co2mpas 1.2.1

A vehicle simulator predicting CO2 emissions for NEDC using WLTP time-series

.. meta::
:theme-color: #CCCC00
.. doc/_static/CO2MPAS_banner.png
:width: 300 px
:align: center

##################################################################
CO2MPAS: Vehicle simulator predicting NEDC CO2 emissions from WLTP
##################################################################

:Release: 1.2.1
:Date: 2016-04-18 22:31:58
:Home: http://co2mpas.io/
:Releases: http://files.co2mpas.io/
:Sources: https://github.com/JRCSTU/co2mpas
:pypi-repo: https://pypi.python.org/pypi/co2mpas
:Keywords: CO2, fuel-consumption, WLTP, NEDC, vehicle, automotive,
EU, JRC, IET, STU, back-translation, policy,
simulator, engineering, scientific
:Developers: .. include:: AUTHORS.rst
:Copyright: 2015-2016 European Commission (`JRC-IET
<https://ec.europa.eu/jrc/en/institutes/iet>`_)
:License: `EUPL 1.1+ <https://joinup.ec.europa.eu/software/page/eupl>`_

**CO2MPAS** is backward-looking longitudinal-dynamics CO\ sub(`2`) and
fuel-consumption simulator for light-duty vehicles (cars and vans),
specially crafted to back-translate consumption figures from WLTP cycles
into NEDC ones.

It is an open-source project developed with Python-3.4,
using Anaconda & WinPython under Windows 7, Anaconda under MacOS, and
Linux's standard python environment.
It runs as a *console command*, with various graphical UIs on the making.

History
=======
The *European Commission* is supporting the introduction of the *WLTP cycle*
for Light-duty vehicles developed at the *United Nations (UNECE)*
level, in the shortest possible time-frame. Its introduction requires
the adaptation of CO\ sub(`2`) certification and monitoring procedures set
by European regulations. European Commission's *Joint Research Centre* has been
assigned the development of this vehicle simulator to facilitate this
adaptation.

For recent activity, check the doc(`changes`).


Quickstart
==========
.. Tip::
**About console-commands:**

- Console-commands beginning with ``$`` symbol are for the ``bash`` shell
(UNIX).
You can install it on *Windows* with **cygwin**: https://www.cygwin.com/
along with these useful utilities::

* git, git-completion
* make, zip, unzip, bzip2, 7z, dos2unix
* openssh, curl, wget

- Console-commands beginning with ``>`` symbol are for *Windows* ``cmd.exe``
command-prompt.
You can augment it with bash-like capabilities using **Clink**:
http://mridgers.github.io/clink/

- You can adapt commands between the two shells with minor modifications
(i.e. ``ls <--> dir``, ``rm -r <--> rmdir /s/q``).

- You may download and install the *all-in-one* archive which contains
both shells configured in a console supporting decent copy-paste and
resizing capabilities (see ref:`all-in-one`_).


IF you have familiarity with v1 release AND IF you already have a full-blown
*python-3 environment* (i.e. *Linux* or the *all-in-one* archive) you can
immediately start working with the following *bash* commands; otherwise
follow the detailed instructions under sections ref:`install`_ and
ref:`usage`_.

.. code-block:: console

## Install co2mpas.
## NOTE: If behind proxy, specify additionally this option:
## --proxy http://user:password@yourProxyUrl:yourProxyPort
##
$ pip install co2mpas

## Where to store input and output files.
## In *Windows* cmd-prompt use `md` command instead.
$ mkdir input output

## Create a template excel-file for inputs.
$ co2mpas template input/vehicle_1.xlsx

###################################################
## Edit generated `./input/vehicle_1.xlsx` file. ##
###################################################

## Run simulator.
$ co2mpas batch input -O output

###################################################
## Inspect generated results inside `./output/`. ##
###################################################


.. _end-opening:
.. contents:: Table of Contents
:backlinks: top
:depth: 4



.. _install:

Install
=======
The installation procedure has 2-stages:

1. Install (or Upgrade) Python (2 choices under *Windows*).
2. Install CO2MPAS:
a. Install (or Upgrade) executable.
b. (optional) Install documents.
c. (optional) Install sources.

On *Windows* you may alternatively install the *all-In-One* archive
instead of performing the above 2 steps separately.


.. _all-in-one:

*All-In-One* Installation under Windows
---------------------------------------
- Download **all-in-one archive** from
http://files.co2mpas.io/.
Ensure that you download the correct 32/64 architecture for your PC
(the 64bit archive CANNOT run on 32bit PCs).

- Use the original `"7z" extraxtor <http://portableapps.com/apps/utilities/7-zip_portable>`_,
since "plain-zip" produces out-of-memory errors when expanding long
directories.
Prefer to **extract it in a folder without any spaces in its path.**

- Run ``INSTALL.bat`` script contained in the root of the unzipped folder.
It will install links for commons CO2MPAS tasks under your *Windows*
Start-Menu.

- Visit the guidelines for its usage: doc(`allinone`)
(also contained within the archive).

.. Note::
If you have downloaded an *all-in-one* from previous version of CO2MPAS
you may upgrade CO2MPAS contained within.
Follow the instructions in the "Upgrade" section, below.


Python Installation
-------------------
If you already have a suitable python-3 installation with all scientific
packages updated to their latest versions, you may skip this 1st stage.

.. Note::
**Installing Python under Windows:**

The program requires CPython-3, and depends on *numpy*, *scipy*, *pandas*,
*sklearn* and *matplotlib* packages, which depend on C-native backends
and need a C-compiler to install from sources.

