyCode}
-\begin{par}
-COMPILATION
-\end{par} \vspace{1em}
-\begin{DoxyCode}
-    [exdir,~,~]=fileparts(which('example_dirac_secondorder_vectmult.m'));
-    % compile the model
-    amiwrap('model_dirac_secondorder_vectmult','model_dirac_secondorder_vectmult_syms',exdir,2)
-\end{DoxyCode}
-
-         \begin{DoxyCode}Generating model struct ...
-x | k | p | deltax | xdot | deltaxdot | ddeltaxdx | ddeltaxdp | ddeltaxdt | root | drootdx | sx | drootdp | drootdt | dtaudp | sroot | stau | deltasx | sigma_y | dsigma_ydp | y | dydp | sigma_z | dsigma_zdp | z | dzdp | Parsing model struct ...
-z | 
-
-Generating C code ...
-deltasx | deltax | dsigma_ydp | dsigma_zdp | dydp | dzdp | root | sigma_y | sigma_z | stau | xdot | y | z | headers | wrapfunctions | 
-headers | wrapfunctions | 
-Compiling mex file ...
-amici | Building with 'Xcode with Clang'.
-MEX completed successfully.
-Building with 'Xcode with Clang'.
-MEX completed successfully.
-amici | Building with 'Xcode with Clang'.
-MEX completed successfully.
-Building with 'Xcode with Clang'.
-MEX completed successfully.
-\end{DoxyCode} 
-    \begin{par}
-SIMULATION
-\end{par} \vspace{1em}
-\begin{DoxyCode}
-    % time vector
-    t = linspace(0,3,1001);
-    p = [1;0.5;2;3];
-    k = [];
-    v = [0.7;0.3;1.4;0.1];
-
-    options = amioption('sensi',0,...
-        'maxsteps',1e4);
-
-    % load mex into memory
-    [msg] = which('model_dirac_secondorder_vectmult'); % fix for inaccessability problems
-    options.sensi = 2;
-    sol = simulate_model_dirac_secondorder_vectmult(t,log10(p),k,[],options,v);
-\end{DoxyCode}
-\begin{par}
-FORWARD SENSITIVITY ANALYSIS
-\end{par} \vspace{1em}
-\begin{DoxyCode}
-    options.sensi = 2;
-
-    sol = simulate_model_dirac_secondorder_vectmult(t,log10(p),k,[],options,v);
-\end{DoxyCode}
-\begin{par}
-FINITE DIFFERENCES
-\end{par} \vspace{1em}
-\begin{DoxyCode}
-    options.sensi = 1;
-
-    eps = 1e-4;
-    xi = log10(p);
-    for ip = 1:4;
-        xip = xi;
-        xip(ip) = xip(ip) + eps;
-        solp = simulate_model_dirac_secondorder_vectmult(t,xip,k,[],options);
-        s2x_fd(:,:,ip) = sum(bsxfun(@times,(solp.sx - sol.sx)/eps,permute(v,[3,2,1])),3);
-        s2y_fd(:,:,ip) = sum(bsxfun(@times,(solp.sy - sol.sy)/eps,permute(v,[3,2,1])),3);
-    end
-\end{DoxyCode}
-\begin{par}
-PLOTTING
-\end{par} \vspace{1em}
-\begin{DoxyCode}
-    figure
-    c_x = get(gca,'ColorOrder');
-    for ip = 1:4
-        subplot(4,2,ip*2-1)
-        hold on
-        for ix = 1:size(sol.x,2)
-            plot(t,sol.s2x(:,ix,ip),'.-','Color',c_x(ix,:))
-            plot(t,s2x_fd(:,ix,ip),'--','Color',c_x(ix,:))
-        end
-        ylim([-10,10])
-        legend('x1','x1_{fd}','x2','x2_{fd}','Location','NorthEastOutside')
-        legend boxoff
-        title(['state sensitivity for p' num2str(ip)])
-        xlabel('time t')
-        ylabel('x')
-        box on
-
-        subplot(4,2,ip*2)
-        plot(t,abs(sol.s2x(:,:,ip)-s2x_fd(:,:,ip)),'r--')
-        legend('error x1','error x2','Location','NorthEastOutside')
-        legend boxoff
-        title(['state sensitivity for p' num2str(ip)])
-        xlabel('time t')
-        ylabel('error')
-        ylim([1e-12,1e0])
-        set(gca,'YScale','log')
-        box on
-    end
-    set(gcf,'Position',[100 300 1200 500])
-
-    figure
-    for ip = 1:4
-        subplot(4,2,ip*2-1)
-        hold on
-        for iy = 1:size(sol.y,2)
-            plot(t,sol.s2y(:,iy,ip),'.-','Color',c_x(iy,:))
-            plot(t,s2y_fd(:,iy,ip),'--','Color',c_x(iy,:))
-        end
-        ylim([-10,10])
-        legend('y1','y1_{fd}','Location','NorthEastOutside')
-        legend boxoff
-        title(['observable sensitivity for p' num2str(ip)])
-        xlabel('time t')
-        ylabel('y')
-        box on
-
-        subplot(4,2,ip*2)
-        plot(t,abs(sol.s2y(:,:,ip)-s2y_fd(:,:,ip)),'r--')
-        legend('error y1','Location','NorthEastOutside')
-        legend boxoff
-        title(['observable sensitivity for p' num2str(ip)])
-        xlabel('time t')
-        ylabel('error')
-        ylim([1e-12,1e0])
-        set(gca,'YScale','log')
-        box on
-    end
-    set(gcf,'Position',[100 300 1200 500])
-
-    drawnow
-\end{DoxyCode}
-
-\includegraphics[width=\textwidth]{../../examples/example_dirac_secondorder_vectmult/html/example_dirac_secondorder_vectmult_01.png}
-
-\includegraphics[width=\textwidth]{../../examples/example_dirac_secondorder_vectmult/html/example_dirac_secondorder_vectmult_02.png}
-\begin{DoxyCode}
-end
-\end{DoxyCode}
-
-
-
-
-    
\ No newline at end of file
diff --git a/matlab/examples/example_dirac_secondorder_vectmult/html/example_dirac_secondorder_vectmult_01.png b/matlab/examples/example_dirac_secondorder_vectmult/html/example_dirac_secondorder_vectmult_01.png
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-      --><title>model_dirac_secondorder_vectmult_syms</title><meta name="generator" content="MATLAB 9.0"><link rel="schema.DC" href="http://purl.org/dc/elements/1.1/"><meta name="DC.date" content="2016-05-04"><meta name="DC.source" content="model_dirac_secondorder_vectmult_syms.m"><style type="text/css">
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-  </style></head><body><div class="content"><pre class="codeinput"><span class="keyword">function</span> [model] = model_dirac_secondorder_vectmult_syms()
-</pre><p>STATES</p><pre class="codeinput"><span class="comment">% create state syms</span>
-syms <span class="string">x1</span> <span class="string">x2</span>
-
-<span class="comment">% create state vector</span>
-model.sym.x = [ x1 x2 ];
-</pre><p>PARAMETERS ( for these sensitivities will be computed )</p><pre class="codeinput"><span class="comment">% create parameter syms</span>
-syms <span class="string">p1</span> <span class="string">p2</span> <span class="string">p3</span> <span class="string">p4</span>
-
-<span class="comment">% create parameter vector</span>
-model.sym.p = [p1,p2,p3,p4];
-
-<span class="comment">% set the parametrisation of the problem options are 'log', 'log10' and</span>
-<span class="comment">% 'lin' (default).</span>
-model.param = <span class="string">'log10'</span>;
-</pre><p>SYSTEM EQUATIONS</p><pre class="codeinput"><span class="comment">% create symbolic variable for time</span>
-syms <span class="string">t</span>
-
-model.sym.xdot = sym(zeros(size(model.sym.x)));
-
-<span class="comment">% piecewise defined function</span>
-model.sym.xdot(1) = -p1*x1 + dirac(t-p2);
-<span class="comment">% inhomogeneous</span>
-model.sym.xdot(2) = p3*x1 - p4*x2 ;
-</pre><p>INITIAL CONDITIONS</p><pre class="codeinput">model.sym.x0 = sym(zeros(size(model.sym.x)));
-
-model.sym.x0(1) = 0;
-model.sym.x0(2) = 0;
-</pre><p>OBSERVALES</p><pre class="codeinput">model.sym.y = sym(zeros(1,1));
-
-model.sym.y(1) = x2;
-</pre><pre class="codeinput"><span class="keyword">end</span>
-</pre><pre class="codeoutput">ans = 
-      sym: [1x1 struct]
-    param: 'log10'
-</pre><p class="footer"><br><a href="http://www.mathworks.com/products/matlab/">Published with MATLAB&reg; R2016a</a><br></p></div><!--
-##### SOURCE BEGIN #####
-function [model] = model_dirac_secondorder_vectmult_syms()
-    
-%%
-% STATES
-
-% create state syms
-syms x1 x2
-
-% create state vector
-model.sym.x = [ x1 x2 ];
-
-%%
-% PARAMETERS ( for these sensitivities will be computed )
-
-% create parameter syms
-syms p1 p2 p3 p4
-
-% create parameter vector 
-model.sym.p = [p1,p2,p3,p4];
-
-% set the parametrisation of the problem options are 'log', 'log10' and
-% 'lin' (default).
-model.param = 'log10'; 
-
-%%
-% SYSTEM EQUATIONS
-
-% create symbolic variable for time
-syms t
-
-model.sym.xdot = sym(zeros(size(model.sym.x)));
-
-% piecewise defined function
-model.sym.xdot(1) = -p1*x1 + dirac(t-p2);
-% inhomogeneous
-model.sym.xdot(2) = p3*x1 - p4*x2 ;
-
-%%
-% INITIAL CONDITIONS
-
-model.sym.x0 = sym(zeros(size(model.sym.x)));
-
-model.sym.x0(1) = 0;
-model.sym.x0(2) = 0;
-
-%%
-% OBSERVALES
-
-model.sym.y = sym(zeros(1,1));
-
-model.sym.y(1) = x2;
-end
-##### SOURCE END #####
---></body></html>
\ No newline at end of file
diff --git a/matlab/examples/example_dirac_secondorder_vectmult/html/model_dirac_secondorder_vectmult_syms.tex b/matlab/examples/example_dirac_secondorder_vectmult/html/model_dirac_secondorder_vectmult_syms.tex
deleted file mode 100644
index 3574b25f42..0000000000
--- a/matlab/examples/example_dirac_secondorder_vectmult/html/model_dirac_secondorder_vectmult_syms.tex
+++ /dev/null
@@ -1,86 +0,0 @@
-
-% This LaTeX was auto-generated from MATLAB code.
-% To make changes, update the MATLAB code and republish this document.
-
-
-
-
-
-
-
-
-
-
-
-    
-    \begin{DoxyCode}
-function [model] = model_dirac_secondorder_vectmult_syms()
-\end{DoxyCode}
-\begin{par}
-STATES
-\end{par} \vspace{1em}
-\begin{DoxyCode}
-% create state syms
-syms x1 x2
-
-% create state vector
-model.sym.x = [ x1 x2 ];
-\end{DoxyCode}
-\begin{par}
-PARAMETERS ( for these sensitivities will be computed )
-\end{par} \vspace{1em}
-\begin{DoxyCode}
-% create parameter syms
-syms p1 p2 p3 p4
-
-% create parameter vector
-model.sym.p = [p1,p2,p3,p4];
-
-% set the parametrisation of the problem options are 'log', 'log10' and
-% 'lin' (default).
-model.param = 'log10';
-\end{DoxyCode}
-\begin{par}
-SYSTEM EQUATIONS
-\end{par} \vspace{1em}
-\begin{DoxyCode}
-% create symbolic variable for time
-syms t
-
-model.sym.xdot = sym(zeros(size(model.sym.x)));
-
-% piecewise defined function
-model.sym.xdot(1) = -p1*x1 + dirac(t-p2);
-% inhomogeneous
-model.sym.xdot(2) = p3*x1 - p4*x2 ;
-\end{DoxyCode}
-\begin{par}
-INITIAL CONDITIONS
-\end{par} \vspace{1em}
-\begin{DoxyCode}
-model.sym.x0 = sym(zeros(size(model.sym.x)));
-
-model.sym.x0(1) = 0;
-model.sym.x0(2) = 0;
-\end{DoxyCode}
-\begin{par}
-OBSERVALES
-\end{par} \vspace{1em}
-\begin{DoxyCode}
-model.sym.y = sym(zeros(1,1));
-
-model.sym.y(1) = x2;
-\end{DoxyCode}
-\begin{DoxyCode}
-end
-\end{DoxyCode}
-
-         \begin{DoxyCode}ans = 
-      sym: [1x1 struct]
-    param: 'log10'
-\end{DoxyCode} 
-    
-
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-    
\ No newline at end of file
diff --git a/matlab/examples/example_events/html/example_events.html b/matlab/examples/example_events/html/example_events.html
deleted file mode 100644
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--- a/matlab/examples/example_events/html/example_events.html
+++ /dev/null
@@ -1,441 +0,0 @@
-
-<!DOCTYPE html
-  PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN">
-<html><head>
-      <meta http-equiv="Content-Type" content="text/html; charset=utf-8">
-   <!--
-This HTML was auto-generated from MATLAB code.
-To make changes, update the MATLAB code and republish this document.
-      --><title>example_events</title><meta name="generator" content="MATLAB 9.0"><link rel="schema.DC" href="http://purl.org/dc/elements/1.1/"><meta name="DC.date" content="2016-05-04"><meta name="DC.source" content="example_events.m"><style type="text/css">
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-
-
-
-
-
-  </style></head><body><div class="content"><pre class="codeinput"><span class="keyword">function</span> example_events()
-</pre><p>COMPILATION</p><pre class="codeinput">[exdir,~,~]=fileparts(which(<span class="string">'example_events.m'</span>));
-<span class="comment">% compile the model</span>
-amiwrap(<span class="string">'model_events'</span>,<span class="string">'model_events_syms'</span>,exdir)
-</pre><pre class="codeoutput">Generating model struct ...
-Parsing model struct ...
-Generating C code ...
-headers | wrapfunctions | Compiling mex file ...
-amici | Building with 'Xcode with Clang'.
-MEX completed successfully.
-Building with 'Xcode with Clang'.
-MEX completed successfully.
-</pre><p>SIMULATION</p><pre class="codeinput"><span class="comment">% time vector</span>
-t = linspace(0,10,20);
-p = [0.5;2;0.5;0.5];
-k = [4,8,10,4];
-
-options = amioption(<span class="string">'sensi'</span>,0,<span class="keyword">...</span>
-    <span class="string">'maxsteps'</span>,1e4,<span class="keyword">...</span>
-    <span class="string">'nmaxevent'</span>, 2);
-D = amidata(length(t),1,2,2,4);
-<span class="comment">% load mex into memory</span>
-[~] = which(<span class="string">'simulate_model_events'</span>); <span class="comment">% fix for inaccessability problems</span>
-sol = simulate_model_events(t,log10(p),k,D,options);
-
-tic
-sol = simulate_model_events(t,log10(p),k,D,options);
-disp([<span class="string">'Time elapsed with cvodes: '</span> num2str(toc) ])
-</pre><pre class="codeoutput">Time elapsed with cvodes: 0.0033863
-</pre><p>ODE15S</p><pre class="codeinput">ode_system = @(t,x,p,k) [-p(1)*heaviside(t-p(4))*x(1);
-    +p(2)*x(1)*exp(-0.1*t)-p(3)*x(2);
-    -1.5*x(3)];
-<span class="comment">% event_fn = @(t,x) [x(3) - x(2);</span>
-<span class="comment">%     x(3) - x(1)];</span>
-<span class="comment">% 'Events',event_fn</span>
-options_ode15s = odeset(<span class="string">'RelTol'</span>,options.rtol,<span class="string">'AbsTol'</span>,options.atol,<span class="string">'MaxStep'</span>,options.maxsteps);
-
-tic
-[~, X_ode15s] = ode15s(@(t,x) ode_system(t,x,p,k),t,k(1:3),options_ode15s);
-disp([<span class="string">'Time elapsed with ode15s: '</span> num2str(toc) ])
-</pre><pre class="codeoutput">Time elapsed with ode15s: 0.13084
-</pre><p>PLOTTING</p><pre class="codeinput">figure
-c_x = get(gca,<span class="string">'ColorOrder'</span>);
-subplot(2,2,1)
-<span class="keyword">for</span> ix = 1:size(sol.x,2)
-    plot(t,sol.x(:,ix),<span class="string">'.-'</span>,<span class="string">'Color'</span>,c_x(ix,:))
-    hold <span class="string">on</span>
-    plot(t,X_ode15s(:,ix),<span class="string">'d'</span>,<span class="string">'Color'</span>,c_x(ix,:))
-<span class="keyword">end</span>
-stem(sol.z(:,1),sol.z(:,1)*0+10,<span class="string">'r'</span>)
-stem(sol.z(:,2),sol.z(:,2)*0+10,<span class="string">'k'</span>)
-legend(<span class="string">'x1'</span>,<span class="string">'x1_{ode15s}'</span>,<span class="string">'x2'</span>,<span class="string">'x2_{ode15s}'</span>,<span class="string">'x3'</span>,<span class="string">'x3_{ode15s}'</span>,<span class="string">'x3==x2'</span>,<span class="string">'x3==x1'</span>,<span class="string">'Location'</span>,<span class="string">'NorthEastOutside'</span>)
-legend <span class="string">boxoff</span>
-xlabel(<span class="string">'time t'</span>)
-ylabel(<span class="string">'x'</span>)
-box <span class="string">on</span>
-subplot(2,2,2)
-plot(t,abs(sol.x-X_ode15s),<span class="string">'--'</span>)
-set(gca,<span class="string">'YScale'</span>,<span class="string">'log'</span>)
-legend(<span class="string">'error x1'</span>,<span class="string">'error x2'</span>,<span class="string">'error x3'</span>,<span class="string">'Location'</span>,<span class="string">'NorthEastOutside'</span>)
-legend <span class="string">boxoff</span>
-ylabel(<span class="string">'x'</span>)
-
-subplot(2,2,3)
-plot(t,sol.y,<span class="string">'.-'</span>,<span class="string">'Color'</span>,c_x(1,:))
-hold <span class="string">on</span>
-plot(t,p(4)*sum(X_ode15s,2),<span class="string">'d'</span>,<span class="string">'Color'</span>,c_x(1,:))
-legend(<span class="string">'y1'</span>,<span class="string">'y1_{ode15s}'</span>,<span class="string">'Location'</span>,<span class="string">'NorthEastOutside'</span>)
-legend <span class="string">boxoff</span>
-xlabel(<span class="string">'time t'</span>)
-ylabel(<span class="string">'y'</span>)
-box <span class="string">on</span>
-
-subplot(2,2,4)
-plot(t,abs(sol.y-p(4)*sum(X_ode15s,2)),<span class="string">'--'</span>)
-set(gca,<span class="string">'YScale'</span>,<span class="string">'log'</span>)
-legend(<span class="string">'error y1'</span>,<span class="string">'Location'</span>,<span class="string">'NorthEastOutside'</span>)
-legend <span class="string">boxoff</span>
-xlabel(<span class="string">'time t'</span>)
-ylabel(<span class="string">'y'</span>)
-box <span class="string">on</span>
-
-set(gcf,<span class="string">'Position'</span>,[100 300 1200 500])
-</pre><img vspace="5" hspace="5" src="../examples/example_events/html/example_events_01.png" alt=""> <p>FORWARD SENSITIVITY ANALYSIS</p><pre class="codeinput">options.sensi = 1;
-
-sol = simulate_model_events(t,log10(p),k,D,options);
-</pre><p>FINITE DIFFERENCES</p><pre class="codeinput">eps = 1e-4;
-xi = log10(p);
-<span class="keyword">for</span> ip = 1:4;
-    xip = xi;
-    xip(ip) = xip(ip) + eps;
-    solp = simulate_model_events(t,xip,k,D,options);
-    sx_fd(:,:,ip) = (solp.x - sol.x)/eps;
-    sy_fd(:,:,ip) = (solp.y - sol.y)/eps;
-    sz_fd(:,:,ip) = (solp.z - sol.z)/eps;
-<span class="keyword">end</span>
-</pre><p>PLOTTING</p><pre class="codeinput">figure
-<span class="keyword">for</span> ip = 1:4
-    subplot(4,2,ip*2-1)
-    hold <span class="string">on</span>
-    <span class="keyword">for</span> ix = 1:size(sol.x,2)
-        plot(t,sol.sx(:,ix,ip),<span class="string">'.-'</span>,<span class="string">'Color'</span>,c_x(ix,:))
-        plot(t,sx_fd(:,ix,ip),<span class="string">'d'</span>,<span class="string">'Color'</span>,c_x(ix,:))
-    <span class="keyword">end</span>
-    legend(<span class="string">'sx1'</span>,<span class="string">'sx1_{fd}'</span>,<span class="string">'sx2'</span>,<span class="string">'sx2_{fd}'</span>,<span class="string">'sx3'</span>,<span class="string">'sx3_{fd}'</span>,<span class="string">'Location'</span>,<span class="string">'NorthEastOutside'</span>)
-    legend <span class="string">boxoff</span>
-    title([<span class="string">'state sensitivity for p'</span> num2str(ip)])
-    xlabel(<span class="string">'time t'</span>)
-    ylabel(<span class="string">'sx'</span>)
-    box <span class="string">on</span>
-
-    subplot(4,2,ip*2)
-    plot(t,abs(sol.sx(:,:,ip)-sx_fd(:,:,ip)),<span class="string">'--'</span>)
-    legend(<span class="string">'error sx1'</span>,<span class="string">'error sx2'</span>,<span class="string">'error sx3'</span>,<span class="string">'Location'</span>,<span class="string">'NorthEastOutside'</span>)
-    legend <span class="string">boxoff</span>
-    title([<span class="string">'state sensitivity for p'</span> num2str(ip)])
-    xlabel(<span class="string">'time t'</span>)
-    ylabel(<span class="string">'error'</span>)
-    set(gca,<span class="string">'YScale'</span>,<span class="string">'log'</span>)
-    box <span class="string">on</span>
-<span class="keyword">end</span>
-set(gcf,<span class="string">'Position'</span>,[100 300 1200 500])
-
-figure
-<span class="keyword">for</span> ip = 1:4
-    subplot(4,2,ip*2-1)
-    hold <span class="string">on</span>
