gtsam/cython/README.md

This is the Cython/Python wrapper around the GTSAM C++ library.

INSTALL
=======
- This wrapper needs Cython(>=0.25), numpy and eigency, which can be installed 
as follows:

```bash
 cd <gtsam_folder>/cython
 pip install -r requirements.txt
 pip install eigency
```

Note: Currently there's some issue with including eigency in requirements.txt

- Build and install gtsam using cmake with GTSAM_INSTALL_CYTHON_TOOLBOX enabled
Note: The wrapped module will be installed to GTSAM_CYTHON_INSTALL_PATH, which is
by default: <your CMAKE_INSTALL_PREFIX>/cython


UNIT TESTS
==========
The Cython toolbox also has a small set of unit tests located in the
test directory. To run them:

```bash
 cd <your GTSAM_CYTHON_INSTALL_PATH>
 python -m unittest discover
```

WRITING YOUR OWN SCRIPTS
========================
See the tests for examples.

## Some important notes:

- Vector/Matrix: Due to a design choice of eigency, numpy.array matrices with the default order='A'
will always be transposed in C++ no matter how you transpose it in Python. Use order='F', or use
two functions Vector and Matrix in cython/gtsam/utils/np_utils.py for your conveniences. These two functions
also help to avoid a common but very subtle bug of using integers when creating numpy arrays, 
e.g. np.array([1,2,3]). These can't be an input for gtsam functions as they only accept floating-point arrays.
For more details, see: https://github.com/wouterboomsma/eigency#storage-layout---why-arrays-are-sometimes-transposed

- Inner namespace: Classes in inner namespace will be prefixed by <innerNamespace>_ in Python.
Examples: noiseModel_Gaussian, noiseModel_mEstimator_Tukey

- Casting from a base class to a derive class must be done explicitly.
Examples: 
```Python
      noiseBase = factor.get_noiseModel()
      noiseGaussian = dynamic_cast_noiseModel_Gaussian_noiseModel_Base(noiseBase)       
```

WRAPPING YOUR OWN PROJECT THAT USES GTSAM
=========================================

- Set PYTHONPATH to include ${GTSAM_CYTHON_INSTALL_PATH}
  + so that it can find gtsam Cython header: gtsam/gtsam.pxd

- Create your setup.py.in as follows:
```python
from distutils.core import setup
from distutils.extension import Extension
from Cython.Build import cythonize
import eigency

include_dirs = ["${CMAKE_SOURCE_DIR}/cpp", "${CMAKE_BINARY_DIR}"]
include_dirs += "${GTSAM_INCLUDE_DIR}".split(";")
include_dirs += eigency.get_includes(include_eigen=False)

setup(
    ext_modules=cythonize(Extension(
        "your_module_name",
        sources=["your_module_name.pyx"],
        include_dirs= include_dirs,
        libraries=['gtsam'],
        library_dirs=["${GTSAM_DIR}/../../"],
        language="c++",
        extra_compile_args=["-std=c++11"])),
)

```

- In your CMakeList.txt
```cmake
find_package(GTSAM REQUIRED) # Make sure gtsam's install folder is in your PATH
set(CMAKE_MODULE_PATH "${CMAKE_MODULE_PATH}" "${GTSAM_DIR}/../GTSAMCMakeTools")
# Wrap
include(GtsamCythonWrap)
wrap_and_install_library_cython("your_project_interface.h"
                                "from gtsam.gtsam cimport *" # extra import of gtsam/gtsam.pxd Cython header
                                "path_to_your_setup.py.in"
                                "your_install_path"
```



KNOWN ISSUES
============
  - Doesn't work with python3 installed from homebrew
    - size-related issue: can only wrap up to a certain number of classes: up to mEstimator!
    - Guess: 64 vs 32b? disutils Compiler flags?
  - Bug with Cython 0.24: instantiated factor classes return FastVector<size_t> for keys(), which can't be casted to FastVector<Key>
    - Upgrading to 0.25 solves the problem 
  - Need default constructor and default copy constructor for almost every classes... :(
    - support these constructors by default and declare "delete" for special classes?


TODO
=====
☐ Unify cython/gtsam.h and the original gtsam.h
  - 25-11-16:
    Try to unify but failed. Main reasons are: Key/size_t, std containers, KeyVector/KeyList/KeySet. 
    Matlab doesn't need to know about Key, but I can't make Cython to ignore Key as it couldn't cast KeyVector, i.e. FastVector<Key>,
    to FastVector<size_t>. 

Completed/Cancelled:
✔ CMake install script @done (25-11-16 02:30)
✘ [REFACTOR] better name for uninstantiateClass: very vague!! @cancelled (25-11-16 02:30) -- lazy
✘ forward declaration? @cancelled (23-11-16 13:00) - nothing to do, seem to work?
✔ wrap VariableIndex: why is it in inference? If need to, shouldn't have constructors to specific FactorGraphs @done (23-11-16 13:00)
✔ Global functions @done (22-11-16 21:00)
✔ [REFACTOR] typesEqual --> isSameSignature @done (22-11-16 21:00)
✔ Proper overloads (constructors, static methods, methods) @done (20-11-16 21:00)
✔ Allow overloading methods. The current solution is annoying!!! @done (20-11-16 21:00)
✔ Casting from parent and grandparents @done (16-11-16 17:00)
✔ Allow overloading constructors. The current solution is annoying!!! @done (16-11-16 17:00)
✔ Support "print obj" @done (16-11-16 17:00)
✔ methods for FastVector: at, [], ...  @done (16-11-16 17:00)
✔ Cython: Key and size_t: traits<size_t> doesn't exist @done (16-09-12 18:34)
✔ KeyVector, KeyList, KeySet... @done (16-09-13 17:19)
✔ [Nice to have] parse typedef @done (16-09-13 17:19)
✔ ctypedef at correct places @done (16-09-12 18:34)
✔ expand template variable type in constructor/static methods? @done (16-09-12 18:34)
✔ NonlinearOptimizer: copy constructor deleted!!! @done (16-09-13 17:20)
✔ Value: no default constructor @done (16-09-13 17:20)
✔ ctypedef PriorFactor[Vector] PriorFactorVector @done (16-09-19 12:25)
✔ Delete duplicate methods in derived class @done (16-09-12 13:38)
✔ Fix return properly @done (16-09-11 17:14)
 ✔ handle pair @done (16-09-11 17:14)
✔ Eigency: ambiguous call: A(const T&) A(const Vector& v) and Eigency A(Map[Vector]& v) @done (16-09-11 07:59)
✔ Eigency: Constructor: ambiguous construct from Vector/Matrix @done (16-09-11 07:59)
✔ Eigency: Fix method template of Vector/Matrix: template argument is [Vector] while arugment is Map[Vector] @done (16-09-11 08:22)
✔ Robust noise: copy assignment operator is deleted because of shared_ptr of the abstract Base class @done (16-09-10 09:05)
✘ Cython: Constructor: generate default constructor? (hack: if it's serializable?) @cancelled (16-09-13 17:20)
✘ Eigency: Map[] to Block @created(16-09-10 07:59) @cancelled (16-09-11 08:28)

- inference before symbolic/linear
- what's the purpose of "virtual" ??

Installation:
  ☐ Prerequisite: 
    - Users create venv and pip install requirements before compiling
    - Wrap cython script in gtsam/cython folder
  ☐ Install built module into venv?