In *Windows* it is strongly suggested **NOT to install the standard CPython
distribution that comes up first(!) when you google for "python windows"**,
unless you are an experienced python-developer, and you know how to
hunt down pre-compiled dependencies from the *PyPi* repository and/or
from the `Unofficial Windows Binaries for Python Extension Packages
<http://www.lfd.uci.edu/~gohlke/pythonlibs/>`_.

Therefore we suggest that you download one of the following two
*scientific-python* distributions:

#. `WinPython <https://winpython.github.io/>`_ **python-3** (64 bit)
#. `Anaconda <http://continuum.io/downloads>`_ **python-3** (64 bit)



Install WinPython
~~~~~~~~~~~~~~~~~
The *WinPython* distribution is just a collection of the standard pre-compiled
binaries for *Windows* containing all the scientific packages, and much more.
It is not update-able, and has a quasi-regular release-cycle of 3 months.


1. Install the latest **python-3.4+ 64 bit** from https://winpython.github.io/.
Prefer an **installation-folder without any spaces leading to it**.

2. Open the WinPython's command-prompt console, by locating the folder where
you just installed it and run (double-click) the following file::

<winpython-folder>\"WinPython Command Prompt.exe"


3. In the console-window check that you have the correct version of
WinPython installed, and expect a similar response:

.. code-block:: console

> python -V
Python 3.4.3

REM Check your python is indeed where you installed it.
> where python
....


4. Use this console and follow ref:`co2mpas-install`_ instructions, below.



Install Anaconda
~~~~~~~~~~~~~~~~
The *Anaconda* distribution is a non-standard Python environment that
for *Windows* containing all the scientific packages we need, and much more.
It is not update-able, and has a semi-regular release-cycle of 3 months.

1. Install Anaconda **python-3.4+ 64 bit** from http://continuum.io/downloads.
Prefer an **installation-folder without any spaces leading to it**.

.. Note::
When asked by the installation wizard, ensure that *Anaconda* gets to be
registered as the default python-environment for the user's account.

2. Open a *Windows* command-prompt console::

"windows start button" --> `cmd.exe`

3. In the console-window check that you have the correct version of
Anaconda-python installed, by typing:

.. code-block:: console

> python -V
Python 3.4.3 :: Anaconda 2.3.0 (64-bit)

REM Check your python is indeed where you installed it.
> where python
....

4. Use this console and follow ref:`co2mpas-install`_ instructions, below.


.. _co2mpas-install:

CO2MPAS installation
--------------------
1. Install CO2MPAS executable internally into your python-environment with
the following console-commands (there is no prob if the 1st `uninstall`
command fails):

.. code-block:: console

> pip uninstall co2mpas
> pip install co2mpas
Collecting co2mpas
Downloading http://pypi.co2mpas.io/packages/co2mpas-...
...
Installing collected packages: co2mpas
Successfully installed co2mpas-1.2.1

.. Warning::
**Installation failures:**

The previous step require http-connectivity for ``pip`` command to
Python's "standard" repository (https://pypi.python.org/) and to
co2mpas-site (http://files.co2mpas.io).
In case you are behind a **corporate proxy**, you may try one of the methods
described in section `Different ways of installation`_, below.

If all methods to install CO2MPAS fail, re-run ``pip`` command adding
extra *verbose* flags ``-vv``, copy-paste the console-output, and report it
to JRC.

2. Check that when you run ``co2mpas``, the version executed is indeed the one
installed above (check both version-identifiers and paths):

.. code-block:: console

> co2mpas -vV
co2mpas_version: 1.2.1
co2mpas_rel_date: 2016-04-18 22:31:58
co2mpas_path: d:\co2mpas_ALLINONE-64bit-v1.0.5.dev1\Apps\WinPython\python-3.4.3\lib\site-packages\co2mpas
python_path: D:\co2mpas_ALLINONE-64bit-v1.0.5.dev1\WinPython\python-3.4.3
python_version: 3.4.3 (v3.4.3:9b73f1c3e601, Feb 24 2015, 22:44:40) [MSC v.1600 XXX]
PATH: D:\co2mpas_ALLINONE-64bit-v1.0.5.dev1\WinPython...


.. Note::
The above procedure installs the *latest* CO2MPAS, which
**might be more up-to-date than the version described here!**

In that case you can either:

a) Visit the documents for the newer version actually installed.
b) "Pin" the exact version you wish to install with a ``pip`` command
(see section below).


Install extras
~~~~~~~~~~~~~~
Internally CO2MPAS uses an algorithmic scheduler to execute model functions.
In order to visualize the *design-time models* and *run-time workflows*
you need to install the **Graphviz** visualization library from:
http://www.graphviz.org/.

If you skip this step, the ``modelgraph`` sub-command and the ``--plot-workflow``
option would both fail to run (see ref:`debug`_).



Upgrade CO2MPAS
~~~~~~~~~~~~~~~
1. Uninstall (see below) and re-install it.