-    <span class="keyword">for</span> iy = 1:size(sol.y,2)
-        plot(t,sol.sy(:,iy,ip),<span class="string">'.-'</span>,<span class="string">'Color'</span>,c_x(iy,:))
-        plot(t,sy_fd(:,iy,ip),<span class="string">'d'</span>,<span class="string">'Color'</span>,c_x(iy,:))
-    <span class="keyword">end</span>
-    legend(<span class="string">'sy1'</span>,<span class="string">'sy1_fd'</span>,<span class="string">'Location'</span>,<span class="string">'NorthEastOutside'</span>)
-    legend <span class="string">boxoff</span>
-    title([<span class="string">'observable sensitivity for p'</span> num2str(ip)])
-    xlabel(<span class="string">'time t'</span>)
-    ylabel(<span class="string">'sy'</span>)
-    box <span class="string">on</span>
-
-    subplot(4,2,ip*2)
-    plot(t,abs(sol.sy(:,:,ip)-sy_fd(:,:,ip)),<span class="string">'--'</span>)
-    legend(<span class="string">'error sy1'</span>,<span class="string">'Location'</span>,<span class="string">'NorthEastOutside'</span>)
-    legend <span class="string">boxoff</span>
-    title([<span class="string">'error observable sensitivity for p'</span> num2str(ip)])
-    xlabel(<span class="string">'time t'</span>)
-    ylabel(<span class="string">'error'</span>)
-    set(gca,<span class="string">'YScale'</span>,<span class="string">'log'</span>)
-    box <span class="string">on</span>
-<span class="keyword">end</span>
-set(gcf,<span class="string">'Position'</span>,[100 300 1200 500])
-
-figure
-<span class="keyword">for</span> ip = 1:4
-subplot(4,2,2*ip-1)
-bar(1:options.nmaxevent,sol.sz(1:options.nmaxevent,:,ip),0.8)
-hold <span class="string">on</span>
-bar(1:options.nmaxevent,sz_fd(1:options.nmaxevent,:,ip),0.4)
-legend(<span class="string">'x3==x2'</span>,<span class="string">'x3==x1'</span>,<span class="string">'x3==x2 fd'</span>,<span class="string">'x3==x1 fd'</span>,<span class="string">'Location'</span>,<span class="string">'NorthEastOutside'</span>)
-legend <span class="string">boxoff</span>
-title([<span class="string">'event sensitivity for p'</span> num2str(ip)])
-xlabel(<span class="string">'event #'</span>)
-ylabel(<span class="string">'sz'</span>)
-box <span class="string">on</span>
-
-subplot(4,2,2*ip)
-bar(1:options.nmaxevent,sol.sz(1:options.nmaxevent,:,ip)-sz_fd(1:options.nmaxevent,:,ip),0.8)
-legend(<span class="string">'error x3==x2'</span>,<span class="string">'error x3==x1'</span>,<span class="string">'Location'</span>,<span class="string">'NorthEastOutside'</span>)
-legend <span class="string">boxoff</span>
-title([<span class="string">'error event sensitivity for p'</span> num2str(ip)])
-xlabel(<span class="string">'event #'</span>)
-ylabel(<span class="string">'sz'</span>)
-box <span class="string">on</span>
-<span class="keyword">end</span>
-set(gcf,<span class="string">'Position'</span>,[100 300 1200 500])
-
-drawnow
-</pre><img vspace="5" hspace="5" src="../examples/example_events/html/example_events_02.png" alt=""> <img vspace="5" hspace="5" src="../examples/example_events/html/example_events_03.png" alt=""> <img vspace="5" hspace="5" src="../examples/example_events/html/example_events_04.png" alt=""> <pre class="codeinput"><span class="keyword">end</span>
-</pre><p class="footer"><br><a href="http://www.mathworks.com/products/matlab/">Published with MATLAB&reg; R2016a</a><br></p></div><!--
-##### SOURCE BEGIN #####
-function example_events()
-%%
-% COMPILATION
-
-[exdir,~,~]=fileparts(which('example_events.m'));
-% compile the model
-amiwrap('model_events','model_events_syms',exdir)
-
-%%
-% SIMULATION
-
-% time vector
-t = linspace(0,10,20);
-p = [0.5;2;0.5;0.5];
-k = [4,8,10,4];
-
-options = amioption('sensi',0,...
-    'maxsteps',1e4,...
-    'nmaxevent', 2);
-D = amidata(length(t),1,2,2,4);
-% load mex into memory
-[~] = which('simulate_model_events'); % fix for inaccessability problems
-sol = simulate_model_events(t,log10(p),k,D,options);
-
-tic
-sol = simulate_model_events(t,log10(p),k,D,options);
-disp(['Time elapsed with cvodes: ' num2str(toc) ])
-
-%%
-% ODE15S
-
-ode_system = @(t,x,p,k) [-p(1)*heaviside(t-p(4))*x(1);
-    +p(2)*x(1)*exp(-0.1*t)-p(3)*x(2);
-    -1.5*x(3)];
-% event_fn = @(t,x) [x(3) - x(2);
-%     x(3) - x(1)];
-% 'Events',event_fn
-options_ode15s = odeset('RelTol',options.rtol,'AbsTol',options.atol,'MaxStep',options.maxsteps);
-
-tic
-[~, X_ode15s] = ode15s(@(t,x) ode_system(t,x,p,k),t,k(1:3),options_ode15s);
-disp(['Time elapsed with ode15s: ' num2str(toc) ])
-
-%%
-% PLOTTING
-
-figure
-c_x = get(gca,'ColorOrder');
-subplot(2,2,1)
-for ix = 1:size(sol.x,2)
-    plot(t,sol.x(:,ix),'.-','Color',c_x(ix,:))
-    hold on
-    plot(t,X_ode15s(:,ix),'d','Color',c_x(ix,:))
-end
-stem(sol.z(:,1),sol.z(:,1)*0+10,'r')
-stem(sol.z(:,2),sol.z(:,2)*0+10,'k')
-legend('x1','x1_{ode15s}','x2','x2_{ode15s}','x3','x3_{ode15s}','x3==x2','x3==x1','Location','NorthEastOutside')
-legend boxoff
-xlabel('time t')
-ylabel('x')
-box on
-subplot(2,2,2)
-plot(t,abs(sol.x-X_ode15s),'REPLACE_WITH_DASH_DASH')
-set(gca,'YScale','log')
-legend('error x1','error x2','error x3','Location','NorthEastOutside')
-legend boxoff
-ylabel('x')
-
-subplot(2,2,3)
-plot(t,sol.y,'.-','Color',c_x(1,:))
-hold on
-plot(t,p(4)*sum(X_ode15s,2),'d','Color',c_x(1,:))
-legend('y1','y1_{ode15s}','Location','NorthEastOutside')
-legend boxoff
-xlabel('time t')
-ylabel('y')
-box on
-
-subplot(2,2,4)
-plot(t,abs(sol.y-p(4)*sum(X_ode15s,2)),'REPLACE_WITH_DASH_DASH')
-set(gca,'YScale','log')
-legend('error y1','Location','NorthEastOutside')
-legend boxoff
-xlabel('time t')
-ylabel('y')
-box on
-
-set(gcf,'Position',[100 300 1200 500])
-
-
-%%
-% FORWARD SENSITIVITY ANALYSIS
-
-options.sensi = 1;
-
-sol = simulate_model_events(t,log10(p),k,D,options);
-
-%%
-% FINITE DIFFERENCES
-
-eps = 1e-4;
-xi = log10(p);
-for ip = 1:4;
-    xip = xi;
-    xip(ip) = xip(ip) + eps;
-    solp = simulate_model_events(t,xip,k,D,options);
-    sx_fd(:,:,ip) = (solp.x - sol.x)/eps;
-    sy_fd(:,:,ip) = (solp.y - sol.y)/eps;
-    sz_fd(:,:,ip) = (solp.z - sol.z)/eps;
-end
-
-%%
-% PLOTTING
-figure
-for ip = 1:4
-    subplot(4,2,ip*2-1)
-    hold on
-    for ix = 1:size(sol.x,2)
-        plot(t,sol.sx(:,ix,ip),'.-','Color',c_x(ix,:))
-        plot(t,sx_fd(:,ix,ip),'d','Color',c_x(ix,:))
-    end
-    legend('sx1','sx1_{fd}','sx2','sx2_{fd}','sx3','sx3_{fd}','Location','NorthEastOutside')
-    legend boxoff
-    title(['state sensitivity for p' num2str(ip)])
-    xlabel('time t')
-    ylabel('sx')
-    box on
-    
-    subplot(4,2,ip*2)
-    plot(t,abs(sol.sx(:,:,ip)-sx_fd(:,:,ip)),'REPLACE_WITH_DASH_DASH')
-    legend('error sx1','error sx2','error sx3','Location','NorthEastOutside')
-    legend boxoff
-    title(['state sensitivity for p' num2str(ip)])
-    xlabel('time t')
-    ylabel('error')
-    set(gca,'YScale','log')
-    box on
-end
-set(gcf,'Position',[100 300 1200 500])
-
-figure
-for ip = 1:4
-    subplot(4,2,ip*2-1)
-    hold on
-    for iy = 1:size(sol.y,2)
-        plot(t,sol.sy(:,iy,ip),'.-','Color',c_x(iy,:))
-        plot(t,sy_fd(:,iy,ip),'d','Color',c_x(iy,:))
-    end
-    legend('sy1','sy1_fd','Location','NorthEastOutside')
-    legend boxoff
-    title(['observable sensitivity for p' num2str(ip)])
-    xlabel('time t')
-    ylabel('sy')
-    box on
-    
-    subplot(4,2,ip*2)
-    plot(t,abs(sol.sy(:,:,ip)-sy_fd(:,:,ip)),'REPLACE_WITH_DASH_DASH')
-    legend('error sy1','Location','NorthEastOutside')
-    legend boxoff
-    title(['error observable sensitivity for p' num2str(ip)])
-    xlabel('time t')
-    ylabel('error')
-    set(gca,'YScale','log')
-    box on
-end
-set(gcf,'Position',[100 300 1200 500])
-
-figure
-for ip = 1:4
-subplot(4,2,2*ip-1)
-bar(1:options.nmaxevent,sol.sz(1:options.nmaxevent,:,ip),0.8)
-hold on
-bar(1:options.nmaxevent,sz_fd(1:options.nmaxevent,:,ip),0.4)
-legend('x3==x2','x3==x1','x3==x2 fd','x3==x1 fd','Location','NorthEastOutside')
-legend boxoff
-title(['event sensitivity for p' num2str(ip)])
-xlabel('event #')
-ylabel('sz')
-box on
-
-subplot(4,2,2*ip)
-bar(1:options.nmaxevent,sol.sz(1:options.nmaxevent,:,ip)-sz_fd(1:options.nmaxevent,:,ip),0.8)
-legend('error x3==x2','error x3==x1','Location','NorthEastOutside')
-legend boxoff
-title(['error event sensitivity for p' num2str(ip)])
-xlabel('event #')
-ylabel('sz')
-box on
-end
-set(gcf,'Position',[100 300 1200 500])
-
-drawnow
-end
-##### SOURCE END #####
---></body></html>
\ No newline at end of file
diff --git a/matlab/examples/example_events/html/example_events.png b/matlab/examples/example_events/html/example_events.png
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diff --git a/matlab/examples/example_events/html/example_events.tex b/matlab/examples/example_events/html/example_events.tex
deleted file mode 100644
index f827837418..0000000000
--- a/matlab/examples/example_events/html/example_events.tex
+++ /dev/null
@@ -1,251 +0,0 @@
-
-% This LaTeX was auto-generated from MATLAB code.
-% To make changes, update the MATLAB code and republish this document.
-
-
-
-
-
-
-
-
-
-
-
-    
-    \begin{DoxyCode}
-function example_events()
-\end{DoxyCode}
-\begin{par}
-COMPILATION
-\end{par} \vspace{1em}
-\begin{DoxyCode}
-[exdir,~,~]=fileparts(which('example_events.m'));
-% compile the model
-amiwrap('model_events','model_events_syms',exdir)
-\end{DoxyCode}
-
-         \begin{DoxyCode}Generating model struct ...
-Parsing model struct ...
-
-Generating C code ...
-headers | wrapfunctions | 
-Compiling mex file ...
-amici | Building with 'Xcode with Clang'.
-MEX completed successfully.
-Building with 'Xcode with Clang'.
-MEX completed successfully.
-\end{DoxyCode} 
-    \begin{par}
-SIMULATION
-\end{par} \vspace{1em}
-\begin{DoxyCode}
-% time vector
-t = linspace(0,10,20);
-p = [0.5;2;0.5;0.5];
-k = [4,8,10,4];
-
-options = amioption('sensi',0,...
-    'maxsteps',1e4,...
-    'nmaxevent', 2);
-D = amidata(length(t),1,2,2,4);
-% load mex into memory
-[~] = which('simulate_model_events'); % fix for inaccessability problems
-sol = simulate_model_events(t,log10(p),k,D,options);
-
-tic
-sol = simulate_model_events(t,log10(p),k,D,options);
-disp(['Time elapsed with cvodes: ' num2str(toc) ])
-\end{DoxyCode}
-
-         \begin{DoxyCode}Time elapsed with cvodes: 0.0037064
-\end{DoxyCode} 
-    \begin{par}
-ODE15S
-\end{par} \vspace{1em}
-\begin{DoxyCode}
-ode_system = @(t,x,p,k) [-p(1)*heaviside(t-p(4))*x(1);
-    +p(2)*x(1)*exp(-0.1*t)-p(3)*x(2);
-    -1.5*x(3)];
-% event_fn = @(t,x) [x(3) - x(2);
-%     x(3) - x(1)];
-% 'Events',event_fn
-options_ode15s = odeset('RelTol',options.rtol,'AbsTol',options.atol,'MaxStep',options.maxsteps);
-
-tic
-[~, X_ode15s] = ode15s(@(t,x) ode_system(t,x,p,k),t,k(1:3),options_ode15s);
-disp(['Time elapsed with ode15s: ' num2str(toc) ])
-\end{DoxyCode}
-
-         \begin{DoxyCode}Time elapsed with ode15s: 0.074866
-\end{DoxyCode} 
-    \begin{par}
-PLOTTING
-\end{par} \vspace{1em}
-\begin{DoxyCode}
-figure
-c_x = get(gca,'ColorOrder');
-subplot(2,2,1)
-for ix = 1:size(sol.x,2)
-    plot(t,sol.x(:,ix),'.-','Color',c_x(ix,:))
-    hold on
-    plot(t,X_ode15s(:,ix),'d','Color',c_x(ix,:))
-end
-stem(sol.z(:,1),sol.z(:,1)*0+10,'r')
-stem(sol.z(:,2),sol.z(:,2)*0+10,'k')
-legend('x1','x1_{ode15s}','x2','x2_{ode15s}','x3','x3_{ode15s}','x3==x2','x3==x1','Location','NorthEastOutside')
-legend boxoff
-xlabel('time t')
-ylabel('x')
-box on
-subplot(2,2,2)
-plot(t,abs(sol.x-X_ode15s),'--')
-set(gca,'YScale','log')
-legend('error x1','error x2','error x3','Location','NorthEastOutside')
-legend boxoff
-ylabel('x')
-
-subplot(2,2,3)
-plot(t,sol.y,'.-','Color',c_x(1,:))
-hold on
-plot(t,p(4)*sum(X_ode15s,2),'d','Color',c_x(1,:))
-legend('y1','y1_{ode15s}','Location','NorthEastOutside')
-legend boxoff
-xlabel('time t')
-ylabel('y')
-box on
-
-subplot(2,2,4)
-plot(t,abs(sol.y-p(4)*sum(X_ode15s,2)),'--')
-set(gca,'YScale','log')
-legend('error y1','Location','NorthEastOutside')
-legend boxoff
-xlabel('time t')
-ylabel('y')
-box on
-
-set(gcf,'Position',[100 300 1200 500])
-\end{DoxyCode}
-
-\includegraphics[width=\textwidth]{../../examples/example_events/html/example_events_01.png}
-\begin{par}
-FORWARD SENSITIVITY ANALYSIS
-\end{par} \vspace{1em}
-\begin{DoxyCode}
-options.sensi = 1;
-
-sol = simulate_model_events(t,log10(p),k,D,options);
-\end{DoxyCode}
-\begin{par}
-FINITE DIFFERENCES
-\end{par} \vspace{1em}
-\begin{DoxyCode}
-eps = 1e-4;
-xi = log10(p);
-for ip = 1:4;
-    xip = xi;
-    xip(ip) = xip(ip) + eps;
-    solp = simulate_model_events(t,xip,k,D,options);
-    sx_fd(:,:,ip) = (solp.x - sol.x)/eps;
-    sy_fd(:,:,ip) = (solp.y - sol.y)/eps;
-    sz_fd(:,:,ip) = (solp.z - sol.z)/eps;
-end
-\end{DoxyCode}
-\begin{par}
-PLOTTING
-\end{par} \vspace{1em}
-\begin{DoxyCode}
-figure
-for ip = 1:4
-    subplot(4,2,ip*2-1)
-    hold on
-    for ix = 1:size(sol.x,2)
-        plot(t,sol.sx(:,ix,ip),'.-','Color',c_x(ix,:))
-        plot(t,sx_fd(:,ix,ip),'d','Color',c_x(ix,:))
-    end
-    legend('sx1','sx1_{fd}','sx2','sx2_{fd}','sx3','sx3_{fd}','Location','NorthEastOutside')
-    legend boxoff
-    title(['state sensitivity for p' num2str(ip)])
-    xlabel('time t')
-    ylabel('sx')
-    box on
-
-    subplot(4,2,ip*2)
-    plot(t,abs(sol.sx(:,:,ip)-sx_fd(:,:,ip)),'--')
-    legend('error sx1','error sx2','error sx3','Location','NorthEastOutside')
-    legend boxoff
-    title(['state sensitivity for p' num2str(ip)])
-    xlabel('time t')
-    ylabel('error')
-    set(gca,'YScale','log')
-    box on
-end
-set(gcf,'Position',[100 300 1200 500])
-
-figure
-for ip = 1:4
-    subplot(4,2,ip*2-1)
-    hold on
-    for iy = 1:size(sol.y,2)
-        plot(t,sol.sy(:,iy,ip),'.-','Color',c_x(iy,:))
-        plot(t,sy_fd(:,iy,ip),'d','Color',c_x(iy,:))
-    end
-    legend('sy1','sy1_fd','Location','NorthEastOutside')
-    legend boxoff
-    title(['observable sensitivity for p' num2str(ip)])
-    xlabel('time t')
-    ylabel('sy')
-    box on
-
-    subplot(4,2,ip*2)
-    plot(t,abs(sol.sy(:,:,ip)-sy_fd(:,:,ip)),'--')
-    legend('error sy1','Location','NorthEastOutside')
-    legend boxoff
-    title(['error observable sensitivity for p' num2str(ip)])
-    xlabel('time t')
-    ylabel('error')
-    set(gca,'YScale','log')
-    box on
-end
-set(gcf,'Position',[100 300 1200 500])
-
-figure
-for ip = 1:4
-subplot(4,2,2*ip-1)
-bar(1:options.nmaxevent,sol.sz(1:options.nmaxevent,:,ip),0.8)
-hold on
-bar(1:options.nmaxevent,sz_fd(1:options.nmaxevent,:,ip),0.4)
-legend('x3==x2','x3==x1','x3==x2 fd','x3==x1 fd','Location','NorthEastOutside')
-legend boxoff
-title(['event sensitivity for p' num2str(ip)])
-xlabel('event #')
-ylabel('sz')
-box on
-
-subplot(4,2,2*ip)
-bar(1:options.nmaxevent,sol.sz(1:options.nmaxevent,:,ip)-sz_fd(1:options.nmaxevent,:,ip),0.8)
-legend('error x3==x2','error x3==x1','Location','NorthEastOutside')
-legend boxoff
-title(['error event sensitivity for p' num2str(ip)])
-xlabel('event #')
-ylabel('sz')
-box on
-end
-set(gcf,'Position',[100 300 1200 500])
-
-drawnow
-\end{DoxyCode}
-
-\includegraphics[width=\textwidth]{../../examples/example_events/html/example_events_02.png}
-
-\includegraphics[width=\textwidth]{../../examples/example_events/html/example_events_03.png}
-
-\includegraphics[width=\textwidth]{../../examples/example_events/html/example_events_04.png}
-\begin{DoxyCode}
-end
-\end{DoxyCode}
-
-
-
-
-    
\ No newline at end of file
diff --git a/matlab/examples/example_events/html/example_events_01.png b/matlab/examples/example_events/html/example_events_01.png
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-
-  </style></head><body><div class="content"><pre class="codeinput"><span class="keyword">function</span> [model] = model_events_syms()
-</pre><pre class="codeinput"><span class="comment">% set the parametrisation of the problem options are 'log', 'log10' and</span>
-<span class="comment">% 'lin' (default).</span>
-model.param = <span class="string">'log10'</span>;
-</pre><p>STATES</p><pre class="codeinput"><span class="comment">% create state syms</span>
-syms <span class="string">x1</span> <span class="string">x2</span> <span class="string">x3</span>
-
-<span class="comment">% create state vector</span>
-model.sym.x = [
-x1 x2 x3
-];
-</pre><p>PARAMETERS ( for these sensitivities will be computed )</p><pre class="codeinput"><span class="comment">% create parameter syms</span>
-syms <span class="string">p1</span> <span class="string">p2</span> <span class="string">p3</span> <span class="string">p4</span>
-
-<span class="comment">% create parameter vector</span>
-model.sym.p = [p1,p2,p3,p4];
-
-<span class="comment">% set the parametrisation of the problem options are 'log', 'log10' and</span>
-<span class="comment">% 'lin' (default).</span>
-model.param = <span class="string">'log10'</span>;
-</pre><p>CONSTANTS ( for these no sensitivities will be computed ) this part is optional and can be ommited</p><pre class="codeinput"><span class="comment">% create parameter syms</span>
-syms <span class="string">k1</span> <span class="string">k2</span> <span class="string">k3</span> <span class="string">k4</span>
-
-<span class="comment">% create parameter vector</span>
-model.sym.k = [k1 k2 k3 k4];
-</pre><p>SYSTEM EQUATIONS</p><pre class="codeinput"><span class="comment">% create symbolic variable for time</span>
-syms <span class="string">t</span>
-
-model.sym.xdot = sym(zeros(size(model.sym.x)));
-
-<span class="comment">% piecewise defined function</span>
-model.sym.xdot(1) = -p1*heaviside(t-p4)*x1;
-<span class="comment">% inhomogeneous</span>
-model.sym.xdot(2) = +p2*x1*exp(-0.1*t)-p3*x2 ;
-model.sym.xdot(3) = -1.5*x3;
-</pre><p>INITIAL CONDITIONS</p><pre class="codeinput">model.sym.x0 = sym(zeros(size(model.sym.x)));
-
-model.sym.x0(1) = k1;
-model.sym.x0(2) = k2;
-model.sym.x0(3) = k3;
-</pre><p>OBSERVALES</p><pre class="codeinput">model.sym.y = sym(zeros(1,1));
-
-model.sym.y(1) = p4 * (x1+x2+x3);
-</pre><p>EVENTS this part is optional and can be ommited</p><pre class="codeinput">syms <span class="string">t</span>
-
-<span class="comment">% events fire when there is a zero crossing of the root function</span>
-model.event(1) = amievent(x3-x2,0,t);
-model.event(2) = amievent(x3-x1,0,t);
-</pre><pre class="codeinput"><span class="keyword">end</span>
-</pre><pre class="codeoutput">ans = 
-    param: 'log10'
-      sym: [1x1 struct]
-    event: [1x2 amievent]
-</pre><p class="footer"><br><a href="http://www.mathworks.com/products/matlab/">Published with MATLAB&reg; R2016a</a><br></p></div><!--
-##### SOURCE BEGIN #####
-function [model] = model_events_syms()
-
-% set the parametrisation of the problem options are 'log', 'log10' and
-% 'lin' (default).
-model.param = 'log10';
-
-%%
-% STATES