Uninstall CO2MPAS
~~~~~~~~~~~~~~~~~
To uninstall CO2MPAS type the following command, and confirm it with ``y``:

.. code-block:: console

> pip uninstall co2mpas
Uninstalling co2mpas-<installed-version>
...
Proceed (y/n)?


Re-run the command *again*, to make sure that no dangling installations are left
over; disregard any errors this time.


Different ways of installation
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
You may get multiple versions of CO2MPAS, from various places, but all
require the use of ``pip`` command from a *console* to install:

.. Warning::
In all cases below, remember to uninstall CO2MPAS if it's already installed.

- **Latest STABLE:**
use the default ``pip`` described command above.

- **Latest PRE-RELEASE:**
append the ``--pre`` option in the ``pip`` command.

- **Specific version:**
modify the ``pip`` command like that, with optionally appending ``--pre``:

.. code-block:: console

pip install co2mpas==1.0.1 ... # Other options, like above.

- **Specific branch** from the GitHub-sources:

.. code-block:: console

pip install git+https://github.com/JRCSTU/co2mpas.git@dev

- **Specific commit** from the GitHub-sources:

.. code-block:: console

pip install git+https://github.com/JRCSTU/co2mpas.git@2927346f4c513a

- **Speed-up download**:
append the ``--use-mirrors`` option in the ``pip`` command.

- (for all of the above) When you are **behind an http-proxy**:
append an appropriately adapted option
``--proxy http://user:password@yourProxyUrl:yourProxyPort``.

.. Important::
To avert any security deliberations for this http-proxy "tunnel",
JRC *cryptographically signs* all *final releases*, so that you or
your IT staff may `validate their authenticity
<https://www.davidfischer.name/2012/05/signing-and-verifying-python-packages-with-pgp/>`_
and detect *man-in-the-middle* attacks, however impossible.

- (for all of the above) **Without internet connectivity** or when the above
proxy cmd fails:

1. With with a "regular" browser and when connected to the Internet,
pre-download locally all files present in the ``packages`` folder
located in the desired CO2MPAS version in the *CO2MPAS site*
(e.g. http://files.co2mpas.io/CO2MPAS-1.2.1/packages/).

2. Install *co2mpas*, referencing the above folder.
Assuming that you downloaded the packages in the folder ``path/to/co2mpas_packages``,
use a console-command like this:

.. code-block:: console

pip install co2mpas --no-index -f path/to/co2mpas_packages


Install Multiple versions in parallel
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
In order to run and compare results from different CO2MPAS versions,
you may use `virtualenv <http://docs.python-guide.org/en/latest/dev/virtualenvs/>`_
command.

The `virtualenv` command creates isolated python-environments ("children-venvs")
where in each one you can install a different versions of CO2MPAS.

.. Note::
The `virtualenv` command does NOT run under the "conda" python-environment.
Use the `conda command <http://conda.pydata.org/docs/using/envs.html>`_
in similar manner to create child *conda-environments* instead.


1. Ensure `virtualenv` command installed in your "parent" python-environment,
i.e the "WinPython" you use:

.. code-block:: console

> pip install virtualenv

.. Note::
The ``pip`` command above has to run only once for each parent python-env.
If `virtualenv` is already installed, ``pip`` will exit gracefully.



2. Ensure co2mpas uninstalled in your parent-env:

.. code-block:: console

> pip uninstall co2mpas

.. Warning::
It is important for the "parent" python-env NOT to have CO2MPAS installed!
The reasone is that you must set "children venvs" to inherit all packages
installed on their "parent" (i.e. `numpy` and `pandas`), and you cannot
update any inherited package from within a child-env.


3. Move to the folder where you want your "venvs" to reside and create
the "venv" with this command:

.. code-block:: console

> virtualenv --system-site-packages co2mpas_v1.0.1.venv.venv

The ``--system-site-packages`` option instructs the child-venv to inherit
all "parent" packages (numpy, pandas).

Select a venv's name to signify the version it will contains,
e.g. ``co2mpas_v1.0.1.venv``. The ``.venv`` at the end is not required,
it is just for tagging the *venv* folders.

4. Workaround a `virtualenv bug <https://github.com/pypa/virtualenv/issues/93>`_
with `TCL/TK` on *Windows*!

This is technically the most "difficult" step, and it is required so that
CO2MPAS can open GUI dialog-boxes, such as those for selecting
the *input/output* dialogs.

a. Open with an editor the ``co2mpas_v1.0.1.venv.venv\Scripts\activate.bat`` script,
b. locate the `set PATH=...` line towards the bottom of the file, and
append the following 2 lines::

set "TCL_LIBRARY=d:\WinPython-64bit-3.Y.Y.Y\python-3.Y.Y.amd64\tcl\tcl8.6"
set "TK_LIBRARY=d:\WinPython-64bit-3.Y.Y.Y\python-3.Y.Y.amd64\tcl\tk8.6"

.. Warning::
If you don't modify the *activation-script*, you will receive
the following message while running CO2MPAS::

This probably means that Tcl wasn't installed properly.

Of course you have to **adapt the paths above** to match the `TCL` & `TK`
folder in your parent python-env. For instance, in ALLINONE the lines
above would become::

set "TCL_LIBRARY=%WINPYTHON%\tcl\tcl8.6"
set "TK_LIBRARY=%WINPYTHON%\tcl\tk8.6"

.. Tip::
The ALLINONE archives already include this workaround ;-)


5. "Activate" the new "venv" by running the following command
(notice the dot(``.``) at the begining of the command):

.. code-block:: console

> .\co2mpas_v1.0.1.venv.venv\Scripts\activate.bat

Or type this in *bash*:

.. code-block:: console

$ source co2mpas_v1.0.1.venv.venv\Scripts\activate.bat

You must now see that your prompt has been prefixed with the venv's name.


6. Install the co2mpas version you want inside the activated venv.
See the ref:`co2mpas-install`_ section, above.

Don't forget to check that what you get when running co2mpas is what you
installed.

7. To "deactivate" the active venv, type:

.. code-block:: console

> deactivate

The prompt-prefix with the venv-name should now dissappear. And if you
try to invoke ``co2mpas``, it should fail.



.. Tip::
- Repeat steps 2-->5 to create venvs for different versions of co2mpas.
- Use steps (6: Activate) and (9: Deactivate) to switch between different
venvs.


Autocompletion
--------------
In order to press ``[Tab]`` and get completions, do the following in your
environment (ALLINONE is pre-configured with them):

- For the |clink|_ environment, on `cmd.exe`, add the following *lua* script
inside clink's profile folder: ``clink/profile/co2mpas_autocompletion.lua``

.. code-block:: lua

--[[ clink-autocompletion for CO2MPAS
--]]
local handle = io.popen('co2mpas-autocompletions')
words_str = handle:read("*a")
handle:close()

function words_generator(prefix, first, last)
local cmd = 'co2mpas'
local prefix_len = #prefix

--print('P:'..prefix..', F:'..first..', L:'..last..', l:'..rl_state.line_buffer)
if prefix_len == 0 or rl_state.line_buffer:sub(1, cmd:len()) ~= cmd then
return false
end

for w in string.gmatch(words_str, "%S+") do
-- Add matching app-words.
--
if w:sub(1, prefix_len) == prefix then
clink.add_match(w)
end

-- Add matching files & dirs.
--
full_path = true
nf = clink.match_files(prefix..'*', full_path)
if nf > 0 then
clink.matches_are_files()
end
end
return clink.match_count() > 0
end

sort_id = 100
clink.register_match_generator(words_generator)


- For the *bash* shell just add this command in your file(`~/.bashrc`)
(or type it every time you open a new console):

.. code-block:: console

complete -fdev -W "`co2mpas-autocompletions`" co2mpas


.. |clink| replace:: *Clink*
.. _clink: http://mridgers.github.io/clink/


.. _usage:

Usage
=====
.. Note::
The following commands are for the **bash console**, specifically tailored
for the **all-in-one** archive. In `cmd.exe` the commands are rougly similar,
but remember to substitute the slashes (`/`) in paths with backslashes(`\\`).

The doc(`allinone`) contains additionally batch-files
(e.g. file(`RUN_CO2MPAS.bat`), file(`NEW_TEMPLATE.bat`), etc)
that offer roughly the same capabillities described below.
When you double-click them, the output from these commands gets to be
written in the file(`ALLINONE/CO2MPAS/co2mpas.log`) file.



First ensure that the latest version of CO2MPAS is properly installed, and that
its version match the version declared on this file.

The main entry for the simulator is the ``co2mpas`` console-command,
which **is not visible, but it is installed in your PATH**.
To get the syntax of the ``co2mpas`` console-command, open a console where
you have installed CO2MPAS (see ref:`install`_ above) and type::

Predict NEDC CO2 emissions from WLTP.

:Home: http://co2mpas.io/
:Copyright: 2015-2016 European Commission (JRC-IET <https://ec.europa.eu/jrc/en/institutes/iet>
:License: EUPL 1.1+ <https://joinup.ec.europa.eu/software/page/eupl>

Use the `batch` sub-command to simulate a vehicle contained in an excel-file.


USAGE:
co2mpas batch [-v | --logconf=<conf-file>] [--gui]
[--overwrite-cache]
[--out-template=<xlsx-file> | --charts]
[--plot-workflow] [-O=<output-folder>]
[--only-summary] [--soft-validation]
[<input-path>]...
co2mpas demo [-v | --logconf=<conf-file>] [--gui]
[-f] [<output-folder>]
co2mpas template [-v | --logconf=<conf-file>] [--gui] [-f] [<excel-file-path> ...]
co2mpas ipynb [-v | --logconf=<conf-file>] [--gui] [-f] [<output-folder>]
co2mpas modelgraph [-v | --logconf=<conf-file>] [-O=<output-folder>]
(--list | [--graph-depth=<levels>] [<models> ...])
co2mpas sa [-v | --logconf=<conf-file>] [-f] [-O=<output-folder>]
[--soft-validation] [--only-summary] [--overwrite-cache]
[--out-template=<xlsx-file> | --charts]
[<input-path>] [<input-params>] [<defaults>]...
co2mpas [--verbose | -v] (--version | -V)
co2mpas --help

Syntax tip:
The brackets `[ ]`, parens `( )`, pipes `|` and ellipsis `...` signify
"optional", "required", "mutually exclusive", and "repeating elements";
for more syntax-help see: http://docopt.org/


OPTIONS:
<input-path> Input xlsx-file or folder. Assumes current-dir if missing.
-O=<output-folder> Output folder or file [default: .].
--gui Launches GUI dialog-boxes to choose Input, Output
and Options. [default: False].
--only-summary Do not save vehicle outputs, just the summary file.
--overwrite-cache Overwrite the cached file.
--charts Add basic charts to output file.
--soft-validation Validate only partially input-data (no schema).
--out-template=<xlsx-file> Clone the given excel-file and appends model-results into it.
By default, results are appended into an empty excel-file.
Use `--out-template=-` to use input excel-files as templates.
--plot-workflow Open workflow-plot in browser, after run finished.
-l, --list List available models.
--graph-depth=<levels> An integer to Limit the levels of sub-models plotted
(no limit by default).