-
-
-% create state syms
-syms x1 x2 x3
-
-% create state vector
-model.sym.x = [
-x1 x2 x3
-];
-
-%%
-% PARAMETERS ( for these sensitivities will be computed )
-
-% create parameter syms
-syms p1 p2 p3 p4
-
-% create parameter vector 
-model.sym.p = [p1,p2,p3,p4];
-
-% set the parametrisation of the problem options are 'log', 'log10' and
-% 'lin' (default).
-model.param = 'log10'; 
-
-%%
-% CONSTANTS ( for these no sensitivities will be computed )
-% this part is optional and can be ommited
-
-% create parameter syms
-syms k1 k2 k3 k4
-
-% create parameter vector 
-model.sym.k = [k1 k2 k3 k4];
-
-%%
-% SYSTEM EQUATIONS
-
-% create symbolic variable for time
-syms t
-
-model.sym.xdot = sym(zeros(size(model.sym.x)));
-
-% piecewise defined function
-model.sym.xdot(1) = -p1*heaviside(t-p4)*x1;
-% inhomogeneous
-model.sym.xdot(2) = +p2*x1*exp(-0.1*t)-p3*x2 ;
-model.sym.xdot(3) = -1.5*x3;
-
-%%
-% INITIAL CONDITIONS
-
-model.sym.x0 = sym(zeros(size(model.sym.x)));
-
-model.sym.x0(1) = k1;
-model.sym.x0(2) = k2;
-model.sym.x0(3) = k3;
-
-%%
-% OBSERVALES
-
-model.sym.y = sym(zeros(1,1));
-
-model.sym.y(1) = p4 * (x1+x2+x3);
-
-
-%%
-% EVENTS
-% this part is optional and can be ommited
-syms t
-
-% events fire when there is a zero crossing of the root function
-model.event(1) = amievent(x3-x2,0,t);
-model.event(2) = amievent(x3-x1,0,t);
-
-end
-##### SOURCE END #####
---></body></html>
\ No newline at end of file
diff --git a/matlab/examples/example_events/html/model_events_syms.tex b/matlab/examples/example_events/html/model_events_syms.tex
deleted file mode 100644
index 4cfaa06d19..0000000000
--- a/matlab/examples/example_events/html/model_events_syms.tex
+++ /dev/null
@@ -1,116 +0,0 @@
-
-% This LaTeX was auto-generated from MATLAB code.
-% To make changes, update the MATLAB code and republish this document.
-
-
-
-
-
-
-
-
-
-
-
-    
-    \begin{DoxyCode}
-function [model] = model_events_syms()
-\end{DoxyCode}
-\begin{DoxyCode}
-% set the parametrisation of the problem options are 'log', 'log10' and
-% 'lin' (default).
-model.param = 'log10';
-\end{DoxyCode}
-\begin{par}
-STATES
-\end{par} \vspace{1em}
-\begin{DoxyCode}
-% create state syms
-syms x1 x2 x3
-
-% create state vector
-model.sym.x = [
-x1 x2 x3
-];
-\end{DoxyCode}
-\begin{par}
-PARAMETERS ( for these sensitivities will be computed )
-\end{par} \vspace{1em}
-\begin{DoxyCode}
-% create parameter syms
-syms p1 p2 p3 p4
-
-% create parameter vector
-model.sym.p = [p1,p2,p3,p4];
-
-% set the parametrisation of the problem options are 'log', 'log10' and
-% 'lin' (default).
-model.param = 'log10';
-\end{DoxyCode}
-\begin{par}
-CONSTANTS ( for these no sensitivities will be computed ) this part is optional and can be ommited
-\end{par} \vspace{1em}
-\begin{DoxyCode}
-% create parameter syms
-syms k1 k2 k3 k4
-
-% create parameter vector
-model.sym.k = [k1 k2 k3 k4];
-\end{DoxyCode}
-\begin{par}
-SYSTEM EQUATIONS
-\end{par} \vspace{1em}
-\begin{DoxyCode}
-% create symbolic variable for time
-syms t
-
-model.sym.xdot = sym(zeros(size(model.sym.x)));
-
-% piecewise defined function
-model.sym.xdot(1) = -p1*heaviside(t-p4)*x1;
-% inhomogeneous
-model.sym.xdot(2) = +p2*x1*exp(-0.1*t)-p3*x2 ;
-model.sym.xdot(3) = -1.5*x3;
-\end{DoxyCode}
-\begin{par}
-INITIAL CONDITIONS
-\end{par} \vspace{1em}
-\begin{DoxyCode}
-model.sym.x0 = sym(zeros(size(model.sym.x)));
-
-model.sym.x0(1) = k1;
-model.sym.x0(2) = k2;
-model.sym.x0(3) = k3;
-\end{DoxyCode}
-\begin{par}
-OBSERVALES
-\end{par} \vspace{1em}
-\begin{DoxyCode}
-model.sym.y = sym(zeros(1,1));
-
-model.sym.y(1) = p4 * (x1+x2+x3);
-\end{DoxyCode}
-\begin{par}
-EVENTS this part is optional and can be ommited
-\end{par} \vspace{1em}
-\begin{DoxyCode}
-syms t
-
-% events fire when there is a zero crossing of the root function
-model.event(1) = amievent(x3-x2,0,t);
-model.event(2) = amievent(x3-x1,0,t);
-\end{DoxyCode}
-\begin{DoxyCode}
-end
-\end{DoxyCode}
-
-         \begin{DoxyCode}ans = 
-    param: 'log10'
-      sym: [1x1 struct]
-    event: [1x2 amievent]
-\end{DoxyCode} 
-    
-
-
-
-    
\ No newline at end of file
diff --git a/matlab/examples/example_jakstat_adjoint/html/example_jakstat_adjoint.html b/matlab/examples/example_jakstat_adjoint/html/example_jakstat_adjoint.html
deleted file mode 100644
index 711bc3bfe1..0000000000
--- a/matlab/examples/example_jakstat_adjoint/html/example_jakstat_adjoint.html
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-
-.footer { width:auto; padding:10px 0px; margin:25px 0px 0px; border-top:1px dotted #878787; font-size:0.8em; line-height:140%; font-style:italic; color:#878787; text-align:left; float:none; }
-.footer p { margin:0px; }
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-table td { padding:7px 5px; text-align:left; vertical-align:top; border:1px solid #d6d4d4; }
-
-
-
-
-
-  </style></head><body><div class="content"><pre class="codeinput"><span class="keyword">function</span> example_jakstat_adjoint()
-
-    <span class="comment">% compile the model</span>
-    [exdir,~,~]=fileparts(which(<span class="string">'example_jakstat_adjoint.m'</span>));
-    amiwrap(<span class="string">'model_jakstat'</span>,<span class="string">'model_jakstat_adjoint_syms'</span>,exdir)
-
-    num = xlsread(fullfile(exdir,<span class="string">'pnas_data_original.xls'</span>));
-
-    D.t = num(:,1);
-    D.condition= [1.4,0.45];
-    D.Y = num(:,[2,4,6]);
-    D.Sigma_Y = NaN(size(D.Y));
-    D = amidata(D);
-
-    xi =  [0.60
-        3
-        -0.95
-        -0.0075
-        0
-        -2.8
-        -0.26
-        -0.075
-        -0.41
-        -5
-        -0.74
-        -0.64
-        -0.11
-        0.027
-        -0.5
-        0
-        -0.5];
-
-    options.sensi = 0;
-    sol = simulate_model_jakstat([],xi,[],D,options);
-
-    figure
-    <span class="keyword">for</span> iy = 1:3
-        subplot(2,2,iy)
-        plot(D.t,D.Y(:,iy),<span class="string">'rx'</span>)
-        hold <span class="string">on</span>
-        plot(sol.t,sol.y(:,iy),<span class="string">'.-'</span>)
-        xlim([0,60])
-        xlabel(<span class="string">'t'</span>)
-        <span class="keyword">switch</span>(iy)
-            <span class="keyword">case</span> 1
-                ylabel(<span class="string">'pStat'</span>)
-            <span class="keyword">case</span> 2
-                ylabel(<span class="string">'tStat'</span>)
-            <span class="keyword">case</span> 3
-                ylabel(<span class="string">'pEpoR'</span>)
-        <span class="keyword">end</span>
-        ylim([0,1.2])
-    <span class="keyword">end</span>
-    set(gcf,<span class="string">'Position'</span>,[100 300 1200 500])
-
-    <span class="comment">% generate new</span>
-    xi_rand = xi + 0.1;
-    options.sensi = 1;
-    options.sensi_meth = <span class="string">'adjoint'</span>;
-    sol = simulate_model_jakstat([],xi_rand,[],D,options);
-
-    options.sensi = 0;
-    eps = 1e-4;
-    fd_grad = NaN(length(xi),1);
-    <span class="keyword">for</span> ip = 1:length(xi)
-        xip = xi_rand;
-        xip(ip) = xip(ip) + eps;
-        psol = simulate_model_jakstat([],xip,[],D,options);
-        fd_grad(ip) = (psol.llh-sol.llh)/eps;
-    <span class="keyword">end</span>
-
-    figure
-    scatter(abs(sol.sllh),abs(fd_grad))
-    set(gca,<span class="string">'XScale'</span>,<span class="string">'log'</span>)
-    set(gca,<span class="string">'YScale'</span>,<span class="string">'log'</span>)
-    xlim([1e-2,1e2])
-    ylim([1e-2,1e2])
-    box <span class="string">on</span>
-    hold <span class="string">on</span>
-    axis <span class="string">square</span>
-    plot([1e-2,1e2],[1e-2,1e2],<span class="string">'k:'</span>)
-    xlabel(<span class="string">'adjoint sensitivity absolute value of gradient element'</span>)
-    ylabel(<span class="string">'finite difference absolute value of gradient element'</span>)
-    set(gcf,<span class="string">'Position'</span>,[100 300 1200 500])
-
-
-    drawnow
-
-<span class="keyword">end</span>
-</pre><pre class="codeoutput">Generating model struct ...
-Parsing model struct ...
-Generating C code ...
-headers | wrapfunctions | Compiling mex file ...
-amici | Building with 'Xcode with Clang'.
-MEX completed successfully.
-Building with 'Xcode with Clang'.
-MEX completed successfully.
-</pre><img vspace="5" hspace="5" src="../examples/example_jakstat_adjoint/html/example_jakstat_adjoint_01.png" alt=""> <img vspace="5" hspace="5" src="../examples/example_jakstat_adjoint/html/example_jakstat_adjoint_02.png" alt=""> <p class="footer"><br><a href="http://www.mathworks.com/products/matlab/">Published with MATLAB&reg; R2016a</a><br></p></div><!--
-##### SOURCE BEGIN #####
-function example_jakstat_adjoint()
-    
-    % compile the model
-    [exdir,~,~]=fileparts(which('example_jakstat_adjoint.m'));
-    amiwrap('model_jakstat','model_jakstat_adjoint_syms',exdir)
-    
-    num = xlsread(fullfile(exdir,'pnas_data_original.xls'));
-    
-    D.t = num(:,1);
-    D.condition= [1.4,0.45];
-    D.Y = num(:,[2,4,6]);
-    D.Sigma_Y = NaN(size(D.Y));
-    D = amidata(D);
-    
-    xi =  [0.60
-        3
-        -0.95
-        -0.0075
-        0
-        -2.8
-        -0.26
-        -0.075
-        -0.41
-        -5
-        -0.74
-        -0.64
-        -0.11
-        0.027
-        -0.5
-        0
-        -0.5];
-    
-    options.sensi = 0;
-    sol = simulate_model_jakstat([],xi,[],D,options);
-    
-    figure
-    for iy = 1:3
-        subplot(2,2,iy)
-        plot(D.t,D.Y(:,iy),'rx')
-        hold on
-        plot(sol.t,sol.y(:,iy),'.-')
-        xlim([0,60])
-        xlabel('t')
-        switch(iy)
-            case 1
-                ylabel('pStat')
-            case 2
-                ylabel('tStat')
-            case 3
-                ylabel('pEpoR')
-        end
-        ylim([0,1.2])
-    end
-    set(gcf,'Position',[100 300 1200 500])
-    
-    % generate new
-    xi_rand = xi + 0.1;
-    options.sensi = 1;
-    options.sensi_meth = 'adjoint';
-    sol = simulate_model_jakstat([],xi_rand,[],D,options);
-    
-    options.sensi = 0;
-    eps = 1e-4;
-    fd_grad = NaN(length(xi),1);
-    for ip = 1:length(xi)
-        xip = xi_rand;
-        xip(ip) = xip(ip) + eps;
-        psol = simulate_model_jakstat([],xip,[],D,options);
-        fd_grad(ip) = (psol.llh-sol.llh)/eps;
-    end
-    
-    figure
-    scatter(abs(sol.sllh),abs(fd_grad))
-    set(gca,'XScale','log')
-    set(gca,'YScale','log')
-    xlim([1e-2,1e2])
-    ylim([1e-2,1e2])
-    box on
-    hold on
-    axis square
-    plot([1e-2,1e2],[1e-2,1e2],'k:')
-    xlabel('adjoint sensitivity absolute value of gradient element')
-    ylabel('finite difference absolute value of gradient element')
-    set(gcf,'Position',[100 300 1200 500])
-    
-    
-    drawnow
-    
-end
-
-##### SOURCE END #####
---></body></html>
\ No newline at end of file
diff --git a/matlab/examples/example_jakstat_adjoint/html/example_jakstat_adjoint.png b/matlab/examples/example_jakstat_adjoint/html/example_jakstat_adjoint.png
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diff --git a/matlab/examples/example_jakstat_adjoint/html/example_jakstat_adjoint.tex b/matlab/examples/example_jakstat_adjoint/html/example_jakstat_adjoint.tex
deleted file mode 100644
index 44e9688a17..0000000000
--- a/matlab/examples/example_jakstat_adjoint/html/example_jakstat_adjoint.tex
+++ /dev/null
@@ -1,127 +0,0 @@
-
-% This LaTeX was auto-generated from MATLAB code.
-% To make changes, update the MATLAB code and republish this document.
-
-
-
-
-
-
-
-
-
-
-
-    
-    \begin{DoxyCode}
-function example_jakstat_adjoint()
-
-    % compile the model
-    [exdir,~,~]=fileparts(which('example_jakstat_adjoint.m'));
-    amiwrap('model_jakstat','model_jakstat_adjoint_syms',exdir)
-
-    num = xlsread(fullfile(exdir,'pnas_data_original.xls'));
-
-    D.t = num(:,1);
-    D.condition= [1.4,0.45];
-    D.Y = num(:,[2,4,6]);
-    D.Sigma_Y = NaN(size(D.Y));
-    D = amidata(D);
-
-    xi =  [0.60
-        3
-        -0.95
-        -0.0075
-        0
-        -2.8
-        -0.26
-        -0.075
-        -0.41
-        -5
-        -0.74
-        -0.64
-        -0.11
-        0.027
-        -0.5
-        0
-        -0.5];
-
-    options.sensi = 0;
-    sol = simulate_model_jakstat([],xi,[],D,options);
-
-    figure
-    for iy = 1:3
-        subplot(2,2,iy)
-        plot(D.t,D.Y(:,iy),'rx')
-        hold on
-        plot(sol.t,sol.y(:,iy),'.-')
-        xlim([0,60])
-        xlabel('t')
-        switch(iy)
-            case 1
-                ylabel('pStat')
-            case 2
-                ylabel('tStat')
-            case 3
-                ylabel('pEpoR')
-        end
-        ylim([0,1.2])
-    end
-    set(gcf,'Position',[100 300 1200 500])
-
-    % generate new
-    xi_rand = xi + 0.1;
-    options.sensi = 1;
-    options.sensi_meth = 'adjoint';
-    sol = simulate_model_jakstat([],xi_rand,[],D,options);
-
-    options.sensi = 0;
-    eps = 1e-4;
-    fd_grad = NaN(length(xi),1);
-    for ip = 1:length(xi)
-        xip = xi_rand;
-        xip(ip) = xip(ip) + eps;
-        psol = simulate_model_jakstat([],xip,[],D,options);
-        fd_grad(ip) = (psol.llh-sol.llh)/eps;
-    end
-
-    figure
-    scatter(abs(sol.sllh),abs(fd_grad))
-    set(gca,'XScale','log')
-    set(gca,'YScale','log')
-    xlim([1e-2,1e2])
-    ylim([1e-2,1e2])
-    box on
-    hold on
-    axis square
-    plot([1e-2,1e2],[1e-2,1e2],'k:')
-    xlabel('adjoint sensitivity absolute value of gradient element')
-    ylabel('finite difference absolute value of gradient element')
-    set(gcf,'Position',[100 300 1200 500])
-
-
-    drawnow
-
-end
-\end{DoxyCode}
-
-         \begin{DoxyCode}Generating model struct ...
-Parsing model struct ...
-
-Generating C code ...
-headers | wrapfunctions | 
-Compiling mex file ...
-amici | Building with 'Xcode with Clang'.
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-Building with 'Xcode with Clang'.
-MEX completed successfully.
-\end{DoxyCode} 
-    
-\includegraphics[width=\textwidth]{../../examples/example_jakstat_adjoint/html/example_jakstat_adjoint_01.png}
-
-\includegraphics[width=\textwidth]{../../examples/example_jakstat_adjoint/html/example_jakstat_adjoint_02.png}
-
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\ No newline at end of file
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-      --><title>model_jakstat_adjoint_syms</title><meta name="generator" content="MATLAB 9.0"><link rel="schema.DC" href="http://purl.org/dc/elements/1.1/"><meta name="DC.date" content="2016-05-04"><meta name="DC.source" content="model_jakstat_adjoint_syms.m"><style type="text/css">
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-
-  </style></head><body><div class="content"><pre class="codeinput"><span class="keyword">function</span> [model] = model_jakstat_syms()
-</pre><p>STATES</p><pre class="codeinput">    syms <span class="string">STAT</span> <span class="string">pSTAT</span> <span class="string">pSTAT_pSTAT</span> <span class="string">npSTAT_npSTAT</span> <span class="string">nSTAT1</span> <span class="string">nSTAT2</span> <span class="string">nSTAT3</span> <span class="string">nSTAT4</span> <span class="string">nSTAT5</span>
-
-    model.sym.x = [
-        STAT, pSTAT, pSTAT_pSTAT, npSTAT_npSTAT, nSTAT1, nSTAT2, nSTAT3, nSTAT4, nSTAT5 <span class="keyword">...</span>
-        ];
-</pre><p>PARAMETERS</p><pre class="codeinput">    syms <span class="string">p1</span> <span class="string">p2</span> <span class="string">p3</span> <span class="string">p4</span> <span class="string">init_STAT</span> <span class="string">Omega_cyt</span> <span class="string">Omega_nuc</span> <span class="string">sp1</span> <span class="string">sp2</span> <span class="string">sp3</span> <span class="string">sp4</span> <span class="string">sp5</span> <span class="string">offset_tSTAT</span> <span class="string">offset_pSTAT</span> <span class="string">scale_tSTAT</span> <span class="string">scale_pSTAT</span> <span class="string">sigma_pSTAT</span> <span class="string">sigma_tSTAT</span> <span class="string">sigma_pEpoR</span>
-
-    model.sym.p = [p1,p2,p3,p4,init_STAT,sp1,sp2,sp3,sp4,sp5,offset_tSTAT,offset_pSTAT,scale_tSTAT,scale_pSTAT,sigma_pSTAT,sigma_tSTAT,sigma_pEpoR];
-
-    model.param = <span class="string">'log10'</span>;
-
-    model.sym.k = [Omega_cyt,Omega_nuc];
-</pre><p>INPUT</p><pre class="codeinput">    syms <span class="string">t</span>
-    u(1) = spline_pos5(t, 0.0, sp1, 5.0, sp2, 10.0, sp3, 20.0, sp4, 60.0, sp5, 0, 0.0);
-</pre><pre class="codeoutput">Warning: Support of strings that are not valid variable names or define a number
-will be removed in a future release. To create symbolic expressions, first
-create symbolic variables and then use operations on them. 
-</pre><p>SYSTEM EQUATIONS</p><pre class="codeinput">    model.sym.xdot = sym(zeros(size(model.sym.x)));
-
-    model.sym.xdot(1) = (Omega_nuc*p4*nSTAT5 - Omega_cyt*STAT*p1*u(1))/Omega_cyt;
-    model.sym.xdot(2) = STAT*p1*u(1) - 2*p2*pSTAT^2;
-    model.sym.xdot(3) = p2*pSTAT^2 - p3*pSTAT_pSTAT;
-    model.sym.xdot(4) = -(Omega_nuc*p4*npSTAT_npSTAT - Omega_cyt*p3*pSTAT_pSTAT)/Omega_nuc;
-    model.sym.xdot(5) = -p4*(nSTAT1 - 2*npSTAT_npSTAT);
-    model.sym.xdot(6) = p4*(nSTAT1 - nSTAT2);
-    model.sym.xdot(7) = p4*(nSTAT2 - nSTAT3);
-    model.sym.xdot(8) = p4*(nSTAT3 - nSTAT4);
-    model.sym.xdot(9) = p4*(nSTAT4 - nSTAT5);
-</pre><p>INITIAL CONDITIONS</p><pre class="codeinput">    model.sym.x0 = sym(zeros(size(model.sym.x)));
-
-    model.sym.x0(1) = init_STAT;
-</pre><p>OBSERVABLES</p><pre class="codeinput">    model.sym.y = sym(zeros(3,1));
-
-    model.sym.y(1) = offset_pSTAT + scale_pSTAT/init_STAT*(pSTAT + 2*pSTAT_pSTAT);
-    model.sym.y(2) = offset_tSTAT + scale_tSTAT/init_STAT*(STAT + pSTAT + 2*(pSTAT_pSTAT));
-    model.sym.y(3) = u(1);
-</pre><p>SIGMA</p><pre class="codeinput">    model.sym.sigma_y = sym(size(model.sym.y));
-
-    model.sym.sigma_y(1) = sigma_pSTAT;
-    model.sym.sigma_y(2) = sigma_tSTAT;
-    model.sym.sigma_y(3) = sigma_pEpoR;
-</pre><pre class="codeinput"><span class="keyword">end</span>
-</pre><pre class="codeoutput">ans = 
-      sym: [1x1 struct]
-    param: 'log10'
-</pre><p class="footer"><br><a href="http://www.mathworks.com/products/matlab/">Published with MATLAB&reg; R2016a</a><br></p></div><!--
-##### SOURCE BEGIN #####
-function [model] = model_jakstat_syms()
-    
-    %%
-    % STATES
-    
-    syms STAT pSTAT pSTAT_pSTAT npSTAT_npSTAT nSTAT1 nSTAT2 nSTAT3 nSTAT4 nSTAT5
-    
-    model.sym.x = [
-        STAT, pSTAT, pSTAT_pSTAT, npSTAT_npSTAT, nSTAT1, nSTAT2, nSTAT3, nSTAT4, nSTAT5 ...