-f, --force Overwrite template/demo excel-file(s).

Miscellaneous:
-h, --help Show this help message and exit.
-V, --version Print version of the program, with --verbose
list release-date and installation details.
-v, --verbose Print more verbosely messages - overridden by --logconf.
--logconf=<conf-file> Path to a logging-configuration file, according to:
https://docs.python.org/3/library/logging.config.html#configuration-file-format
If the file-extension is '.yaml' or '.yml', it reads a dict-schema from YAML:
https://docs.python.org/3.5/library/logging.config.html#logging-config-dictschema


SUB-COMMANDS:
batch Simulate vehicle for all <input-path> excel-files & folder.
If no <input-path> given, reads all excel-files from current-dir.
Read this for explanations of the param names:
http://co2mpas.io/explanation.html#excel-input-data-naming-conventions
demo Generate demo input-files for the `batch` cmd inside <output-folder>.
template Generate "empty" input-file for the `batch` cmd as <excel-file-path>.
ipynb Generate IPython notebooks inside <output-folder>; view them with cmd:
jupyter --notebook-dir=<output-folder>
modelgraph List or plot available models. If no model(s) specified, all assumed.
sa (undocumented - subject to change)


EXAMPLES::

# Don't enter lines starting with `#`.

# Create work folders and then fill `input` with sample-vehicles:
md input output
co2mpas demo input

# Launch GUI dialog-boxes on the sample-vehicles just created:
co2mpas batch --gui input

# or specify them with output-charts and workflow plots:
co2mpas batch input -O output --charts --plot-workflow

# Create an empty vehicle-file inside `input` folder:
co2mpas template input/vehicle_1.xlsx

# View a specific submodel on your browser:
co2mpas modelgraph co2mpas.model.physical.wheels.wheels

# View full version specs:
co2mpas -vV




The default sub-command (``batch``) accepts either a single **input-excel-file**
or a folder with multiple input-files for each vehicle, and generates a
**summary-excel-file** aggregating the major result-values from these vehicles,
and (optionally) multiple **output-excel-files** for each vehicle run.


Demo files
----------
The simulator contains input-files for demo-vehicles that are a nice
starting point to try out:

== ====== ====== ========== ========== =========== === ==== ==========
id manual precon cal WLTP-H cal WLTP-L theoretical S/S BERS correct_f0
== ====== ====== ========== ========== =========== === ==== ==========
0 X X X X X
1 X X X X X
2 X X X
3 X X X X X
4 X X X
5 X X X X X
6 X X X X
7 X X X
8 X X X X
9 X X
10 X X X X X X
== ====== ====== ========== ========== =========== === ==== ==========

To run them, do the following:

1. Choose a folder where you will store the *input* and *output* files:

.. code-block:: console

## Skip this if ``tutorial`` folder already exists.
$ mkdir tutorial
$ cd tutorial

## Skip also this if folders exist.
$ mkdir input output

.. Note::
The input & output folders do not have to reside in the same parent,
neither to have these names.
It is only for demonstration purposes that we decided to group them both
under a hypothetical ``some-folder``.

2. Create the demo vehicles inside the *input-folder* with the ``demo``
sub-command:


.. code-block:: console

$ co2mpas demo input
INFO:co2mpas.__main__:Creating INPUT-DEMO file 't\co2mpas_demo-0.xlsx'...
INFO:co2mpas.__main__:Creating INPUT-DEMO file 't\co2mpas_demo-1.xlsx'...
INFO:co2mpas.__main__:Creating INPUT-DEMO file 't\co2mpas_demo-10.xlsx'...
INFO:co2mpas.__main__:Creating INPUT-DEMO file 't\co2mpas_demo-2.xlsx'...
INFO:co2mpas.__main__:Creating INPUT-DEMO file 't\co2mpas_demo-3.xlsx'...
INFO:co2mpas.__main__:Creating INPUT-DEMO file 't\co2mpas_demo-4.xlsx'...
INFO:co2mpas.__main__:Creating INPUT-DEMO file 't\co2mpas_demo-5.xlsx'...
INFO:co2mpas.__main__:Creating INPUT-DEMO file 't\co2mpas_demo-6.xlsx'...
INFO:co2mpas.__main__:Creating INPUT-DEMO file 't\co2mpas_demo-7.xlsx'...
INFO:co2mpas.__main__:Creating INPUT-DEMO file 't\co2mpas_demo-8.xlsx'...
INFO:co2mpas.__main__:Creating INPUT-DEMO file 't\co2mpas_demo-9.xlsx'...
INFO:co2mpas.__main__:You may run DEMOS with:
co2mpas batch input

3. Run the simulator on all demo-files (note, it might take considerable time):

.. code-block:: console

$ co2mpas batch input -O output
Processing ['input'] --> 'output'...
Processing: co2mpas_demo-0
...
...
Done! [499.579 sec]


4. Inspect the results (explained in the next section):

.. code-block:: console

$ start output/*summary.xlsx ## More summaries might exist in the folder from previous runs.
$ start output ## View the folder with all files generated.


Output files
------------
The output-files produced on each run are the following:

- One file per vehicle, named as `<timestamp>-<inp-fname>.xls`:
This file contains all the inputs and calculation results for each vehicle
contained in the batch-run: scalar-parameters and time series for target,
calibration and prediction phases, for all cycles.
In addition, the file contains all the specific submodel-functions that
generated the results, a comparison summary, and information on the python
libraries installed on the system (for investigating reproducibility issues).

- A Summary-file named as `<timestamp>-summary.xls`:
Major CO2 emissions values, optimized CO2 parameters values and
success/fail flags of CO2MPAS submodels for all vehicles in the batch-run.

.. tip::

Additionally, a sample output file is provide here:
http://files.co2mpas.io/CO2MPAS-1.2.1/CO2MPAS-empty_output-1.2.1.xlsx


Entering new vehicles
---------------------
You may modify the samples vehicles and run again the model.
But to be sure that your vehicle does not contain by accident any of
the sample-data, use the ``template`` sub-command to make an *empty* input
excel-file:

1. Decide the *input/output* folders. Assuming we are still in the ``tutorial``
folder and we wish to re-use the ``input/output`` folders from the example
above, we may clear all their contents with this:

.. code-block:: console

$ rm -r ./input/* ./output/* ## Replace `rm` with `del` in *Windows* (`cmd.exe`)


2. Create an empty vehicle template-file (eg. ``vehicle_1.xlsx``) inside
the *input-folder* with the ``template`` sub-command:

.. code-block:: console

$ co2mpas template input/vehicle_1.xlsx ## Note that here we specify the filename, not the folder!
Creating TEMPLATE INPUT file 'input/vehicle_1.xlsx'...


3. Open the template excel-file to fill-in your vehicle data
(and save it afterwards):

.. code-block:: console

$ start input/vehicle_1.xlsx ## Opens the excel-file. Use `start` in *cmd.exe*.

The generated file contains help descriptions to help you populate it
with vehicle data. For items where an array of values is required
(i.e. gear-box ratios) you may reference different parts of
the spreadsheet following the syntax of the `"xlref" mini-language
<https://pandalone.readthedocs.org/en/latest/reference.html#module-pandalone.xleash>`_.

.. tip::
You may also read the `"annotated" input excel-file
<http://files.co2mpas.io/CO2MPAS-1.2.1/co2mpas-annotated_input-1.2.1.xls>`_
to get an understanding of each scalar paramet and series required,
but **DO NOT USE THIS "fatty" xl-file (~10Mb) when running the model.**

For an explanation of the naming of the fields, read below the
ref:`excel-model`_ section

You may repeat these last 2 steps if you want to add more vehicles in
the *batch-run*.

4. Run the simulator. Specify the single excel-file as input:

.. code-block:: console

$ co2mpas batch ./input/vehicle_1.xlsx -O output
Processing './input/vehicle_1.xlsx' --> 'output'...
Processing: vehicle_1
...
Done! [12.938986 sec]

5. Assuming you do receive any error, you may now inspect the results:

.. code-block:: console

$ start output/*summary.xlsx ## More summaries might open from previous runs.
$ start output ## View all files generated (see below).


6. In the case of errors, or if the results are not satisfactory, repeat the
above procedure from step 3 to modify the vehicle and re-run the model.
See also ref:`debug`_, below.


Synchronizing time-series
-------------------------
The model might fail in case your time-series signals are time-shifted and/or
with different sampling rates. Even if the run succeeds, the results will not
be accurate enough.

As an aid tool, you may use the ``datasync`` command-line tool to "synchronize"
your *data-tables*. This command reads one or more tables from excel-files and
synchronizes their columns. The syntax of this utility command is given
by typing ``datasync --help`` in the command line
(listing below just the main fields)::

Shift and resample excel-tables; see http://co2mpas.io/usage.html#Synchronizing-time-series.

Usage:
datasync [(-v | --verbose) | --logconf <conf-file>]
[--force | -f] [--no-clone] [--prefix-cols] [-O <output>]
<x-label> <y-label> <ref-table> [<sync-table> ...]
datasync [--verbose | -v] (--version | -V)
datasync --help

Options:
<x-label> Column-name of the common x-axis (e.g. 'times') to be resampled if needed.
<y-label> Column-name of y-axis cross-correlated between all <sync-table>
and <ref-table>.
<ref-table> The reference table, in *xl-ref* notation (usually given as `file#sheet!`);
synced columns will be appended into this table.
The captured table must contain <x_label> & <y_label> as column labels.
If hash(`#`) symbol missing, assumed as file-path and
the table is read from its 1st sheet .
<sync-table> Sheets to be synced in relation to <ref-table>, also in *xl-ref* notation.
All tables must contain <x_label> & <y_label> as column labels.
Each xlref may omit file or sheet-name parts; in that case,
those from the previous xlref(s) are reused.
If hash(`#`) symbol missing, assumed as sheet-name.
If none given, all non-empty sheets of <ref-table> are synced
against the 1st one.


All input tables must share 2 common columns: ``<x-label>`` and ``<y-label>``, as if
those tables describe 2D cartesian data, with a common *X-axis* and multiple
data-series on the *Y-Axis*.

.. Tip:: The ``<x-label>`` usually refers to the "time" dimension.

The 1st table given (`<ref-table>`) is considered to contain the "reference"
X/Y values; the data-columns to shift-and-resample are contained in one
or more tables (``<sync-table>``) specified subsequently in the command line,
that are possibly read from different excel work-books.

- *Shifting* is based on the *cross-correlation* of ``<y-label>`` columns;
- *resampling* is based on the values of ``<x-label>`` columns among the
different tables.

All tables are read from excel-sheets using the `xl-ref syntax
<https://pandalone.readthedocs.org/en/latest/reference.html#module-pandalone.xleash>`_,
which is best explained with some examples.


Examples
~~~~~~~~
- Read the full contents from all `wbook.xlsx` sheets as tables and
sync their columns using the table from the 1st sheet as reference::