-        ];
-    
-    %%
-    % PARAMETERS
-    
-    syms p1 p2 p3 p4 init_STAT Omega_cyt Omega_nuc sp1 sp2 sp3 sp4 sp5 offset_tSTAT offset_pSTAT scale_tSTAT scale_pSTAT sigma_pSTAT sigma_tSTAT sigma_pEpoR
-    
-    model.sym.p = [p1,p2,p3,p4,init_STAT,sp1,sp2,sp3,sp4,sp5,offset_tSTAT,offset_pSTAT,scale_tSTAT,scale_pSTAT,sigma_pSTAT,sigma_tSTAT,sigma_pEpoR];
-    
-    model.param = 'log10';
-    
-    model.sym.k = [Omega_cyt,Omega_nuc];
-    
-    %%
-    % INPUT
-    syms t
-    u(1) = spline_pos5(t, 0.0, sp1, 5.0, sp2, 10.0, sp3, 20.0, sp4, 60.0, sp5, 0, 0.0);
-    
-    %%
-    % SYSTEM EQUATIONS
-    
-    model.sym.xdot = sym(zeros(size(model.sym.x)));
-    
-    model.sym.xdot(1) = (Omega_nuc*p4*nSTAT5 - Omega_cyt*STAT*p1*u(1))/Omega_cyt;
-    model.sym.xdot(2) = STAT*p1*u(1) - 2*p2*pSTAT^2;
-    model.sym.xdot(3) = p2*pSTAT^2 - p3*pSTAT_pSTAT;
-    model.sym.xdot(4) = -(Omega_nuc*p4*npSTAT_npSTAT - Omega_cyt*p3*pSTAT_pSTAT)/Omega_nuc;
-    model.sym.xdot(5) = -p4*(nSTAT1 - 2*npSTAT_npSTAT);
-    model.sym.xdot(6) = p4*(nSTAT1 - nSTAT2);
-    model.sym.xdot(7) = p4*(nSTAT2 - nSTAT3);
-    model.sym.xdot(8) = p4*(nSTAT3 - nSTAT4);
-    model.sym.xdot(9) = p4*(nSTAT4 - nSTAT5);
-    
-    %%
-    % INITIAL CONDITIONS
-    
-    model.sym.x0 = sym(zeros(size(model.sym.x)));
-    
-    model.sym.x0(1) = init_STAT;
-    
-    %%
-    % OBSERVABLES
-    
-    model.sym.y = sym(zeros(3,1));
-    
-    model.sym.y(1) = offset_pSTAT + scale_pSTAT/init_STAT*(pSTAT + 2*pSTAT_pSTAT);
-    model.sym.y(2) = offset_tSTAT + scale_tSTAT/init_STAT*(STAT + pSTAT + 2*(pSTAT_pSTAT));
-    model.sym.y(3) = u(1);
-    
-    %%
-    % SIGMA
-    
-    model.sym.sigma_y = sym(size(model.sym.y));
-    
-    model.sym.sigma_y(1) = sigma_pSTAT;
-    model.sym.sigma_y(2) = sigma_tSTAT;
-    model.sym.sigma_y(3) = sigma_pEpoR;
-    
-end
-##### SOURCE END #####
---></body></html>
\ No newline at end of file
diff --git a/matlab/examples/example_jakstat_adjoint/html/model_jakstat_adjoint_syms.tex b/matlab/examples/example_jakstat_adjoint/html/model_jakstat_adjoint_syms.tex
deleted file mode 100644
index 67b5416988..0000000000
--- a/matlab/examples/example_jakstat_adjoint/html/model_jakstat_adjoint_syms.tex
+++ /dev/null
@@ -1,109 +0,0 @@
-
-% This LaTeX was auto-generated from MATLAB code.
-% To make changes, update the MATLAB code and republish this document.
-
-
-
-
-
-
-
-
-
-
-
-    
-    \begin{DoxyCode}
-function [model] = model_jakstat_syms()
-\end{DoxyCode}
-\begin{par}
-STATES
-\end{par} \vspace{1em}
-\begin{DoxyCode}
-    syms STAT pSTAT pSTAT_pSTAT npSTAT_npSTAT nSTAT1 nSTAT2 nSTAT3 nSTAT4 nSTAT5
-
-    model.sym.x = [
-        STAT, pSTAT, pSTAT_pSTAT, npSTAT_npSTAT, nSTAT1, nSTAT2, nSTAT3, nSTAT4, nSTAT5 ...
-        ];
-\end{DoxyCode}
-\begin{par}
-PARAMETERS
-\end{par} \vspace{1em}
-\begin{DoxyCode}
-    syms p1 p2 p3 p4 init_STAT Omega_cyt Omega_nuc sp1 sp2 sp3 sp4 sp5 offset_tSTAT offset_pSTAT scale_tSTAT scale_pSTAT sigma_pSTAT sigma_tSTAT sigma_pEpoR
-
-    model.sym.p = [p1,p2,p3,p4,init_STAT,sp1,sp2,sp3,sp4,sp5,offset_tSTAT,offset_pSTAT,scale_tSTAT,scale_pSTAT,sigma_pSTAT,sigma_tSTAT,sigma_pEpoR];
-
-    model.param = 'log10';
-
-    model.sym.k = [Omega_cyt,Omega_nuc];
-\end{DoxyCode}
-\begin{par}
-INPUT
-\end{par} \vspace{1em}
-\begin{DoxyCode}
-    syms t
-    u(1) = spline_pos5(t, 0.0, sp1, 5.0, sp2, 10.0, sp3, 20.0, sp4, 60.0, sp5, 0, 0.0);
-\end{DoxyCode}
-
-         \begin{DoxyCode}Warning: Support of strings that are not valid variable names or define a number
-will be removed in a future release. To create symbolic expressions, first
-create symbolic variables and then use operations on them. 
-\end{DoxyCode} 
-    \begin{par}
-SYSTEM EQUATIONS
-\end{par} \vspace{1em}
-\begin{DoxyCode}
-    model.sym.xdot = sym(zeros(size(model.sym.x)));
-
-    model.sym.xdot(1) = (Omega_nuc*p4*nSTAT5 - Omega_cyt*STAT*p1*u(1))/Omega_cyt;
-    model.sym.xdot(2) = STAT*p1*u(1) - 2*p2*pSTAT^2;
-    model.sym.xdot(3) = p2*pSTAT^2 - p3*pSTAT_pSTAT;
-    model.sym.xdot(4) = -(Omega_nuc*p4*npSTAT_npSTAT - Omega_cyt*p3*pSTAT_pSTAT)/Omega_nuc;
-    model.sym.xdot(5) = -p4*(nSTAT1 - 2*npSTAT_npSTAT);
-    model.sym.xdot(6) = p4*(nSTAT1 - nSTAT2);
-    model.sym.xdot(7) = p4*(nSTAT2 - nSTAT3);
-    model.sym.xdot(8) = p4*(nSTAT3 - nSTAT4);
-    model.sym.xdot(9) = p4*(nSTAT4 - nSTAT5);
-\end{DoxyCode}
-\begin{par}
-INITIAL CONDITIONS
-\end{par} \vspace{1em}
-\begin{DoxyCode}
-    model.sym.x0 = sym(zeros(size(model.sym.x)));
-
-    model.sym.x0(1) = init_STAT;
-\end{DoxyCode}
-\begin{par}
-OBSERVABLES
-\end{par} \vspace{1em}
-\begin{DoxyCode}
-    model.sym.y = sym(zeros(3,1));
-
-    model.sym.y(1) = offset_pSTAT + scale_pSTAT/init_STAT*(pSTAT + 2*pSTAT_pSTAT);
-    model.sym.y(2) = offset_tSTAT + scale_tSTAT/init_STAT*(STAT + pSTAT + 2*(pSTAT_pSTAT));
-    model.sym.y(3) = u(1);
-\end{DoxyCode}
-\begin{par}
-SIGMA
-\end{par} \vspace{1em}
-\begin{DoxyCode}
-    model.sym.sigma_y = sym(size(model.sym.y));
-
-    model.sym.sigma_y(1) = sigma_pSTAT;
-    model.sym.sigma_y(2) = sigma_tSTAT;
-    model.sym.sigma_y(3) = sigma_pEpoR;
-\end{DoxyCode}
-\begin{DoxyCode}
-end
-\end{DoxyCode}
-
-         \begin{DoxyCode}ans = 
-      sym: [1x1 struct]
-    param: 'log10'
-\end{DoxyCode} 
-    
-
-
-
-    
\ No newline at end of file
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-   <!--
-This HTML was auto-generated from MATLAB code.
-To make changes, update the MATLAB code and republish this document.
-      --><title>example_steadystate</title><meta name="generator" content="MATLAB 9.0"><link rel="schema.DC" href="http://purl.org/dc/elements/1.1/"><meta name="DC.date" content="2016-05-04"><meta name="DC.source" content="example_steadystate.m"><style type="text/css">
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-
-
-
-
-
-  </style></head><body><div class="content"><pre class="codeinput"><span class="keyword">function</span> example_steadystate
-</pre><p>COMPILATION</p><pre class="codeinput">    [exdir,~,~]=fileparts(which(<span class="string">'example_steadystate.m'</span>));
-    <span class="comment">% compile the model</span>
-    amiwrap(<span class="string">'model_steadystate'</span>,<span class="string">'model_steadystate_syms'</span>,exdir)
-</pre><pre class="codeoutput">Generating model struct ...
-Parsing model struct ...
-Generating C code ...
-headers | wrapfunctions | Compiling mex file ...
-amici | Building with 'Xcode with Clang'.
-MEX completed successfully.
-Building with 'Xcode with Clang'.
-MEX completed successfully.
-</pre><p>SIMULATION</p><pre class="codeinput">    <span class="comment">% time vector</span>
-    t = linspace(0,300,20);
-    p = [1;0.5;0.4;2;0.1];
-    k = [0.1,0.4,0.7,1];
-
-    options = amioption(<span class="string">'sensi'</span>,0,<span class="keyword">...</span>
-        <span class="string">'maxsteps'</span>,1e4);
-    <span class="comment">% load mex into memory</span>
-    sol = simulate_model_steadystate(t,log10(p),k,[],options);
-
-    tic
-    sol = simulate_model_steadystate(t,log10(p),k,[],options);
-    disp([<span class="string">'Time elapsed with cvodes: '</span> num2str(toc) ])
-</pre><pre class="codeoutput">Time elapsed with cvodes: 0.0040652
-</pre><p>ODE15S</p><pre class="codeinput">    ode_system = @(t,x,p,k) [-2*p(1)*x(1)^2 - p(2)*x(1)*x(2) + 2*p(3)*x(2) + p(4)*x(3) + p(5);
-        + p(1)*x(1)^2 - p(2)*x(1)*x(2) - p(3)*x(2) + p(4)*x(3);
-        + p(2)*x(1)*x(2) - p(4)*x(3) - k(4)*x(3)];
-    options_ode15s = odeset(<span class="string">'RelTol'</span>,options.rtol,<span class="string">'AbsTol'</span>,options.atol,<span class="string">'MaxStep'</span>,options.maxsteps);
-
-    tic
-    [~, X_ode15s] = ode15s(@(t,x) ode_system(t,x,p,k),t,k(1:3),options_ode15s);
-    disp([<span class="string">'Time elapsed with ode15s: '</span> num2str(toc) ])
-</pre><pre class="codeoutput">Time elapsed with ode15s: 0.10806
-</pre><p>PLOTTING</p><pre class="codeinput">    figure
-    c_x = get(gca,<span class="string">'ColorOrder'</span>);
-    subplot(2,2,1)
-    <span class="keyword">for</span> ix = 1:size(sol.x,2)
-        plot(t,sol.x(:,ix),<span class="string">'.-'</span>,<span class="string">'Color'</span>,c_x(ix,:))
-        hold <span class="string">on</span>
-        plot(t,X_ode15s(:,ix),<span class="string">'d'</span>,<span class="string">'Color'</span>,c_x(ix,:))
-    <span class="keyword">end</span>
-    legend(<span class="string">'x1'</span>,<span class="string">'x1_{ode15s}'</span>,<span class="string">'x2'</span>,<span class="string">'x2_{ode15s}'</span>,<span class="string">'x3'</span>,<span class="string">'x3_{ode15s}'</span>,<span class="string">'Location'</span>,<span class="string">'NorthEastOutside'</span>)
-    legend <span class="string">boxoff</span>
-    xlabel(<span class="string">'time t'</span>)
-    ylabel(<span class="string">'x'</span>)
-    box <span class="string">on</span>
-    subplot(2,2,2)
-    plot(t,abs(sol.x-X_ode15s),<span class="string">'--'</span>)
-    set(gca,<span class="string">'YScale'</span>,<span class="string">'log'</span>)
-    legend(<span class="string">'error x1'</span>,<span class="string">'error x2'</span>,<span class="string">'error x3'</span>,<span class="string">'Location'</span>,<span class="string">'NorthEastOutside'</span>)
-    legend <span class="string">boxoff</span>
-    set(gcf,<span class="string">'Position'</span>,[100 300 1200 500])
-</pre><img vspace="5" hspace="5" src="../examples/example_steadystate/html/example_steadystate_01.png" alt=""> <p>FORWARD SENSITIVITY ANALYSIS</p><pre class="codeinput">    options.sensi = 1;
-    options.sens_ind = [3,1,2,4];
-
-    sol = simulate_model_steadystate(t,log10(p),k,[],options);
-</pre><p>FINITE DIFFERENCES</p><pre class="codeinput">    eps = 1e-3;
-
-    xi = log10(p);
-    <span class="keyword">for</span> ip = 1:4;
-        xip = xi;
-        xip(ip) = xip(ip) + eps;
-        solp = simulate_model_steadystate(t,xip,k,[],options);
-        sx_fd(:,:,ip) = (solp.x - sol.x)/eps;
-        sy_fd(:,:,ip) = (solp.y - sol.y)/eps;
-    <span class="keyword">end</span>
-</pre><p>PLOTTING</p><pre class="codeinput">    figure
-    <span class="keyword">for</span> ip = 1:4
-        subplot(4,2,ip*2-1)
-        hold <span class="string">on</span>
-        <span class="keyword">for</span> ix = 1:size(sol.x,2)
-            plot(t,sol.sx(:,ix,ip),<span class="string">'.-'</span>,<span class="string">'Color'</span>,c_x(ix,:))
-            plot(t,sx_fd(:,ix,options.sens_ind(ip)),<span class="string">'d'</span>,<span class="string">'Color'</span>,c_x(ix,:))
-        <span class="keyword">end</span>
-        legend(<span class="string">'x1'</span>,<span class="string">'x1_{fd}'</span>,<span class="string">'x2'</span>,<span class="string">'x2_{fd}'</span>,<span class="string">'x3'</span>,<span class="string">'x3_{fd}'</span>,<span class="string">'Location'</span>,<span class="string">'NorthEastOutside'</span>)
-        legend <span class="string">boxoff</span>
-        title([<span class="string">'state sensitivity for p'</span> num2str(options.sens_ind(ip))])
-        xlabel(<span class="string">'time t'</span>)
-        ylabel(<span class="string">'x'</span>)
-        box <span class="string">on</span>
-
-        subplot(4,2,ip*2)
-        plot(t,abs(sol.sx(:,:,ip)-sx_fd(:,:,options.sens_ind(ip))),<span class="string">'--'</span>)
-        legend(<span class="string">'error x1'</span>,<span class="string">'error x2'</span>,<span class="string">'error x3'</span>,<span class="string">'Location'</span>,<span class="string">'NorthEastOutside'</span>)
-        legend <span class="string">boxoff</span>
-        title([<span class="string">'error of state sensitivity for p'</span> num2str(options.sens_ind(ip))])
-        xlabel(<span class="string">'time t'</span>)
-        ylabel(<span class="string">'error'</span>)
-        set(gca,<span class="string">'YScale'</span>,<span class="string">'log'</span>)
-        box <span class="string">on</span>
-    <span class="keyword">end</span>
-    set(gcf,<span class="string">'Position'</span>,[100 300 1200 500])
-</pre><img vspace="5" hspace="5" src="../examples/example_steadystate/html/example_steadystate_02.png" alt=""> <p>STEADY STATE SENSITIVITY</p><pre class="codeinput">    sssens = NaN(size(sol.sx));
-    <span class="keyword">for</span> it = 2:length(t)
-        tt = [0,t(it)];
-        options.sensi_meth = <span class="string">'ss'</span>;
-        solss = simulate_model_steadystate(tt,log10(p),k,[],options);
-        sssens(it,:,:) = solss.sx;
-        ssxdot(it,:) = solss.xdot;
-    <span class="keyword">end</span>
-</pre><p>PLOTTING</p><pre class="codeinput">    figure
-    <span class="keyword">for</span> ip = 1:4
-        subplot(4,2,ip*2-1)
-        hold <span class="string">on</span>
-        <span class="keyword">for</span> ix = 1:size(sol.x,2)
-            plot(t,sol.sx(:,ix,ip),<span class="string">'.-'</span>,<span class="string">'Color'</span>,c_x(ix,:))
-            plot(t,sssens(:,ix,ip),<span class="string">'d-'</span>,<span class="string">'Color'</span>,c_x(ix,:))
-        <span class="keyword">end</span>
-        legend(<span class="string">'x1'</span>,<span class="string">'x1_{ss}'</span>,<span class="string">'x2'</span>,<span class="string">'x2_{ss}'</span>,<span class="string">'x3'</span>,<span class="string">'x3_{ss}'</span>,<span class="string">'Location'</span>,<span class="string">'NorthEastOutside'</span>)
-        legend <span class="string">boxoff</span>
-        title([<span class="string">'state steady sensitivity for p'</span> num2str(ip)])
-        xlabel(<span class="string">'time t'</span>)
-        ylabel(<span class="string">'x'</span>)
-        box <span class="string">on</span>
-
-        subplot(4,2,ip*2)
-        plot(t,abs(sol.sx(:,:,ip)-sssens(:,:,ip)),<span class="string">'--'</span>)
-        legend(<span class="string">'error x1'</span>,<span class="string">'error x2'</span>,<span class="string">'error x3'</span>,<span class="string">'Location'</span>,<span class="string">'NorthEastOutside'</span>)
-        legend <span class="string">boxoff</span>
-        title([<span class="string">'error of steady state sensitivity for p'</span> num2str(ip)])
-        xlabel(<span class="string">'time t'</span>)
-        ylabel(<span class="string">'error'</span>)
-        set(gca,<span class="string">'YScale'</span>,<span class="string">'log'</span>)
-        box <span class="string">on</span>
-    <span class="keyword">end</span>
-    set(gcf,<span class="string">'Position'</span>,[100 300 1200 500])
-
-    figure
-    scatter(sqrt(sum((ssxdot./sol.x).^2,2)),sqrt(sum(sum((sol.sx-sssens).^2,2),3)))
-    hold <span class="string">on</span>
-    plot([1e-15,1e5],[1e-15,1e5],<span class="string">'k:'</span>)
-    set(gca,<span class="string">'YScale'</span>,<span class="string">'log'</span>)
-    set(gca,<span class="string">'XScale'</span>,<span class="string">'log'</span>)
-    box <span class="string">on</span>
-    axis <span class="string">square</span>
-    xlabel(<span class="string">'||dxdt/x||_2'</span>)
-    ylabel(<span class="string">'error steady state approximation'</span>)
-    set(gca,<span class="string">'FontSize'</span>,15)
-    set(gca,<span class="string">'LineWidth'</span>,1.5)
-    set(gcf,<span class="string">'Position'</span>,[100 300 1200 500])
-
-    drawnow
-</pre><img vspace="5" hspace="5" src="../examples/example_steadystate/html/example_steadystate_03.png" alt=""> <img vspace="5" hspace="5" src="../examples/example_steadystate/html/example_steadystate_04.png" alt=""> <pre class="codeinput"><span class="keyword">end</span>
-</pre><p class="footer"><br><a href="http://www.mathworks.com/products/matlab/">Published with MATLAB&reg; R2016a</a><br></p></div><!--
-##### SOURCE BEGIN #####
-function example_steadystate
-    %%
-    % COMPILATION
-    
-    [exdir,~,~]=fileparts(which('example_steadystate.m'));
-    % compile the model
-    amiwrap('model_steadystate','model_steadystate_syms',exdir)
-    
-    %%
-    % SIMULATION
-    
-    % time vector
-    t = linspace(0,300,20);
-    p = [1;0.5;0.4;2;0.1];
-    k = [0.1,0.4,0.7,1];
-    
-    options = amioption('sensi',0,...
-        'maxsteps',1e4);
-    % load mex into memory
-    sol = simulate_model_steadystate(t,log10(p),k,[],options);
-    
-    tic
-    sol = simulate_model_steadystate(t,log10(p),k,[],options);
-    disp(['Time elapsed with cvodes: ' num2str(toc) ])
-    
-    %%
-    % ODE15S
-    
-    ode_system = @(t,x,p,k) [-2*p(1)*x(1)^2 - p(2)*x(1)*x(2) + 2*p(3)*x(2) + p(4)*x(3) + p(5);
-        + p(1)*x(1)^2 - p(2)*x(1)*x(2) - p(3)*x(2) + p(4)*x(3);
-        + p(2)*x(1)*x(2) - p(4)*x(3) - k(4)*x(3)];
-    options_ode15s = odeset('RelTol',options.rtol,'AbsTol',options.atol,'MaxStep',options.maxsteps);
-    
-    tic
-    [~, X_ode15s] = ode15s(@(t,x) ode_system(t,x,p,k),t,k(1:3),options_ode15s);
-    disp(['Time elapsed with ode15s: ' num2str(toc) ])
-    
-    %%
-    % PLOTTING
-    
-    figure
-    c_x = get(gca,'ColorOrder');
-    subplot(2,2,1)
-    for ix = 1:size(sol.x,2)
-        plot(t,sol.x(:,ix),'.-','Color',c_x(ix,:))
-        hold on
-        plot(t,X_ode15s(:,ix),'d','Color',c_x(ix,:))
-    end
-    legend('x1','x1_{ode15s}','x2','x2_{ode15s}','x3','x3_{ode15s}','Location','NorthEastOutside')
-    legend boxoff
-    xlabel('time t')
-    ylabel('x')
-    box on
-    subplot(2,2,2)
-    plot(t,abs(sol.x-X_ode15s),'REPLACE_WITH_DASH_DASH')
-    set(gca,'YScale','log')
-    legend('error x1','error x2','error x3','Location','NorthEastOutside')
-    legend boxoff
-    set(gcf,'Position',[100 300 1200 500])
-    
-    %%
-    % FORWARD SENSITIVITY ANALYSIS
-    
-    options.sensi = 1;
-    options.sens_ind = [3,1,2,4];
-    
-    sol = simulate_model_steadystate(t,log10(p),k,[],options);
-    
-    %%
-    % FINITE DIFFERENCES
-    
-    eps = 1e-3;
-    
-    xi = log10(p);
-    for ip = 1:4;
-        xip = xi;
-        xip(ip) = xip(ip) + eps;
-        solp = simulate_model_steadystate(t,xip,k,[],options);
-        sx_fd(:,:,ip) = (solp.x - sol.x)/eps;
-        sy_fd(:,:,ip) = (solp.y - sol.y)/eps;
-    end
-    
-    %%
-    % PLOTTING
-    figure
-    for ip = 1:4
-        subplot(4,2,ip*2-1)
-        hold on
-        for ix = 1:size(sol.x,2)
-            plot(t,sol.sx(:,ix,ip),'.-','Color',c_x(ix,:))
-            plot(t,sx_fd(:,ix,options.sens_ind(ip)),'d','Color',c_x(ix,:))
-        end
-        legend('x1','x1_{fd}','x2','x2_{fd}','x3','x3_{fd}','Location','NorthEastOutside')
-        legend boxoff
-        title(['state sensitivity for p' num2str(options.sens_ind(ip))])
-        xlabel('time t')
-        ylabel('x')
-        box on
-        
-        subplot(4,2,ip*2)
-        plot(t,abs(sol.sx(:,:,ip)-sx_fd(:,:,options.sens_ind(ip))),'REPLACE_WITH_DASH_DASH')
-        legend('error x1','error x2','error x3','Location','NorthEastOutside')
-        legend boxoff
-        title(['error of state sensitivity for p' num2str(options.sens_ind(ip))])
-        xlabel('time t')
-        ylabel('error')
-        set(gca,'YScale','log')
-        box on
-    end
-    set(gcf,'Position',[100 300 1200 500])
-    
-    
-    %%
-    % STEADY STATE SENSITIVITY
-    
-    sssens = NaN(size(sol.sx));
-    for it = 2:length(t)
-        tt = [0,t(it)];
-        options.sensi_meth = 'ss';
-        solss = simulate_model_steadystate(tt,log10(p),k,[],options);
-        sssens(it,:,:) = solss.sx;
-        ssxdot(it,:) = solss.xdot;
-    end
-    
-    %%
-    % PLOTTING
-    
-    figure
-    for ip = 1:4
-        subplot(4,2,ip*2-1)
-        hold on
-        for ix = 1:size(sol.x,2)
-            plot(t,sol.sx(:,ix,ip),'.-','Color',c_x(ix,:))
-            plot(t,sssens(:,ix,ip),'d-','Color',c_x(ix,:))
-        end
-        legend('x1','x1_{ss}','x2','x2_{ss}','x3','x3_{ss}','Location','NorthEastOutside')
-        legend boxoff
-        title(['state steady sensitivity for p' num2str(ip)])
-        xlabel('time t')
-        ylabel('x')
-        box on
-        
-        subplot(4,2,ip*2)
-        plot(t,abs(sol.sx(:,:,ip)-sssens(:,:,ip)),'REPLACE_WITH_DASH_DASH')
-        legend('error x1','error x2','error x3','Location','NorthEastOutside')
-        legend boxoff
-        title(['error of steady state sensitivity for p' num2str(ip)])
-        xlabel('time t')
-        ylabel('error')
-        set(gca,'YScale','log')
-        box on
-    end
-    set(gcf,'Position',[100 300 1200 500])
-    
-    figure
-    scatter(sqrt(sum((ssxdot./sol.x).^2,2)),sqrt(sum(sum((sol.sx-sssens).^2,2),3)))
-    hold on
-    plot([1e-15,1e5],[1e-15,1e5],'k:')
-    set(gca,'YScale','log')
-    set(gca,'XScale','log')
-    box on
-    axis square
-    xlabel('||dxdt/x||_2')
-    ylabel('error steady state approximation')
-    set(gca,'FontSize',15)
-    set(gca,'LineWidth',1.5)
-    set(gcf,'Position',[100 300 1200 500])
-    
-    drawnow
-    
-end
-
-
-
-##### SOURCE END #####
---></body></html>
\ No newline at end of file
diff --git a/matlab/examples/example_steadystate/html/example_steadystate.png b/matlab/examples/example_steadystate/html/example_steadystate.png
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diff --git a/matlab/examples/example_steadystate/html/example_steadystate.tex b/matlab/examples/example_steadystate/html/example_steadystate.tex
deleted file mode 100644
index aa1f66c48c..0000000000
--- a/matlab/examples/example_steadystate/html/example_steadystate.tex
+++ /dev/null
@@ -1,230 +0,0 @@
-
-% This LaTeX was auto-generated from MATLAB code.
-% To make changes, update the MATLAB code and republish this document.
-
-
-
-
-
-
-
-
-
-
-
-    
-    \begin{DoxyCode}
-function example_steadystate
-\end{DoxyCode}
-\begin{par}
-COMPILATION
-\end{par} \vspace{1em}
-\begin{DoxyCode}
-    [exdir,~,~]=fileparts(which('example_steadystate.m'));
-    % compile the model
-    amiwrap('model_steadystate','model_steadystate_syms',exdir)
-\end{DoxyCode}
-
-         \begin{DoxyCode}Generating model struct ...
-Parsing model struct ...
-
-Generating C code ...
-headers | wrapfunctions | 
-Compiling mex file ...
-amici | Building with 'Xcode with Clang'.
-MEX completed successfully.
-Building with 'Xcode with Clang'.
-MEX completed successfully.
-\end{DoxyCode} 
-    \begin{par}
-SIMULATION
-\end{par} \vspace{1em}
-\begin{DoxyCode}
-    % time vector
-    t = linspace(0,300,20);
-    p = [1;0.5;0.4;2;0.1];
-    k = [0.1,0.4,0.7,1];
-
-    options = amioption('sensi',0,...
-        'maxsteps',1e4);
-    % load mex into memory
-    sol = simulate_model_steadystate(t,log10(p),k,[],options);
-
-    tic
-    sol = simulate_model_steadystate(t,log10(p),k,[],options);
-    disp(['Time elapsed with cvodes: ' num2str(toc) ])
-\end{DoxyCode}
-
-         \begin{DoxyCode}Time elapsed with cvodes: 0.004374
-\end{DoxyCode} 
-    \begin{par}
-ODE15S
-\end{par} \vspace{1em}
-\begin{DoxyCode}
-    ode_system = @(t,x,p,k) [-2*p(1)*x(1)^2 - p(2)*x(1)*x(2) + 2*p(3)*x(2) + p(4)*x(3) + p(5);
-        + p(1)*x(1)^2 - p(2)*x(1)*x(2) - p(3)*x(2) + p(4)*x(3);
-        + p(2)*x(1)*x(2) - p(4)*x(3) - k(4)*x(3)];
-    options_ode15s = odeset('RelTol',options.rtol,'AbsTol',options.atol,'MaxStep',options.maxsteps);
-
-    tic
-    [~, X_ode15s] = ode15s(@(t,x) ode_system(t,x,p,k),t,k(1:3),options_ode15s);
-    disp(['Time elapsed with ode15s: ' num2str(toc) ])
-\end{DoxyCode}
-
-         \begin{DoxyCode}Time elapsed with ode15s: 0.066508
-\end{DoxyCode} 
-    \begin{par}
-PLOTTING
-\end{par} \vspace{1em}
-\begin{DoxyCode}
-    figure
-    c_x = get(gca,'ColorOrder');
-    subplot(2,2,1)
-    for ix = 1:size(sol.x,2)
-        plot(t,sol.x(:,ix),'.-','Color',c_x(ix,:))
-        hold on
-        plot(t,X_ode15s(:,ix),'d','Color',c_x(ix,:))
-    end
-    legend('x1','x1_{ode15s}','x2','x2_{ode15s}','x3','x3_{ode15s}','Location','NorthEastOutside')
-    legend boxoff
-    xlabel('time t')
-    ylabel('x')
-    box on
-    subplot(2,2,2)
-    plot(t,abs(sol.x-X_ode15s),'--')
-    set(gca,'YScale','log')
-    legend('error x1','error x2','error x3','Location','NorthEastOutside')
-    legend boxoff
-    set(gcf,'Position',[100 300 1200 500])
-\end{DoxyCode}
-
-\includegraphics[width=\textwidth]{../../examples/example_steadystate/html/example_steadystate_01.png}
-\begin{par}
-FORWARD SENSITIVITY ANALYSIS
-\end{par} \vspace{1em}
-\begin{DoxyCode}
-    options.sensi = 1;
-    options.sens_ind = [3,1,2,4];
-
-    sol = simulate_model_steadystate(t,log10(p),k,[],options);
-\end{DoxyCode}
-\begin{par}
-FINITE DIFFERENCES
-\end{par} \vspace{1em}
-\begin{DoxyCode}
-    eps = 1e-3;
-
-    xi = log10(p);
-    for ip = 1:4;
-        xip = xi;
-        xip(ip) = xip(ip) + eps;
-        solp = simulate_model_steadystate(t,xip,k,[],options);
-        sx_fd(:,:,ip) = (solp.x - sol.x)/eps;
-        sy_fd(:,:,ip) = (solp.y - sol.y)/eps;
-    end
-\end{DoxyCode}
-\begin{par}
-PLOTTING
-\end{par} \vspace{1em}
-\begin{DoxyCode}
-    figure
-    for ip = 1:4
-        subplot(4,2,ip*2-1)
-        hold on
-        for ix = 1:size(sol.x,2)
-            plot(t,sol.sx(:,ix,ip),'.-','Color',c_x(ix,:))
-            plot(t,sx_fd(:,ix,options.sens_ind(ip)),'d','Color',c_x(ix,:))
-        end
-        legend('x1','x1_{fd}','x2','x2_{fd}','x3','x3_{fd}','Location','NorthEastOutside')
-        legend boxoff
-        title(['state sensitivity for p' num2str(options.sens_ind(ip))])
-        xlabel('time t')
-        ylabel('x')
-        box on
-
-        subplot(4,2,ip*2)
-        plot(t,abs(sol.sx(:,:,ip)-sx_fd(:,:,options.sens_ind(ip))),'--')
-        legend('error x1','error x2','error x3','Location','NorthEastOutside')
-        legend boxoff
-        title(['error of state sensitivity for p' num2str(options.sens_ind(ip))])
-        xlabel('time t')
-        ylabel('error')
-        set(gca,'YScale','log')
-        box on
-    end
-    set(gcf,'Position',[100 300 1200 500])
-\end{DoxyCode}
-
-\includegraphics[width=\textwidth]{../../examples/example_steadystate/html/example_steadystate_02.png}
-\begin{par}
-STEADY STATE SENSITIVITY
-\end{par} \vspace{1em}
-\begin{DoxyCode}
-    sssens = NaN(size(sol.sx));
-    for it = 2:length(t)
-        tt = [0,t(it)];
-        options.sensi_meth = 'ss';
-        solss = simulate_model_steadystate(tt,log10(p),k,[],options);
-        sssens(it,:,:) = solss.sx;
-        ssxdot(it,:) = solss.xdot;
-    end
-\end{DoxyCode}
-\begin{par}
-PLOTTING
-\end{par} \vspace{1em}
-\begin{DoxyCode}
-    figure
-    for ip = 1:4
-        subplot(4,2,ip*2-1)
-        hold on
-        for ix = 1:size(sol.x,2)
-            plot(t,sol.sx(:,ix,ip),'.-','Color',c_x(ix,:))
-            plot(t,sssens(:,ix,ip),'d-','Color',c_x(ix,:))
-        end
-        legend('x1','x1_{ss}','x2','x2_{ss}','x3','x3_{ss}','Location','NorthEastOutside')
-        legend boxoff
-        title(['state steady sensitivity for p' num2str(ip)])
-        xlabel('time t')
-        ylabel('x')
-        box on
-
-        subplot(4,2,ip*2)
-        plot(t,abs(sol.sx(:,:,ip)-sssens(:,:,ip)),'--')
-        legend('error x1','error x2','error x3','Location','NorthEastOutside')
-        legend boxoff
-        title(['error of steady state sensitivity for p' num2str(ip)])
-        xlabel('time t')
-        ylabel('error')
-        set(gca,'YScale','log')
-        box on
-    end
-    set(gcf,'Position',[100 300 1200 500])
-
-    figure
-    scatter(sqrt(sum((ssxdot./sol.x).^2,2)),sqrt(sum(sum((sol.sx-sssens).^2,2),3)))
-    hold on
-    plot([1e-15,1e5],[1e-15,1e5],'k:')
-    set(gca,'YScale','log')
-    set(gca,'XScale','log')
-    box on
-    axis square
-    xlabel('||dxdt/x||_2')
-    ylabel('error steady state approximation')
-    set(gca,'FontSize',15)
-    set(gca,'LineWidth',1.5)
-    set(gcf,'Position',[100 300 1200 500])
-
-    drawnow
-\end{DoxyCode}
-
-\includegraphics[width=\textwidth]{../../examples/example_steadystate/html/example_steadystate_03.png}
-
-\includegraphics[width=\textwidth]{../../examples/example_steadystate/html/example_steadystate_04.png}
-\begin{DoxyCode}
-end
-\end{DoxyCode}
-
-
-
-
-    
\ No newline at end of file
diff --git a/matlab/examples/example_steadystate/html/example_steadystate_01.png b/matlab/examples/example_steadystate/html/example_steadystate_01.png
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diff --git a/matlab/examples/example_steadystate/html/model_steadystate_syms.html b/matlab/examples/example_steadystate/html/model_steadystate_syms.html
deleted file mode 100644
index 3ce3a449d3..0000000000
--- a/matlab/examples/example_steadystate/html/model_steadystate_syms.html
+++ /dev/null
@@ -1,180 +0,0 @@
-
-<!DOCTYPE html
-  PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN">
-<html><head>
-      <meta http-equiv="Content-Type" content="text/html; charset=utf-8">
-   <!--
-This HTML was auto-generated from MATLAB code.
-To make changes, update the MATLAB code and republish this document.
-      --><title>model_steadystate_syms</title><meta name="generator" content="MATLAB 9.0"><link rel="schema.DC" href="http://purl.org/dc/elements/1.1/"><meta name="DC.date" content="2016-05-04"><meta name="DC.source" content="model_steadystate_syms.m"><style type="text/css">
-html,body,div,span,applet,object,iframe,h1,h2,h3,h4,h5,h6,p,blockquote,pre,a,abbr,acronym,address,big,cite,code,del,dfn,em,font,img,ins,kbd,q,s,samp,small,strike,strong,sub,sup,tt,var,b,u,i,center,dl,dt,dd,ol,ul,li,fieldset,form,label,legend,table,caption,tbody,tfoot,thead,tr,th,td{margin:0;padding:0;border:0;outline:0;font-size:100%;vertical-align:baseline;background:transparent}body{line-height:1}ol,ul{list-style:none}blockquote,q{quotes:none}blockquote:before,blockquote:after,q:before,q:after{content:'';content:none}:focus{outine:0}ins{text-decoration:none}del{text-decoration:line-through}table{border-collapse:collapse;border-spacing:0}
-
-html { min-height:100%; margin-bottom:1px; }
-html body { height:100%; margin:0px; font-family:Arial, Helvetica, sans-serif; font-size:10px; color:#000; line-height:140%; background:#fff none; overflow-y:scroll; }
-html body td { vertical-align:top; text-align:left; }
-
-h1 { padding:0px; margin:0px 0px 25px; font-family:Arial, Helvetica, sans-serif; font-size:1.5em; color:#d55000; line-height:100%; font-weight:normal; }
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-
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-a:hover { color:#005fce; text-decoration:underline; }
-a:visited { color:#004aa0; text-decoration:none; }
-
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-
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-pre.error { color:red; }
-
-@media print { pre.codeinput, pre.codeoutput { word-wrap:break-word; width:100%; } }
-
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-span.comment { color:#228B22 }
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-
-.footer { width:auto; padding:10px 0px; margin:25px 0px 0px; border-top:1px dotted #878787; font-size:0.8em; line-height:140%; font-style:italic; color:#878787; text-align:left; float:none; }
-.footer p { margin:0px; }
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-
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-table td { padding:7px 5px; text-align:left; vertical-align:top; border:1px solid #d6d4d4; }
-
-
-
-
-
-  </style></head><body><div class="content"><pre class="codeinput"><span class="keyword">function</span> [model] = model_steadystate_syms()
-</pre><p>STATES</p><pre class="codeinput"><span class="comment">% create state syms</span>
-syms <span class="string">x1</span> <span class="string">x2</span> <span class="string">x3</span>
-
-<span class="comment">% create state vector</span>
-model.sym.x = [
-x1 x2 x3
-];
-</pre><p>PARAMETERS ( for these sensitivities will be computed )</p><pre class="codeinput"><span class="comment">% create parameter syms</span>
-syms <span class="string">p1</span> <span class="string">p2</span> <span class="string">p3</span> <span class="string">p4</span> <span class="string">p5</span>
-
-<span class="comment">% create parameter vector</span>
-model.sym.p = [p1,p2,p3,p4,p5];
-
-<span class="comment">% set the parametrisation of the problem options are 'log', 'log10' and</span>
-<span class="comment">% 'lin' (default).</span>
-model.param = <span class="string">'log10'</span>;
-</pre><p>CONSTANTS ( for these no sensitivities will be computed ) this part is optional and can be ommited</p><pre class="codeinput"><span class="comment">% create parameter syms</span>
-syms <span class="string">k1</span> <span class="string">k2</span> <span class="string">k3</span> <span class="string">k4</span>
-
-<span class="comment">% create parameter vector</span>
-model.sym.k = [k1 k2 k3 k4];
-</pre><p>SYSTEM EQUATIONS</p><pre class="codeinput"><span class="comment">% create symbolic variable for time</span>
-syms <span class="string">t</span>
-
-model.sym.xdot = sym(zeros(size(model.sym.x)));
-
-<span class="comment">% piecewise defined function</span>
-model.sym.xdot(1) = -2*p1*x1^2 - p2*x1*x2 + 2*p3*x2 + p4*x3 + p5;
-<span class="comment">% inhomogeneous</span>
-model.sym.xdot(2) = +p1*x1^2 - p2*x1*x2 - p3*x2 + p4*x3;
-model.sym.xdot(3) = p2*x1*x2 - p4*x3 - k4*x3;
-</pre><p>INITIAL CONDITIONS</p><pre class="codeinput">model.sym.x0 = sym(zeros(size(model.sym.x)));
-
-model.sym.x0(1) = k1;
-model.sym.x0(2) = k2;
-model.sym.x0(3) = k3;
-</pre><p>OBSERVALES</p><pre class="codeinput">model.sym.y = model.sym.x;
-</pre><pre class="codeinput"><span class="keyword">end</span>
-</pre><pre class="codeoutput">ans = 
-      sym: [1x1 struct]
-    param: 'log10'
-</pre><p class="footer"><br><a href="http://www.mathworks.com/products/matlab/">Published with MATLAB&reg; R2016a</a><br></p></div><!--
-##### SOURCE BEGIN #####
-function [model] = model_steadystate_syms()
-
-
-%%
-% STATES
-
-% create state syms
-syms x1 x2 x3
-
-% create state vector
-model.sym.x = [
-x1 x2 x3
-];
-
-%%
-% PARAMETERS ( for these sensitivities will be computed )
-
-% create parameter syms
-syms p1 p2 p3 p4 p5
-
-% create parameter vector 
-model.sym.p = [p1,p2,p3,p4,p5];
-
-% set the parametrisation of the problem options are 'log', 'log10' and
-% 'lin' (default).
-model.param = 'log10'; 
-
-
-%%
-% CONSTANTS ( for these no sensitivities will be computed )
-% this part is optional and can be ommited
-
-% create parameter syms
-syms k1 k2 k3 k4
-
-% create parameter vector 
-model.sym.k = [k1 k2 k3 k4];
-
-%%
-% SYSTEM EQUATIONS
-
-% create symbolic variable for time
-syms t
-
-model.sym.xdot = sym(zeros(size(model.sym.x)));
-
-% piecewise defined function
-model.sym.xdot(1) = -2*p1*x1^2 - p2*x1*x2 + 2*p3*x2 + p4*x3 + p5;
-% inhomogeneous
-model.sym.xdot(2) = +p1*x1^2 - p2*x1*x2 - p3*x2 + p4*x3;
-model.sym.xdot(3) = p2*x1*x2 - p4*x3 - k4*x3;
-
-%%
-% INITIAL CONDITIONS
-
-model.sym.x0 = sym(zeros(size(model.sym.x)));
-
-model.sym.x0(1) = k1;
-model.sym.x0(2) = k2;
-model.sym.x0(3) = k3;
-
-%%
-% OBSERVALES
-
-model.sym.y = model.sym.x;
-end
-##### SOURCE END #####
---></body></html>
\ No newline at end of file
diff --git a/matlab/examples/example_steadystate/html/model_steadystate_syms.tex b/matlab/examples/example_steadystate/html/model_steadystate_syms.tex
deleted file mode 100644
index d856dfb665..0000000000
--- a/matlab/examples/example_steadystate/html/model_steadystate_syms.tex
+++ /dev/null
@@ -1,98 +0,0 @@
-
-% This LaTeX was auto-generated from MATLAB code.
-% To make changes, update the MATLAB code and republish this document.
-
-
-
-
-
-
-
-
-
-
-
-    
-    \begin{DoxyCode}
-function [model] = model_steadystate_syms()
-\end{DoxyCode}
-\begin{par}
-STATES
-\end{par} \vspace{1em}
-\begin{DoxyCode}
-% create state syms
-syms x1 x2 x3
-
-% create state vector
-model.sym.x = [
-x1 x2 x3
-];
-\end{DoxyCode}
-\begin{par}
-PARAMETERS ( for these sensitivities will be computed )
-\end{par} \vspace{1em}
-\begin{DoxyCode}
-% create parameter syms
-syms p1 p2 p3 p4 p5
-
-% create parameter vector
-model.sym.p = [p1,p2,p3,p4,p5];
-
-% set the parametrisation of the problem options are 'log', 'log10' and
-% 'lin' (default).
-model.param = 'log10';
-\end{DoxyCode}
-\begin{par}
-CONSTANTS ( for these no sensitivities will be computed ) this part is optional and can be ommited
-\end{par} \vspace{1em}
-\begin{DoxyCode}
-% create parameter syms
-syms k1 k2 k3 k4
-
-% create parameter vector
-model.sym.k = [k1 k2 k3 k4];
-\end{DoxyCode}
-\begin{par}
-SYSTEM EQUATIONS
-\end{par} \vspace{1em}
-\begin{DoxyCode}
-% create symbolic variable for time
-syms t
-
-model.sym.xdot = sym(zeros(size(model.sym.x)));
-
-% piecewise defined function
-model.sym.xdot(1) = -2*p1*x1^2 - p2*x1*x2 + 2*p3*x2 + p4*x3 + p5;
-% inhomogeneous
-model.sym.xdot(2) = +p1*x1^2 - p2*x1*x2 - p3*x2 + p4*x3;
-model.sym.xdot(3) = p2*x1*x2 - p4*x3 - k4*x3;
-\end{DoxyCode}
-\begin{par}
-INITIAL CONDITIONS
-\end{par} \vspace{1em}
-\begin{DoxyCode}
-model.sym.x0 = sym(zeros(size(model.sym.x)));
-
-model.sym.x0(1) = k1;
-model.sym.x0(2) = k2;
-model.sym.x0(3) = k3;
-\end{DoxyCode}
-\begin{par}
-OBSERVALES
-\end{par} \vspace{1em}
-\begin{DoxyCode}
-model.sym.y = model.sym.x;
-\end{DoxyCode}
-\begin{DoxyCode}
-end
-\end{DoxyCode}
-
-         \begin{DoxyCode}ans = 
-      sym: [1x1 struct]
-    param: 'log10'
-\end{DoxyCode} 
-    
-
-
-
-    
\ No newline at end of file