datasync times velocity folder/Book.xlsx

- Sync `Sheet1` using `Sheet3` as reference::

datasync times velocity wbook.xlsx#Sheet3! Sheet1!

- The same as above but with integeres used to index excel-sheets::

datasync times velocity wbook.xlsx#2! 0

.. Note:: Sheet-indices are zero based!

- A more complex *xlr-ref* example which reads the synce-table from sheet2
of wbook-2 starting at D5 cell, or more Down 'n Right if that was empty,
till the first empty cell Down n Right, and synchronizes that based on
1st sheet of wbook-1::

datasync times velocity wbook-1.xlsx wbook-2.xlsx#0!D5(DR):..(DR)

- Typical usage for CO2MPAS velocity time-series from Dyno and OBD::

datasync -O ../output times velocities ../input/book.xlsx#WLTP-H WLTP-H_OBD



Using custom output xl-files as templates
-----------------------------------------
You may have defined customized xl-files for summarizing time-series and
scalar parameters. To have CO2MPAS fill those "output-template" files with
its results, execute it with the ``--out-template`` option.


To create/modify one output-template yourself, do the following:

1. Open a typical CO2MPAS output-file for some vehicle.

2. Add one or more sheets and specify/referring CO2MPAS result-data using
`named-ranges <https://www.google.it/search?q=excel+named-ranges>`_.

.. Warning::
Do not use simple/absolute excel references (e.g. "=B2").
Use excel functions (indirect, lookup, offset, etc.) and array-functions
together with string references to the named ranges
(e.g. "=indirect("nedc_predictions_time_series!_fuel_consumptions")").

3. (Optional) Delete the old sheets and save your file.

4. Use that file together with the ``--out-template`` argument.


Launch CO2MPAS from Jupyter(aka IPython)
----------------------------------------
You may enter the data for a single vehicle and run its simulation, plot its
results and experiment in your browser using `IPython <http://ipython.org/>`_.

The usage pattern is similar to "demos" but requires to have **ipython**
installed:

1. Ensure *ipython* with *notebook* "extra" is installed:

.. Warning::
This step requires too many libraries to provide as standalone files,
so unless you have it already installed, you will need a proper
*http-connectivity* to the standard python-repo.

.. code-block:: console

$ pip install ipython[notebook]
Installing collected packages: ipython[notebook]
...
Successfully installed ipython-x.x.x notebook-x.x.x


2. Then create the demo ipython-notebook(s) into some folder
(i.e. assuming the same setup from above, ``tutorial/input``):

.. code-block:: console

$ pwd ## Check our current folder (``cd`` alone for Windows).
.../tutorial

$ co2mpas ipynb ./input

3. Start-up the server and open a browser page to run the vehicle-simulation:

.. code-block:: console

$ ipython notebook ./input

4. A new window should open to your default browser (AVOID IEXPLORER) listing
the ``simVehicle.ipynb`` notebook (and all the demo xls-files).
Click on the ``*.ippynb`` file to "load" the notebook in a new tab.

The results are of a simulation run already pre-generated for this notebook
but you may run it yourself again, by clicking the menu::

"menu" --> `Cell` --> `Run All`

And watch it as it re-calculates *cell* by cell.

5. You may edit the python code on the cells by selecting them and clicking
``Enter`` (the frame should become green), and then re-run them,
with ``Ctrl + Enter``.

Navigate your self around by taking the tutorial at::

"menu" --> `Help` --> `User Interface Tour`

And study the example code and diagrams.

6. When you have finished, return to the console and issue twice ``Ctrl + C``
to shutdown the *ipython-server*.


.. _debug:

Debugging and investigating results
-----------------------------------

- Make sure that you have installed `graphviz`, and when running the simulation,
append also the ``--plot-workflow`` option.

- Use the ``modelgraph`` sub-command to plot the offending model (or just
out of curiosity). For instance:

.. code-block:: console

$ co2mpas modelgraph co2mpas.model.physical.wheels.wheels

.. _static/Wheel%20model/Wheel_model.gv.svg
:alt: Flow-diagram Wheel-to-Engine speed ratio calculations.
:height: 240
:width: 320

- Inspect the functions mentioned in the workflow and models and search them
in `CO2MPAS documentation <http://files.co2mpas.io/>`_ ensuring you are
visiting the documents for the actual version you are using.


.. _explanation:

Model
=====
Execution Model
---------------
The execution of CO2MPAS model for a single vehicle is a stepwise procedure
of 3 stages: ``precondition``, ``calibration``, and ``prediction``.
These are invoked repeatedly, and subsequently combined, for the various cycles,
as shown in the "active" flow-diagram of the execution, below:

.. _static/CO2MPAS%20model/CO2MPAS_model.gv.svg
:alt: Flow-diagram of the execution of various Stages and Cycles sub-models.
:width: 640

.. Tip:: The models in the diagram are nested; explore by clicking on them.

1. **Precondition:** identifies the initial state of the vehicle by running
a preconditioning *WLTP* cycle, before running the *WLTP-H* and *WLTP-L*
cycles.
The inputs are defined by the ``input.precondition.wltp_p`` node,
while the outputs are stored in ``output.precondition.wltp_p``.

2. **Calibration:** the scope of the stage is to identify, calibrate and select
(see next sections) the best physical models from the WLTP-H and WLTP-L
inputs (``input.calibration.wltp_x``).
If some of the inputs needed to calibrate the physical models are not
provided (e.g. ``initial_state_of_charge``), the model will select the
missing ones from precondition-stage's outputs
(``output.precondition.wltp_p``).
Note that all data provided in ``input.calibration.wltp_x`` overwrite those
in ``output.precondition.wltp_p``.

3. **Prediction:** executed for the NEDC and as well as for the WLTP-H and
WLTP-L cycles. All predictions use the ``calibrated_models``. The inputs to
predict the cycles are defined by the user in ``input.prediction.xxx`` nodes.
If some or all inputs for the prediction of WLTP-H and WLTP-L cycles are not
provided, the model will select from ```output.calibration.wltp_x`` nodes a
minimum set required to predict CO2 emissions.

.. _excel-model:

Excel input: data naming conventions
------------------------------------
This section describes the data naming convention used in the CO2MPAS template
(``.xlsx`` file). In it, the names used as **sheet-names**, **parameter-names**
and **column-names** are "sensitive", in the sense that they construct a
*data-values tree* which is then fed into into the simulation model as input.
These names are splitted in "parts", as explained below with examples:

- **sheet-names** parts::

input.precodintion.WLTP-H
└─┬─┘ └────┬─────┘ └─┬──┘
usage───────────┘ │ │
stage────────────────────┘ │
cycle──────────────────────────────┘


All 3 parts above are optional, but at least one of them must be present on
a **sheet-name**; those parts are then used as defaults for all **parameter-names**
contained in that sheet.