From 1a96be5c64845c04da9ea344cd94fdd79a5c4d68 Mon Sep 17 00:00:00 2001
From: Daniel Weindl <dweindl@users.noreply.github.com>
Date: Sat, 16 Oct 2021 20:34:14 +0200
Subject: [PATCH 04/17] Fix amici::Solver copy ctr missing starttime_  (#1573)

* Fix amici::Solver copy ctr missing starttime_

Fix a bug where amici::Solver::starttime_ was not copied and which,
for example, would lead to failure in simulation-based preequilibration,
where the unset starttime would result in failure during the first
evaluation of xdot.

Fixes #1570

* More informative messages if maxtime was exceeded
---
 src/amici.cpp  | 43 +++++++++++++++++++++++++++++--------------
 src/solver.cpp |  2 +-
 2 files changed, 30 insertions(+), 15 deletions(-)

diff --git a/src/amici.cpp b/src/amici.cpp
index 4d6e57b1c8..87e929060c 100644
--- a/src/amici.cpp
+++ b/src/amici.cpp
@@ -172,29 +172,44 @@ AmiciApplication::runAmiciSimulation(Solver& solver,
     } catch (amici::IntegrationFailure const& ex) {
         if(ex.error_code == AMICI_RHSFUNC_FAIL && solver.timeExceeded()) {
             rdata->status = AMICI_MAX_TIME_EXCEEDED;
+            if(rethrow)
+                throw;
+            warningF("AMICI:simulation",
+                     "AMICI forward simulation failed at t = %f: "
+                     "Maximum time exceeed.\n",
+                     ex.time);
         } else {
             rdata->status = ex.error_code;
+            if (rethrow)
+                throw;
+            warningF("AMICI:simulation",
+                     "AMICI forward simulation failed at t = %f:\n%s\n",
+                     ex.time,
+                     ex.what());
+
         }
-        if (rethrow)
-            throw;
-        warningF("AMICI:simulation",
-                 "AMICI forward simulation failed at t = %f:\n%s\n",
-                 ex.time,
-                 ex.what());
     } catch (amici::IntegrationFailureB const& ex) {
         if(ex.error_code == AMICI_RHSFUNC_FAIL && solver.timeExceeded()) {
             rdata->status = AMICI_MAX_TIME_EXCEEDED;
+            if (rethrow)
+                throw;
+            warningF(
+                "AMICI:simulation",
+                "AMICI backward simulation failed when trying to solve until "
+                "t = %f: Maximum time exceeed.\n",
+                ex.time);
+
         } else {
             rdata->status = ex.error_code;
+            if (rethrow)
+                throw;
+            warningF(
+                "AMICI:simulation",
+                "AMICI backward simulation failed when trying to solve until t = %f"
+                " (see message above):\n%s\n",
+                ex.time,
+                ex.what());
         }
-        if (rethrow)
-            throw;
-        warningF(
-          "AMICI:simulation",
-          "AMICI backward simulation failed when trying to solve until t = %f"
-          " (see message above):\n%s\n",
-          ex.time,
-          ex.what());
     } catch (amici::AmiException const& ex) {
         rdata->status = AMICI_ERROR;
         if (rethrow)
diff --git a/src/solver.cpp b/src/solver.cpp
index 89cb67ae07..c774615669 100644
--- a/src/solver.cpp
+++ b/src/solver.cpp
@@ -20,7 +20,7 @@ Solver::Solver(AmiciApplication *app) : app(app)
 Solver::Solver(const Solver &other)
     : ism_(other.ism_), lmm_(other.lmm_), iter_(other.iter_),
       interp_type_(other.interp_type_), maxsteps_(other.maxsteps_),
-      maxtime_(other.maxtime_),
+      maxtime_(other.maxtime_), starttime_(other.starttime_),
       sensi_meth_(other.sensi_meth_), sensi_meth_preeq_(other.sensi_meth_preeq_),
       stldet_(other.stldet_), ordering_(other.ordering_),
       newton_maxsteps_(other.newton_maxsteps_),

From d07d47be037eb6c8eee162c5b8bc835f0dce36c7 Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Fabian=20Fr=C3=B6hlich?= <fabian_froehlich@hms.harvard.edu>
Date: Sat, 16 Oct 2021 17:25:08 -0400
Subject: [PATCH 05/17] extend checked benchmark models (#1571)

Co-authored-by: Daniel Weindl <dweindl@users.noreply.github.com>
---
 tests/benchmark-models/benchmark_models.yaml    | 17 +++++++++--------
 .../test_benchmark_collection.sh                | 12 ++++++------
 tests/benchmark-models/test_petab_model.py      |  7 ++++++-
 3 files changed, 21 insertions(+), 15 deletions(-)

diff --git a/tests/benchmark-models/benchmark_models.yaml b/tests/benchmark-models/benchmark_models.yaml
index d290171e82..80b37b555d 100644
--- a/tests/benchmark-models/benchmark_models.yaml
+++ b/tests/benchmark-models/benchmark_models.yaml
@@ -1,6 +1,6 @@
 Bachmann_MSB2011:
-  llh: -478.459689232875
-  note: unchecked
+  llh: 418.40573341425295
+  note: benchmark collection reference value matches up to sign when applying log10-correction +sum(log(meas*log(10)) / 2
 
 Becker_Science2010:
   llh: -364.118614198023
@@ -20,7 +20,9 @@ Borghans_BiophysChem1997:
 Brannmark_JBC2010:
   llh: -141.889113770537
 
-#Bruno_JExpBio2016:    None
+Bruno_JExpBot2016:
+  llh: 46.688176988431806
+  note: benchmark collection only reports chi2 value, but llh value can be derived
 
 Chen_MSB2009:
   llh: -115700.1192629893
@@ -43,12 +45,11 @@ Fujita_SciSignal2010:
 # Hass_PONE2017    None
 
 Isensee_JCB2018:
-  llh: 7950.84181339651
-  note: unchecked
+  llh: -3949.375966548649
+  note: benchmark collection reference also includes prior valuation, tested based on agreement of chi2 values
 
 Lucarelli_CellSystems2018:
-  llh: 91.8885069265334
-  note: unchecked
+  llh: -1681.6059879426584
 
 Merkle_PCB2016:
   llh: -1388.59682706751
@@ -60,7 +61,7 @@ Raia_CancerResearch2011:
 
 Schwen_PONE2014:
   llh: -943.9992988598723
-  note: benchmark collection reference value does not match, but model outputs do. maybe due to D2D data normalization
+  note: benchmark collection reference value does not match, but model outputs do. maybe due to priors
 
 Sneyd_PNAS2002:
   llh: 319.79177818768756
diff --git a/tests/benchmark-models/test_benchmark_collection.sh b/tests/benchmark-models/test_benchmark_collection.sh
index 0422dd3e23..d8d9e5f2f5 100755
--- a/tests/benchmark-models/test_benchmark_collection.sh
+++ b/tests/benchmark-models/test_benchmark_collection.sh
@@ -7,22 +7,24 @@
 
 # Confirmed to be working
 models="
+Bachmann_MSB2011
 Beer_MolBioSystems2014
 Boehm_JProteomeRes2014
 Borghans_BiophysChem1997
 Brannmark_JBC2010
+Bruno_JExpBot2016
 Crauste_CellSystems2017
 Elowitz_Nature2000
 Fiedler_BMC2016
 Fujita_SciSignal2010
+Isensee_JCB2018
+Lucarelli_CellSystems2018
 Schwen_PONE2014
 Sneyd_PNAS2002
 Weber_BMC2015
 Zheng_PNAS2012"
 
 #
-# Not matching reference for unclear reasons
-# Lucarelli_CellSystems2018
 #
 # PEtab needs fixing: Bachmann_MSB2011
 #
@@ -36,7 +38,7 @@ Zheng_PNAS2012"
 # Hass_PONE2017
 # Korkut_eLIFE2015
 # Perelson_Science1996
-# Bruno_JExpBio2016
+#
 #
 # yaml missing:
 # Casaletto_PNAS2019
@@ -53,11 +55,9 @@ Zheng_PNAS2012"
 # state-dependent sigmas:
 # Raia_CancerResearch2011
 #
-# Evaluation is known to be inconsistent:
+# Unknown reasons:
 # Chen_MSB2009
 #
-# Integration Failure:
-# Isensee_JCB2018
 
 set -e
 
diff --git a/tests/benchmark-models/test_petab_model.py b/tests/benchmark-models/test_petab_model.py
index 692a7aadd6..935065d10f 100755
--- a/tests/benchmark-models/test_petab_model.py
+++ b/tests/benchmark-models/test_petab_model.py
@@ -82,10 +82,15 @@ def main():
         sys.path.insert(0, args.model_directory)
     model_module = importlib.import_module(args.model_name)
     amici_model = model_module.getModel()
+    amici_solver = amici_model.getSolver()
+
+    if args.model_name == "Isensee_JCB2018":
+        amici_solver.setAbsoluteTolerance(1e-12)
+        amici_solver.setRelativeTolerance(1e-12)
 
     res = simulate_petab(
         petab_problem=problem, amici_model=amici_model,
-        log_level=logging.DEBUG)
+        solver=amici_solver, log_level=logging.DEBUG)
     rdatas = res[RDATAS]
     llh = res[LLH]
 

From aeb0fd7f823f2813594be79145db79c8025427b0 Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Fabian=20Fr=C3=B6hlich?= <fabian_froehlich@hms.harvard.edu>
Date: Sun, 17 Oct 2021 10:25:13 -0400
Subject: [PATCH 06/17] fix nan-propagation (#1574)

---
 python/amici/parameter_mapping.py | 3 +++
 1 file changed, 3 insertions(+)

diff --git a/python/amici/parameter_mapping.py b/python/amici/parameter_mapping.py
index 60b50ab63e..23e98e0bfc 100644
--- a/python/amici/parameter_mapping.py
+++ b/python/amici/parameter_mapping.py
@@ -202,6 +202,9 @@ def _get_par(model_par, value):
         if model_par in problem_parameters:
             # user-provided
             return problem_parameters[model_par]
+        # prevent nan-propagation in derivative
+        if np.isnan(value):
+            return 0.0
         # constant value
         return value
 

From e05907317107c00b5aac173a70466529d5ecf79f Mon Sep 17 00:00:00 2001
From: Daniel Weindl <dweindl@users.noreply.github.com>
Date: Mon, 18 Oct 2021 15:02:50 +0200
Subject: [PATCH 07/17] GHA: Update matlab actions to v1 (#1575)

---
 .github/workflows/test_matlab.yml | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/.github/workflows/test_matlab.yml b/.github/workflows/test_matlab.yml
index d14c0012b5..90757643d5 100644
--- a/.github/workflows/test_matlab.yml
+++ b/.github/workflows/test_matlab.yml
@@ -14,8 +14,8 @@ jobs:
     - run: echo "AMICI_DIR=$(pwd)" >> $GITHUB_ENV
 
     - name: Install MATLAB
-      uses: matlab-actions/setup-matlab@v0
+      uses: matlab-actions/setup-matlab@v1
     - name: Run script
-      uses: matlab-actions/run-command@v0
+      uses: matlab-actions/run-command@v1
       with:
         command: cd matlab; installAMICI; addpath tests; testModels

From 46d18a6bd90790334f9baaab53a71b3bcbd5e371 Mon Sep 17 00:00:00 2001
From: Daniel Weindl <dweindl@users.noreply.github.com>
Date: Mon, 25 Oct 2021 17:01:35 +0200
Subject: [PATCH 08/17] Update expected llh for Fujita_SciSignal2010 (#1577)

Expected llh changed due to incresead precision of measurements in https://github.com/Benchmarking-Initiative/Benchmark-Models-PEtab/pull/131
---
 tests/benchmark-models/benchmark_models.yaml | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/tests/benchmark-models/benchmark_models.yaml b/tests/benchmark-models/benchmark_models.yaml
index 80b37b555d..49e509f421 100644
--- a/tests/benchmark-models/benchmark_models.yaml
+++ b/tests/benchmark-models/benchmark_models.yaml
@@ -40,7 +40,7 @@ Fiedler_BMC2016:
   llh: 58.58390161681
 
 Fujita_SciSignal2010:
-  llh: 53.08749124997969
+  llh: 53.08377736998929
 
 # Hass_PONE2017    None
 

From e429c77804930ffd582049ab6f522b09a48c61ef Mon Sep 17 00:00:00 2001
From: Daniel Weindl <dweindl@users.noreply.github.com>
Date: Mon, 25 Oct 2021 21:58:34 +0200
Subject: [PATCH 09/17] CI: Update sonar scanner version (4.6.1.2450) (#1579)

---
 .github/workflows/test_python_cplusplus.yml | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/.github/workflows/test_python_cplusplus.yml b/.github/workflows/test_python_cplusplus.yml
index 0451ab88fb..a5c8cc7823 100644
--- a/.github/workflows/test_python_cplusplus.yml
+++ b/.github/workflows/test_python_cplusplus.yml
@@ -20,7 +20,7 @@ jobs:
     - run: echo "BNGPATH=${GITHUB_WORKSPACE}/ThirdParty/BioNetGen-2.7.0" >> $GITHUB_ENV
 
     # sonar cloud
-    - run: echo "SONAR_SCANNER_VERSION=4.5.0.2216" >> $GITHUB_ENV
+    - run: echo "SONAR_SCANNER_VERSION=4.6.1.2450" >> $GITHUB_ENV
     - run: echo "SONAR_SCANNER_HOME=${HOME}/.sonar/sonar-scanner-$SONAR_SCANNER_VERSION-linux" >> $GITHUB_ENV
     - run: echo "SONAR_SCANNER_OPTS=-server" >> $GITHUB_ENV
     - run: echo "${SONAR_SCANNER_HOME}/bin" >> $GITHUB_PATH

From b4e33bbdf38f4733d1e53b24502f4756b02507b2 Mon Sep 17 00:00:00 2001
From: Daniel Weindl <dweindl@users.noreply.github.com>
Date: Mon, 25 Oct 2021 22:02:54 +0200
Subject: [PATCH 10/17] Doc: Update list of publications (#1580)

Closes #1566
---
 documentation/amici_refs.bib | 37 ++++++++++++++++++++++++++++++++++++
 documentation/references.md  |  8 +++++++-
 2 files changed, 44 insertions(+), 1 deletion(-)

diff --git a/documentation/amici_refs.bib b/documentation/amici_refs.bib
index bf72b85dfd..900728cb1e 100644
--- a/documentation/amici_refs.bib
+++ b/documentation/amici_refs.bib
@@ -946,6 +946,43 @@ @phdthesis{Maier2021
   doi       = {10.25932/publishup-51587},
   year        = {2021},
 }
+@article {Contento2021.10.01.21263052,
+	author = {Contento, Lorenzo and Castelletti, Noemi and Raim{\'u}ndez, Elba and Le Gleut, Ronan and Sch{\"a}lte, Yannik and Stapor, Paul and Hinske, Ludwig Christian and H{\"o}lscher, Michael and Wieser, Andreas and Radon, Katja and Fuchs, Christiane and Hasenauer, Jan and the KoCo19 study group},
+	title = {Integrative modelling of reported case numbers and seroprevalence reveals time-dependent test efficiency and infection rates},
+	elocation-id = {2021.10.01.21263052},
+	year = {2021},
+	doi = {10.1101/2021.10.01.21263052},
+	publisher = {Cold Spring Harbor Laboratory Press},
+	abstract = {Mathematical models have been widely used during the ongoing SARS-CoV-2 pandemic for data interpretation, forecasting, and policy making. However, most models are based on officially reported case numbers, which depend on test availability and test strategies. The time dependence of these factors renders interpretation difficult and might even result in estimation biases.Here, we present a computational modelling framework that allows for the integration of reported case numbers with seroprevalence estimates obtained from representative population cohorts. To account for the time dependence of infection and testing rates, we embed flexible splines in an epidemiological model. The parameters of these splines are estimated, along with the other parameters, from the available data using a Bayesian approach.The application of this approach to the official case numbers reported for Munich (Germany) and the seroprevalence reported by the prospective COVID-19 Cohort Munich (KoCo19) provides first estimates for the time dependence of the under-reporting factor. Furthermore, we estimate how the effectiveness of non-pharmaceutical interventions and of the testing strategy evolves over time. Overall, our results show that the integration of temporally highly resolved and representative data is beneficial for accurate epidemiological analyses.Competing Interest StatementThe authors have declared no competing interest.Funding StatementThis study was funded by the Bavarian State Ministry of Science and the Arts, the University Hospital of Ludwig-Maximilians-University Munich, the Helmholtz Centre Munich, the University of Bonn (via the Transdiciplinary Research Areas), the University of Bielefeld, Munich Center of Health (McHealth) and the German Ministry for Education and Research (MoKoCo19, reference number 01KI20271), German Research Foundation (SEPAN, reference number HA7376/3-1), Volkswagen Stiftung (reference number: 99 450). This work was supported by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) under Germany{\textquoteright}s Excellence Strategy EXC 2047/1 - 390685813 and EXC 2151 - 390873048. The ORCHESTRA project has received funding from the European Union{\textquoteright}s Horizon 2020 research and innovation programme under grant agreement No 101016167. The views expressed in this paper are the sole responsibility of the authors and the Commission is not responsible for any use that may be made of the information it contains. The funders had no role in study design, data collection, data analyses, data interpretation, writing, or submission of this manuscript.Author DeclarationsI confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained.YesThe details of the IRB/oversight body that provided approval or exemption for the research described are given below:The study protocol was approved by the Institutional Review Board at the Ludwig-Maximilians-University in Munich, Germany (opinion date 31 March 2020, number 20-275, opinion date amendment: 10 October 2020), prior to study initiation.All necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived.YesI understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance).YesI have followed all appropriate research reporting guidelines and uploaded the relevant EQUATOR Network research reporting checklist(s) and other pertinent material as supplementary files, if applicable.YesThe data used in this manuscript (except data from public sources such as the Robert Koch Institute) cannot be made public due to patient consent.},
+	URL = {https://www.medrxiv.org/content/early/2021/10/01/2021.10.01.21263052},
+	eprint = {https://www.medrxiv.org/content/early/2021/10/01/2021.10.01.21263052.full.pdf},
+	journal = {medRxiv}
+}
+
+@Article{GudinaAli2021,
+  author   = {Esayas Kebede Gudina and Solomon Ali and Eyob Girma and Addisu Gize and Birhanemeskel Tegene and Gadissa Bedada Hundie and Wondewosen Tsegaye Sime and Rozina Ambachew and Alganesh Gebreyohanns and Mahteme Bekele and Abhishek Bakuli and Kira Elsbernd and Simon Merkt and Lorenzo Contento and Michael Hoelscher and Jan Hasenauer and Andreas Wieser and Arne Kroidl},
+  journal  = {The Lancet Global Health},
+  title    = {{Seroepidemiology and model-based prediction of SARS-CoV-2 in Ethiopia: longitudinal cohort study among front-line hospital workers and communities}},
+  year     = {2021},
+  issn     = {2214-109X},
+  number   = {11},
+  pages    = {e1517-e1527},
+  volume   = {9},
+  abstract = {Summary
+Background
+Over 1 year since the first reported case, the true COVID-19 burden in Ethiopia remains unknown due to insufficient surveillance. We aimed to investigate the seroepidemiology of SARS-CoV-2 among front-line hospital workers and communities in Ethiopia.
+Methods
+We did a population-based, longitudinal cohort study at two tertiary teaching hospitals involving hospital workers, rural residents, and urban communities in Jimma and Addis Ababa. Hospital workers were recruited at both hospitals, and community participants were recruited by convenience sampling including urban metropolitan settings, urban and semi-urban settings, and rural communities. Participants were eligible if they were aged 18 years or older, had provided written informed consent, and were willing to provide blood samples by venepuncture. Only one participant per household was recruited. Serology was done with Elecsys anti-SARS-CoV-2 anti-nucleocapsid assay in three consecutive rounds, with a mean interval of 6 weeks between tests, to obtain seroprevalence and incidence estimates within the cohorts.
+Findings
+Between Aug 5, 2020, and April 10, 2021, we did three survey rounds with a total of 1104 hospital workers and 1229 community residents participating. SARS-CoV-2 seroprevalence among hospital workers increased strongly during the study period: in Addis Ababa, it increased from 10·9% (95% credible interval [CrI] 8·3–13·8) in August, 2020, to 53·7% (44·8–62·5) in February, 2021, with an incidence rate of 2223 per 100 000 person-weeks (95% CI 1785–2696); in Jimma Town, it increased from 30·8% (95% CrI 26·9–34·8) in November, 2020, to 56·1% (51·1–61·1) in February, 2021, with an incidence rate of 3810 per 100 000 person-weeks (95% CI 3149–4540). Among urban communities, an almost 40% increase in seroprevalence was observed in early 2021, with incidence rates of 1622 per 100 000 person-weeks (1004–2429) in Jimma Town and 4646 per 100 000 person-weeks (2797–7255) in Addis Ababa. Seroprevalence in rural communities increased from 18·0% (95% CrI 13·5–23·2) in November, 2020, to 31·0% (22·3–40·3) in March, 2021.
+Interpretation
+SARS-CoV-2 spread in Ethiopia has been highly dynamic among hospital worker and urban communities. We can speculate that the greatest wave of SARS-CoV-2 infections is currently evolving in rural Ethiopia, and thus requires focused attention regarding health-care burden and disease prevention.
+Funding
+Bavarian State Ministry of Sciences, Research, and the Arts; Germany Ministry of Education and Research; EU Horizon 2020 programme; Deutsche Forschungsgemeinschaft; and Volkswagenstiftung.},
+  doi      = {https://doi.org/10.1016/S2214-109X(21)00386-7},
+  url      = {https://www.sciencedirect.com/science/article/pii/S2214109X21003867},
+}
+
 @Comment{jabref-meta: databaseType:bibtex;}
 
 @Comment{jabref-meta: grouping:
diff --git a/documentation/references.md b/documentation/references.md
index 7ef0254192..42979d7e81 100644
--- a/documentation/references.md
+++ b/documentation/references.md
@@ -1,6 +1,6 @@
 # References
 
-List of publications using AMICI. Total number is 62.
+List of publications using AMICI. Total number is 64.
 
 If you applied AMICI in your work and your publication is missing, please let us know via a new Github issue.
 
@@ -9,6 +9,9 @@ If you applied AMICI in your work and your publication is missing, please let us
 <div id="ref-BastBuc2021">
 <p>Bast, Lisa, Michèle C. Buck, Judith S. Hecker, Robert A. J. Oostendorp, Katharina S. Götze, and Carsten Marr. 2021. “Computational Modeling of Stem and Progenitor Cell Kinetics Identifies Plausible Hematopoietic Lineage Hierarchies.” <em>iScience</em> 24 (2): 102120. <a href="https://doi.org/https://doi.org/10.1016/j.isci.2021.102120">https://doi.org/https://doi.org/10.1016/j.isci.2021.102120</a>.</p>
 </div>
+<div id="ref-Contento2021.10.01.21263052">
+<p>Contento, Lorenzo, Noemi Castelletti, Elba Raimúndez, Ronan Le Gleut, Yannik Schälte, Paul Stapor, Ludwig Christian Hinske, et al. 2021. “Integrative Modelling of Reported Case Numbers and Seroprevalence Reveals Time-Dependent Test Efficiency and Infection Rates.” <em>medRxiv</em>. <a href="https://doi.org/10.1101/2021.10.01.21263052">https://doi.org/10.1101/2021.10.01.21263052</a>.</p>
+</div>
 <div id="ref-ErdemMut2021">
 <p>Erdem, Cemal, Arnab Mutsuddy, Ethan M. Bensman, William B. Dodd, Michael M. Saint-Antoine, Mehdi Bouhaddou, Robert C. Blake, et al. 2021. “A Scalable, Open-Source Implementation of a Large-Scale Mechanistic Model for Single Cell Proliferation and Death Signaling.” <em>bioRxiv</em>. <a href="https://doi.org/10.1101/2020.11.09.373407">https://doi.org/10.1101/2020.11.09.373407</a>.</p>
 </div>
@@ -18,6 +21,9 @@ If you applied AMICI in your work and your publication is missing, please let us
 <div id="ref-Gaspari2021">
 <p>Gaspari, Erika. 2021. “Model-Driven Design of Mycoplasma as a Vaccine Chassis.” PhD thesis, Wageningen: Wageningen University. <a href="https://doi.org/10.18174/539593">https://doi.org/10.18174/539593</a>.</p>
 </div>
+<div id="ref-GudinaAli2021">
+<p>Gudina, Esayas Kebede, Solomon Ali, Eyob Girma, Addisu Gize, Birhanemeskel Tegene, Gadissa Bedada Hundie, Wondewosen Tsegaye Sime, et al. 2021. “Seroepidemiology and model-based prediction of SARS-CoV-2 in Ethiopia: longitudinal cohort study among front-line hospital workers and communities.” <em>The Lancet Global Health</em> 9 (11): e1517–e1527. <a href="https://doi.org/https://doi.org/10.1016/S2214-109X(21)00386-7">https://doi.org/https://doi.org/10.1016/S2214-109X(21)00386-7</a>.</p>
+</div>
 <div id="ref-Maier2021">
 <p>Maier, Corinna. 2021. “Bayesian Data Assimilation and Reinforcement Learning for Model-Informed Precision Dosing in Oncology.” Doctoralthesis, Universität Potsdam. <a href="https://doi.org/10.25932/publishup-51587">https://doi.org/10.25932/publishup-51587</a>.</p>
 </div>

From f4a45c223d6d7faefebb9e437971f1d4cdead607 Mon Sep 17 00:00:00 2001
From: Dilan Pathirana <59329744+dilpath@users.noreply.github.com>
Date: Tue, 26 Oct 2021 20:45:20 +0200
Subject: [PATCH 11/17] Helper methods to save and restore model instance-only
 settings (#1576)

* save model instance settings

* tests for handled getters and setters

* test to identify unhandled getters and setters
---
 python/amici/__init__.py            |  61 ++++++++-
 python/tests/test_swig_interface.py | 192 ++++++++++++++++++++++++++++
 2 files changed, 252 insertions(+), 1 deletion(-)

diff --git a/python/amici/__init__.py b/python/amici/__init__.py
index 6d5420b163..af4b7376d0 100644
--- a/python/amici/__init__.py
+++ b/python/amici/__init__.py
@@ -26,7 +26,7 @@
 import sys
 from contextlib import suppress, contextmanager
 from types import ModuleType as ModelModule
-from typing import Optional, Union, Sequence, List
+from typing import Any, Dict, Optional, Union, Sequence, List
 
 
 def _get_amici_path():
@@ -280,6 +280,65 @@ def writeSolverSettingsToHDF5(
     amici.writeSolverSettingsToHDF5(_get_ptr(solver), file, location)
 
 
+# Values are suffixes of `get[...]` and `set[...]` `amici.Model` methods.
+# If either the getter or setter is not named with this pattern, then the value
+# is a tuple where the first and second elements are the getter and setter
+# methods, respectively.
+model_instance_settings = [
+    'AddSigmaResiduals',
+    'AlwaysCheckFinite',
+    'FixedParameters',
+    'InitialStates',
+    'InitialStateSensitivities',
+    'MinimumSigmaResiduals',
+    ('nMaxEvent', 'setNMaxEvent'),
+    'Parameters',
+    'ParameterList',
+    'ParameterScale',  # getter returns a SWIG object
+    'ReinitializationStateIdxs',
+    'ReinitializeFixedParameterInitialStates',
+    'StateIsNonNegative',
+    'SteadyStateSensitivityMode',
+    ('t0', 'setT0'),
+    'Timepoints',
+]
+
+
+def get_model_settings(
+        model: AmiciModel,
+) -> Dict[str, Any]:
+    """Get model settings that are set independently of the compiled model.
+
+    :param model: The AMICI model instance.
+
+    :returns: Keys are AMICI model attributes, values are attribute values.
+    """
+    settings = {}
+    for setting in model_instance_settings:
+        getter = setting[0] if isinstance(setting, tuple) else f'get{setting}'
+        settings[setting] = getattr(model, getter)()
+        # TODO `amici.Model.getParameterScale` returns a SWIG object instead
+        # of a Python list/tuple.
+        if setting == 'ParameterScale':
+            settings[setting] = tuple(settings[setting])
+    return settings
+
+
+def set_model_settings(
+        model: AmiciModel,
+        settings: Dict[str, Any],
+) -> None:
+    """Set model settings.
+
+    :param model: The AMICI model instance.
+    :param settings: Keys are callable attributes (setters) of an AMICI model,
+        values are provided to the setters.
+    """
+    for setting, value in settings.items():
+        setter = setting[1] if isinstance(setting, tuple) else f'set{setting}'
+        getattr(model, setter)(value)
+
+
 class add_path:
     """Context manager for temporarily changing PYTHONPATH"""
 
diff --git a/python/tests/test_swig_interface.py b/python/tests/test_swig_interface.py
index a951521c53..3459c5c38d 100644
--- a/python/tests/test_swig_interface.py
+++ b/python/tests/test_swig_interface.py
@@ -50,6 +50,198 @@ def test_copy_constructors(pysb_example_presimulation_module):
                 f"{obj} - {attr}"
 