- **parameter-names**/**columns-names** parts::

target.prediction.initial_state_of_charge.WLTP-H
└─┬─┘ └────┬────┘ └──────────┬──────────┘ └──┬─┘
usage(optional)─┘ │ │ │
stage(optional)──────────┘ │ │
parameter──────────────────────────────────┘ │
cycle(optional)────────────────────────────────────────────┘

OR with the last 2 parts reversed::

target.prediction.WLTP-H.initial_state_of_charge
└──┬─┘ └──────────┬──────────┘
cycle(optional)────────────────────┘ │
parameter─────────────────────────────────────────┘

.. note::
- The dot(``.``) may be replaced by space.
- The **usage** and **stage** parts may end with an ``s``, denoting plural,
and are case-insensitive, e.g. ``Inputs``.


Description of the name-parts
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
1. **usage:**

- ``input`` [default]: values provided by the user as input to CO2MPAS.
- ``data``: values selected (see previous section) to calibrate the models
and to predict the CO2 emission.
- ``output``: CO2MPAS precondition, calibration, and prediction results.
- ``target``: reference-values (**NOT USED IN CALIBRATION OR PREDICTION**) to
be compared with the CO2MPAS results. This comparison is performed in the
*report* sub-model by ``compare_outputs_vs_targets()`` function.

2. **stage:**

- ``precondition`` [imposed when: ``wltp-p`` is specified as **cycle**]:
data related to the precondition stage.
- ``calibration`` [default]: data related to the calibration stage.
- ``prediction`` [imposed when: ``nedc`` is specified as **cycle**]:
data related to the prediction stage.

3. **cycle:**

- ``nedc`` data related to the *NEDC* cycle.
- ``wltp-h`` data related to the *WLTP High* cycle.
- ``wltp-l`` data related to the *WLTP Low* cycle.
- ``wltp-precon``: data related to the preconditioning *WLTP* cycle.
- ``wltp-p``: is a shortcut of ``wltp-precon``.
- ``wltp``: is a shortcut to set values for both ``wltp-h`` and ``wltp-l``
cycles.
- ``all`` [default]: is a shortcut to set values for ``nedc``, ``wltp``,
and ``wltp-p`` cycles.

4. **param:** any data node name (e.g. ``vehicle_mass``) used in the physical
model.

Sheet types
~~~~~~~~~~~
There are two sheet types, which are parsed according to their contained
data:

- **parameters** [parsed range is ``#B2:C_``]: scalar or not time-depended
values (e.g. ``r_dynamic``, ``gear_box_ratios``, ``full_load_speeds``).
- **time-series** [parsed range is ``#A2:__``]: time-depended values (e.g.
``times``, ``velocities``, ``gears``). Columns without values are skipped.
**COLUMNS MUST HAVE THE SAME LENGTH!**

When **cycle** is missing in the **sheet-name**, the sheet is parsed as
**parameters**, otherwise it is parsed as **time-series**.

Calibrated Physical Models
--------------------------
There are potentially eight models calibrated from input scalar-values and
time-series (see doc(`reference`)):

1. *AT_model*,
2. *electric_model*,
3. *clutch_torque_converter_model*,
4. *co2_params*,
5. *engine_cold_start_speed_model*,
6. *engine_coolant_temperature_model*,
7. *engine_speed_model*, and
8. *start_stop_model*.

Each model is calibrated separately over *WLTP_H* and *WLTP_L*.
A model can contain one or several functions predicting different quantities.
For example, the electric_model contains the following functions/data:

- *alternator_current_model*,
- *alternator_status_model*,
- *electric_load*,
- *max_battery_charging_current*,
- *start_demand*.

These functions/data are calibrated/estimated based on the provided input
(in the particular case: *alternator current*, *battery current*, and
*initial SOC*) over both cycles, assuming that data for both WLTP_H and WLTP_L
are provided.

.. Note::
The ``co2_params`` model has a third possible calibration configuration
(so called `ALL`) using data from both WLTP_H and WLTP_L combined
(when both are present).


Model selection
---------------
To select which is the best calibration (from *WLTP_H* or *WLTP_L* or *ALL*)
to be used in the prediction phase, the results of each stage are compared
against the provided input data (used in the calibration).
The calibrated models are THEN used to recalculate (predict) the inputs of the
*WLTP_H* and *WLTP_L* cycles. A **score** (weighted average of all computed
metrics) is attributed to each calibration of each model as a result of this
comparison.

.. Note::
The overall score attributed to a specific calibration of a model is
the average score achieved when compared against each one of the input
cycles (*WLTP_H* and *WLTP_L*).

For example, the score of `electric_model` calibrated based on *WLTP_H*
when predicting *WLTP_H* is 20, and when predicting *WLTP_L* is 14.
In this case the overall score of the the `electric_model` calibrated
based on *WLTP_H* is 17. Assuming that the calibration of the same model
over *WLTP_L* was 18 and 12 respectively, this would give an overall score
of 15.

In this case the second calibration (*WLTP_L*) would be chosen for
predicting the NEDC.

In addition to the above, a success flag is defined according to
upper or lower limits of scores which have been defined empirically by the JRC.
If a model fails these limits, priority is then given to a model that succeeds,
even if it has achieved a worse score.

The following table describes the scores, targets, and metrics for each model:

.. _static/CO2MPAS_model_score_targets_limits.png
:width: 600 px
:align: center