 
+# `None` values are skipped in `test_model_instance_settings`.
+# Keys are suffixes of `get[...]` and `set[...]` `amici.Model` methods.
+# If either the getter or setter is not named with this pattern, then the key
+# is a tuple where the first and second elements are the getter and setter
+# methods, respectively.
+# Values are lists where the first element is the default value of the test
+# model, and the second value is some custom value.
+# Default values are based on `pysb_example_presimulation_module`.
+model_instance_settings0 = {
+    # setting name: [default value, custom value]
+    'AddSigmaResiduals': [
+        False,
+        True
+    ],
+    'AlwaysCheckFinite': [
+        False,
+        True,
+    ],
+    # Skipped due to model dependency in `'InitialStates'`.
+    'FixedParameters': None,
+    'InitialStates': [
+        (10.0, 9.0, 1.0, 0.0, 0.0, 0.0),
+        tuple([.1]*6),
+    ],
+    'InitialStateSensitivities': [
+        tuple([1.0] + [0.0]*35),
+        tuple([.1]*36),
+    ],
+    'MinimumSigmaResiduals': [
+        50.0,
+        60.0,
+    ],
+    ('nMaxEvent', 'setNMaxEvent'): [
+        10,
+        20,
+    ],
+    'Parameters': [
+        (10.0, 0.1, 0.1, 0.1, 0.1, 0.1),
+        tuple([1.0] * 6)
+    ],
+    # Skipped due to interdependency with `'InitialStateSensitivities'`.
+    'ParameterList': None,
+    # Skipped due to interdependency with `'InitialStateSensitivities'`.
+    'ParameterScale': None,
+    # Skipped due to interdependencies with
+    # `'ReinitializeFixedParameterInitialStates'`.
+    'ReinitializationStateIdxs': None,
+    # Skipped due to interdependencies with `'ReinitializationStateIdxs'`.
+    'ReinitializeFixedParameterInitialStates': None,
+    # Skipped due to conservation laws in the test model
+    # `pysb_example_presimulation_module.getModel()`.
+    'StateIsNonNegative': None,
+    'SteadyStateSensitivityMode': [
+        0,
+        1,
+    ],
+    ('t0', 'setT0'): [
+        0.0,
+        1.0,
+    ],
+    'Timepoints': [
+        tuple(),
+        (1.0, 2.0, 3.0),
+    ],
+}
+
+
+def test_model_instance_settings(pysb_example_presimulation_module):
+    model0 = pysb_example_presimulation_module.getModel()
+
+    # Indexes of values in the `model_instance_settings0` dictionary.
+    i_default = 0
+    i_custom = 1
+
+    i_getter = 0
+    i_setter = 1
+
+    # All settings are tested.
+    assert set(model_instance_settings0) == set(amici.model_instance_settings)
+
+    # Skip settings with interdependencies.
+    model_instance_settings = \
+        {k: v for k, v in model_instance_settings0.items() if v is not None}
+
+    # All custom values are different to default values.
+    assert all([
+        default != custom
+        for name, (default, custom) in model_instance_settings.items()
+        if name != 'ReinitializeFixedParameterInitialStates'
+    ])
+
+    # All default values are as expected.
+    for name, (default, custom) in model_instance_settings.items():
+        getter = name[i_getter] if isinstance(name, tuple) else f'get{name}'
+        setter = name[i_setter] if isinstance(name, tuple) else f'set{name}'
+        # Default values are as expected.
+        assert getattr(model0, getter)() == default
+        # Custom value is set correctly.
+        getattr(model0, setter)(custom)
+        assert getattr(model0, getter)() == custom
+
+    # The grouped getter method works.
+    custom_settings = amici.get_model_settings(model0)
+    for name in model_instance_settings:
+        assert custom_settings[name] == model_instance_settings[name][i_custom]
+
+    # Create a new model for comparison.
+    model = pysb_example_presimulation_module.getModel()
+
+    # The new model has the default settings.
+    model_default_settings = amici.get_model_settings(model)
+    for name in model_instance_settings:
+        assert model_default_settings[name] == \
+            model_instance_settings[name][i_default]
+
+    # The grouped setter method works.
+    custom_settings_not_none = {
+        name: value
+        for name, value in custom_settings.items()
+        if model_instance_settings0[name] is not None
+    }
+    amici.set_model_settings(model, custom_settings_not_none)
+    assert all([
+        value == custom_settings_not_none[name]
+        for name, value in amici.get_model_settings(model).items()
+        if name in custom_settings_not_none
+    ])
+
+
+def test_unhandled_settings(pysb_example_presimulation_module):
+    """Detect possible getters and setters that are not yet handled.
+
+    Currently, only model attributes that begin with `'get'` and `'set'` are
+    tested.
+
+    The following getters/setters are untested here, due to unusual naming
+    (not prefixed by `'get'` or `'set'`).
+    - nMaxEvent
+    - t0
+    """
+    model = pysb_example_presimulation_module.getModel()
+
+    not_handled = [
+        'get',
+        'getAmiciCommit',
+        'getAmiciVersion',
+        'getExpressionIds',
+        'getExpressionNames',
+        'getFixedParameterById',
+        'getFixedParameterByName',
+        'getFixedParameterIds',
+        'getFixedParameterNames',
+        'getName',
+        'getObservableIds',
+        'getObservableNames',
+        'getObservableScaling',
+        'getParameterById',
+        'getParameterByName',
+        'getParameterIds',
+        'getParameterNames',
+        'getSolver',
+        'getStateIds',
+        'getStateNames',
+        'getTimepoint',
+        'getUnscaledParameters',
+        'setAllStatesNonNegative',
+        'setFixedParameterById',
+        'setFixedParameterByName',
+        'setFixedParametersByIdRegex',
+        'setFixedParametersByNameRegex',
+        'setParameterById',
+        'setParameterByName',
+        'setParametersByIdRegex',
+        'setParametersByNameRegex',
+        'setUnscaledInitialStateSensitivities',
+    ]
+
+    handled = [
+        name
+        for names in amici.model_instance_settings
+        for name in (
+            names
+            if isinstance(names, tuple) else
+            (f'get{names}', f'set{names}')
+        )
+    ]
+
+    for attribute in dir(model):
+        if attribute[:3] in ['get', 'set'] and attribute not in not_handled:
+            assert attribute in handled, attribute
+
+
 def is_callable_but_not_getter(obj, attr):
     if not callable(getattr(obj, attr)):
         return False

From e98850578ff780fe665fbba55cb7cd825e527213 Mon Sep 17 00:00:00 2001
From: Daniel Weindl <dweindl@users.noreply.github.com>
Date: Tue, 26 Oct 2021 21:26:27 +0200
Subject: [PATCH 12/17] GHA: Additional nightly tests (#1578)

Regularly check benchmark collection models, performance tests and documentation.
---
 .github/workflows/test_benchmark_collection_models.yml | 2 ++
 .github/workflows/test_doc.yml                         | 2 ++
 .github/workflows/test_performance.yml                 | 3 +++
 3 files changed, 7 insertions(+)

diff --git a/.github/workflows/test_benchmark_collection_models.yml b/.github/workflows/test_benchmark_collection_models.yml
index c9cc965f94..0acd4bea59 100644
--- a/.github/workflows/test_benchmark_collection_models.yml
+++ b/.github/workflows/test_benchmark_collection_models.yml
@@ -10,6 +10,8 @@ on:
       - master
       - develop
   workflow_dispatch:
+  schedule:
+    - cron:  '48 4 * * *'
 
 jobs:
   build:
diff --git a/.github/workflows/test_doc.yml b/.github/workflows/test_doc.yml
index 1e0be9afee..f2fc8ab6c1 100644
--- a/.github/workflows/test_doc.yml
+++ b/.github/workflows/test_doc.yml
@@ -9,6 +9,8 @@ on:
       - develop
       - master
   workflow_dispatch:
+  schedule:
+    - cron:  '48 4 * * *'
 
 jobs:
   doxygen:
diff --git a/.github/workflows/test_performance.yml b/.github/workflows/test_performance.yml
index a2f463b2f4..16f8018d49 100644
--- a/.github/workflows/test_performance.yml
+++ b/.github/workflows/test_performance.yml
@@ -12,6 +12,9 @@ on:
 
   workflow_dispatch:
 
+  schedule:
+    - cron:  '48 4 * * *'
+
 jobs:
   build:
     name: Performance Test

From 3199d50bd452de053739e0951c8990ce248a4a95 Mon Sep 17 00:00:00 2001
From: Daniel Weindl <dweindl@users.noreply.github.com>
Date: Thu, 28 Oct 2021 16:27:28 +0200
Subject: [PATCH 13/17] doc: Add missing amici.petab_simulate to API doc
 (#1581)

* doc: Add missing amici.petab_simulate to API doc

* Fix formatting
---
 documentation/python_modules.rst | 1 +
 python/amici/petab_simulate.py   | 5 ++++-
 2 files changed, 5 insertions(+), 1 deletion(-)

diff --git a/documentation/python_modules.rst b/documentation/python_modules.rst
index 71109934a7..b493fb7ff7 100644
--- a/documentation/python_modules.rst
+++ b/documentation/python_modules.rst
@@ -13,6 +13,7 @@ AMICI Python API
    amici.petab_import
    amici.petab_import_pysb
    amici.petab_objective
+   amici.petab_simulate
    amici.import_utils
    amici.ode_export
    amici.plotting
diff --git a/python/amici/petab_simulate.py b/python/amici/petab_simulate.py
index 0b4b2d07b6..54058897b7 100644
--- a/python/amici/petab_simulate.py
+++ b/python/amici/petab_simulate.py
@@ -2,7 +2,10 @@
 PEtab Simulate
 --------------
 Functionality related to the use of AMICI for simulation with PEtab's
-Simulator class. Use cases:
+Simulator class.
+
+Use cases:
+
 - generate data for use with PEtab's plotting methods
 - generate synthetic data
 """

From 0374f87a37a888dba774d2d7055316be00abdb5e Mon Sep 17 00:00:00 2001
From: Daniel Weindl <dweindl@users.noreply.github.com>
Date: Sun, 7 Nov 2021 15:14:01 +0100
Subject: [PATCH 14/17] Prepare for Python 3.10 (#1555)

* GHA: Also test on Python3.10
* specify numpy requirement for extension building with Python3.10
---
 .github/workflows/test_python_ver_matrix.yml | 2 +-
 python/sdist/pyproject.toml                  | 7 +++++--
 python/sdist/setup.cfg                       | 3 ++-
 3 files changed, 8 insertions(+), 4 deletions(-)

diff --git a/.github/workflows/test_python_ver_matrix.yml b/.github/workflows/test_python_ver_matrix.yml
index 4e730126d8..a3a6952bfe 100644
--- a/.github/workflows/test_python_ver_matrix.yml
+++ b/.github/workflows/test_python_ver_matrix.yml
@@ -22,7 +22,7 @@ jobs:
     strategy:
       fail-fast: false
       matrix:
-        python-version: [3.7, 3.8, 3.9]
+        python-version: [3.7, 3.8, 3.9, '3.10']
         experimental: [false]
 # Temporarily disabled because the respective jobs somehow runs infinitely
 #        include:
diff --git a/python/sdist/pyproject.toml b/python/sdist/pyproject.toml
index 787846435c..31c8ed75ae 100644
--- a/python/sdist/pyproject.toml
+++ b/python/sdist/pyproject.toml
@@ -9,9 +9,12 @@ requires = [
     # would be pinning the setup.py numpy requirement to the same version as
     # here, which we want to avoid.
     # cf. discussion at https://github.com/numpy/numpy/issues/5888
-    # These requirements are taken from the h5py package, we depend on.
+    # See also:
+    #  https://github.com/scipy/oldest-supported-numpy/blob/master/setup.cfg
+    #  https://github.com/h5py/h5py/blob/master/setup.py
     "numpy==1.14.5; python_version=='3.7'",
     "numpy==1.17.5; python_version=='3.8'",
-    "numpy==1.19.3; python_version>='3.9'",
+    "numpy==1.19.3; python_version=='3.9'",
+    "numpy==1.21.4; python_version>='3.10'",
 ]
 build-backend = "setuptools.build_meta"
diff --git a/python/sdist/setup.cfg b/python/sdist/setup.cfg
index e37885e29c..c0aa1c8bd6 100644
--- a/python/sdist/setup.cfg
+++ b/python/sdist/setup.cfg
@@ -30,7 +30,8 @@ install_requires =
     sympy>=1.7.1,<1.9
     numpy>=1.14.5; python_version=='3.7'
     numpy>=1.17.5; python_version=='3.8'
-    numpy>=1.19.3; python_version>='3.9'
+    numpy>=1.19.3; python_version=='3.9'
+    numpy>=1.21.4; python_version>='3.10'
     python-libsbml
     h5py
     pandas

From 9e96a6e6bb2824dd175d37b1805f681c3b1a60f9 Mon Sep 17 00:00:00 2001
From: Daniel Weindl <dweindl@users.noreply.github.com>
Date: Thu, 11 Nov 2021 20:47:32 +0100
Subject: [PATCH 15/17] Fix dxdotdw for RateRules (#1584)

... and potentially other situations.

Removes dxdotdw hack.

Fixes a bug where dxdotdw would be wrongly set to zero despite w-dependent
SBML RateRules.

Fixes #1583

Co-authored-by: FFroehlich <fabian@schaluck.com>
---
 python/amici/ode_export.py  | 50 +------------------------------------
 python/amici/sbml_import.py | 40 +++--------------------------
 2 files changed, 4 insertions(+), 86 deletions(-)

diff --git a/python/amici/ode_export.py b/python/amici/ode_export.py
index e0376b8791..69d2ba1cf6 100644
--- a/python/amici/ode_export.py
+++ b/python/amici/ode_export.py
@@ -1058,18 +1058,13 @@ def import_from_sbml_importer(self,
 
         # get symbolic expression from SBML importers
         symbols = copy.copy(si.symbols)
-        nexpr = len(symbols[SymbolId.EXPRESSION])
 
         # assemble fluxes and add them as expressions to the model
         assert len(si.flux_ids) == len(si.flux_vector)
         fluxes = [generate_flux_symbol(ir, name=flux_id)
                   for ir, flux_id in enumerate(si.flux_ids)]
-        nr = len(fluxes)
 
         # correct time derivatives for compartment changes
-
-        dxdotdw_updates = []
-
         def transform_dxdt_to_concentration(species_id, dxdt):
             """
             Produces the appropriate expression for the first derivative of a
@@ -1097,14 +1092,9 @@ def transform_dxdt_to_concentration(species_id, dxdt):
             species = si.symbols[SymbolId.SPECIES][species_id]
 
             comp = species['compartment']
-            x_index = species['index']
             if comp in si.symbols[SymbolId.SPECIES]:
                 dv_dt = si.symbols[SymbolId.SPECIES][comp]['dt']
                 xdot = (dxdt - dv_dt * species_id) / comp
-                dxdotdw_updates.extend(
-                    (x_index, w_index, xdot.diff(r_flux))
-                    for w_index, r_flux in enumerate(fluxes)
-                )
                 return xdot
             elif comp in si.compartment_assignment_rules:
                 v = si.compartment_assignment_rules[comp]
@@ -1123,10 +1113,6 @@ def transform_dxdt_to_concentration(species_id, dxdt):
                         v.diff(var) * si.symbols[SymbolId.SPECIES][var]['dt']
                 dv_dx = v.diff(species_id)
                 xdot = (dxdt - dv_dt * species_id) / (dv_dx * species_id + v)
-                dxdotdw_updates.extend(
-                    (x_index, w_index, xdot.diff(r_flux))
-                    for w_index, r_flux in enumerate(fluxes)
-                )
                 return xdot
             else:
                 v = si.compartments[comp]
@@ -1134,13 +1120,6 @@ def transform_dxdt_to_concentration(species_id, dxdt):
                 if v == 1.0:
                     return dxdt
 
-                dxdotdw_updates.extend(
-                    (x_index, w_index,
-                     si.stoichiometric_matrix[x_index, w_index] / v)
-                    for w_index in range(si.stoichiometric_matrix.shape[1])
-                    if si.stoichiometric_matrix[x_index, w_index] != 0
-                )
-
                 return dxdt / v
 
         # create dynamics without respecting conservation laws first
@@ -1196,34 +1175,7 @@ def transform_dxdt_to_concentration(species_id, dxdt):
 
         # process conservation laws
         if compute_cls:
-            dxdotdw_updates = si.process_conservation_laws(self,
-                                                           dxdotdw_updates)
-
-        nx_solver = si.stoichiometric_matrix.shape[0]
-        nw = len(self._expressions)
-        ncl = nw - nr - nexpr
-
-        # set derivatives of xdot, if applicable. We do this as we can save
-        # a substantial amount of computations by exploiting the structure
-        # of the right hand side.
-        # the tricky part is that the expressions w do not only contain the
-        # flux entries, but also assignment rules and conservation laws.
-        # assignment rules are added before the fluxes and
-        # _process_conservation_laws is called after the fluxes,
-        # but conservation law expressions are inserted at the beginning
-        # of the self.eq['w']. Accordingly we concatenate a zero matrix (for
-        # rule assignments and conservation laws) with the stoichiometric
-        # matrix and then apply the necessary updates from
-        # transform_dxdt_to_concentration
-
-        if not any(s in [e.get_id() for e in self._expressions]
-                   for s in si.stoichiometric_matrix.free_symbols):
-            self._eqs['dxdotdw'] = sp.zeros(nx_solver, ncl + nexpr).row_join(
-                si.stoichiometric_matrix
-            )
-            for ix, iw, val in dxdotdw_updates:
-                # offset update according to concatenated zero matrix
-                self._eqs['dxdotdw'][ix, ncl + nexpr + iw] = val
+            si.process_conservation_laws(self)
 
         # fill in 'self._sym' based on prototypes and components in ode_model
         self.generate_basic_variables(from_sbml=True)
diff --git a/python/amici/sbml_import.py b/python/amici/sbml_import.py
index c851384d76..a03bc7cc8c 100644
--- a/python/amici/sbml_import.py
+++ b/python/amici/sbml_import.py
@@ -1380,17 +1380,13 @@ def _make_initial(self, sym_math: Union[sp.Expr, None, float]
 
         return sym_math
 
-    def process_conservation_laws(self, ode_model, volume_updates) -> List:
+    def process_conservation_laws(self, ode_model) -> None:
         """
         Find conservation laws in reactions and species.
 
         :param ode_model:
             ODEModel object with basic definitions
 
-        :param volume_updates:
-            List with updates for the stoichiometric matrix accounting for
-            compartment volumes
-
         :returns volume_updates_solver:
             List (according to reduced stoichiometry) with updates for the
             stoichiometric matrix accounting for compartment volumes
@@ -1409,43 +1405,13 @@ def process_conservation_laws(self, ode_model, volume_updates) -> List:
             species_solver = list(range(ode_model.num_states_rdata()))
 
         # prune out species from stoichiometry and
-        volume_updates_solver = self._reduce_stoichiometry(species_solver,
-                                                           volume_updates)
+        self.stoichiometric_matrix = \
+            self.stoichiometric_matrix[species_solver, :]
 
         # add the found CLs to the ode_model
         for cl in conservation_laws:
             ode_model.add_conservation_law(**cl)
 
-        return volume_updates_solver
-
-    def _reduce_stoichiometry(self, species_solver, volume_updates) -> List:
-        """
-        Reduces the stoichiometry with respect to conserved quantities
-
-        :param species_solver:
-            List of species indices which remain later in the ODE solver
-
-        :param volume_updates:
-            List with updates for the stoichiometric matrix accounting for
-            compartment volumes
-
-        :returns volume_updates_solver:
-            List (according to reduced stoichiometry) with updates for the
-            stoichiometric matrix accounting for compartment volumes
-        """
-
-        # prune out constant species from stoichiometric matrix
-        self.stoichiometric_matrix = \
-            self.stoichiometric_matrix[species_solver, :]
-
-        # updates of stoichiometry (later dxdotdw in ode_exporter) must be
-        # corrected for conserved quantities:
-        volume_updates_solver = [(species_solver.index(ix), iw, val)
-                                 for (ix, iw, val) in volume_updates
-                                 if ix in species_solver]
-
-        return volume_updates_solver
-
     def _replace_compartments_with_volumes(self):
         """
         Replaces compartment symbols in expressions with their respective

From 928c8c5e40dd129a21c0f7d35bd78e756a034f3e Mon Sep 17 00:00:00 2001
From: Daniel Weindl <dweindl@users.noreply.github.com>
Date: Thu, 11 Nov 2021 21:49:22 +0100
Subject: [PATCH 16/17] Fix string formatting in gradient-check output (#1585)

and check "lower-level" sensitivities before likelihood
---
 python/amici/gradient_check.py | 10 ++++++----
 1 file changed, 6 insertions(+), 4 deletions(-)

diff --git a/python/amici/gradient_check.py b/python/amici/gradient_check.py
index 6055e2bdd2..e703d9a69a 100644
--- a/python/amici/gradient_check.py
+++ b/python/amici/gradient_check.py
@@ -183,8 +183,6 @@ def check_derivatives(model: Model,
     assert_fun(rdata['status'] == AMICI_SUCCESS)
 
     fields = []
-    if edata is not None:
-        fields.append('llh')
 
     if solver.getSensitivityMethod() == SensitivityMethod.forward and \
             solver.getSensitivityOrder() <= SensitivityOrder.first:
@@ -210,6 +208,10 @@ def check_derivatives(model: Model,
                       -np.dot(rdata['res'].T, rdata['sres']),
                       assert_fun,
                       1e-8, 1e-4)
+
+    if edata is not None:
+        fields.append('llh')
+
     for ip, pval in enumerate(p):
         if pval == 0.0 and skip_zero_pars:
             continue
@@ -257,10 +259,10 @@ def check_close(result: np.array,
     if not close.all():
         if ip is None:
             index_str = ''
-            check_type = 'Regression check  '
+            check_type = 'Regression check'
         else:
             index_str = f'at index ip={ip} '
-            check_type = 'FD check '
+            check_type = 'FD check'
         print(f'{check_type} failed for {field} {index_str}for '
               f'{close.size - close.sum()} indices:')
         adev = np.abs(result - expected)

From 06ed8b9e95810ea48d209c66294aa6c676fd74be Mon Sep 17 00:00:00 2001
From: FFroehlich <fabian@schaluck.com>
Date: Thu, 11 Nov 2021 18:36:56 -0500
Subject: [PATCH 17/17] bump version and update changelog

---
 CHANGELOG.md | 17 +++++++++++++++++
 version.txt  |  2 +-
 2 files changed, 18 insertions(+), 1 deletion(-)

diff --git a/CHANGELOG.md b/CHANGELOG.md
index f2aeeb35b3..1b30edd21e 100644
--- a/CHANGELOG.md
+++ b/CHANGELOG.md
@@ -2,6 +2,23 @@
 
 ## v0.X Series
 
+### v0.11.20 (2021-11-12)
+
+New: 
+ * Changed parameter mappings such that unassigned values have non-nan default values. This fixes erroneous evaluation of `llh` as `NaN` in some situations (#1574)
+ * Added support for Python 3.10 (#1555)
+
+Fixes:
+ * Fixed a bug when simulation start time was not transferred when copying a solver instance (#1573)
+ * Fixed a bug which led to incorrect sensitivies for models with multiple assignment rules or rate rules (#1584)
+
+Other:
+ * Update CI and documentation settings (#1569, #1527, #1572, #1575, #1579, #1580, #1589, #1581)
+ * Extend set of validated benchmark models that is checked during CI (#1571, #1577)
+ * Fixed string formatting in derivative checks (#1585)
+ * Added helper methods to save and restore model instance-only settings (#1576)
+
+
 ### v0.11.19 (2021-10-13)
 
 New:
diff --git a/version.txt b/version.txt
index 8f78d386f2..7809b80a4f 100644
--- a/version.txt
+++ b/version.txt
@@ -1 +1 @@
-0.11.19
+0.11.20